Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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33 pages, 467 KiB  
Review
Quantitative Approaches in Assessing Soil Organic Matter Dynamics for Sustainable Management
by Yves Theoneste Murindangabo, Marek Kopecký, Petr Konvalina, Mohammad Ghorbani, Kristýna Perná, Thi Giang Nguyen, Jaroslav Bernas, Sadia Babar Baloch, Trong Nghia Hoang, Festus Onyebuchi Eze and Shahzaib Ali
Agronomy 2023, 13(7), 1776; https://doi.org/10.3390/agronomy13071776 - 30 Jun 2023
Cited by 3 | Viewed by 1787
Abstract
The aim of this study was to provide an overview of the approaches and methods used to assess the dynamics of soil organic matter (SOM). This included identifying relevant processes that describe and estimate SOM decomposition, lability, and humification for the purpose of [...] Read more.
The aim of this study was to provide an overview of the approaches and methods used to assess the dynamics of soil organic matter (SOM). This included identifying relevant processes that describe and estimate SOM decomposition, lability, and humification for the purpose of sustainable management. Various existing techniques and models for the qualitative and quantitative assessment of SOM were evaluated to gain a better understanding of advances in organic matter transformation. This evaluation aimed to identify the strengths, limitations, and applications of these techniques and models, and to highlight new research directions in the field. Quantitative analysis of SOM can be performed using various parameters, including oxidation kinetics, lability, carbon management index, humification degree, humification index, and humification ratio. On the other hand, qualitative evaluation of SOM can involve techniques such as oxidizability, high-performance size-exclusion chromatography, electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry, visual examination, smell, assessment of microorganism content, plant growth, cation exchange capacity, type of organic material, and decomposition. These techniques and parameters provide valuable insights into the characteristics and transformation of SOM, enabling a comprehensive understanding of its dynamics. Evaluating SOM dynamics is of utmost importance as it is a determining factor for soil health, fertility, organic matter stability, and sustainability. Therefore, developing SOM models and other assessment techniques based on soil properties, environmental factors, and management practices can serve as a tool for sustainable management. Long-term or extensive short-term experimental data should be used for modeling to obtain reliable results, especially for quantitative SOM transformation analysis, and changes in the quality and quantity of SOM should be considered when developing sustainable soil management strategies. Full article
(This article belongs to the Special Issue Integration of Agronomic Practices for Sustainable Crop Production)
17 pages, 15370 KiB  
Article
Mobile Robot System for Selective Asparagus Harvesting
by Sebastjan Šlajpah, Marko Munih and Matjaž Mihelj
Agronomy 2023, 13(7), 1766; https://doi.org/10.3390/agronomy13071766 - 29 Jun 2023
Cited by 2 | Viewed by 1612
Abstract
Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It [...] Read more.
Asparagus harvesting presents unique challenges, due to the variability in spear growth, which makes large-scale automated harvesting difficult. This paper describes the development of an asparagus harvesting robot system. The system consists of a delta robot mounted on a mobile track-based platform. It employs a real-time asparagus detection algorithm and a sensory system to determine optimal harvesting points. Low-level control and high-level control are separated in the robot control. The performance of the system was evaluated in a laboratory field mock-up and in the open field, using asparagus spears of various shapes. The results demonstrate that the system detected and harvested 88% of the ready-to-harvest spears, with an average harvesting cycle cost of 3.44s±0.14s. In addition, outdoor testing in an open field demonstrated a 77% success rate in identifying and harvesting asparagus spears. Full article
(This article belongs to the Special Issue Agricultural Automation and Innovative Agricultural Systems)
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11 pages, 609 KiB  
Article
Assessment of the Quality of ‘Red Jonaprince’ Apples during Storage after Delayed Harvesting and 1-Methylcyclopropene (1-MCP) Preharvest and Postharvest Treatment
by Kazimierz Tomala, Dominika Guzek, Dominika Głąbska, Maria Małachowska, Łukasz Widłak, Tomasz Krupa and Krystyna Gutkowska
Agronomy 2023, 13(7), 1730; https://doi.org/10.3390/agronomy13071730 - 28 Jun 2023
Cited by 4 | Viewed by 1176
Abstract
Changing the harvesting time of apples from the optimum harvest window to delayed harvesting may be applied if it is impossible to harvest apples at the optimal time, but it requires changing other factors, as they influence the quality of fruits and shelf [...] Read more.
Changing the harvesting time of apples from the optimum harvest window to delayed harvesting may be applied if it is impossible to harvest apples at the optimal time, but it requires changing other factors, as they influence the quality of fruits and shelf life. The aim of the study was to assess the quality of ‘Red Jonaprince’ apples during storage after delayed harvesting and 1-methylcyclopropene (1-MCP) preharvest and postharvest treatment for various storage times. Apples were studied within four groups subjected to preharvest and postharvest treatments, as follows: Group 0—no 1-MCP treatment; Group 1—1-MCP preharvest treatment; Group 2—1-MCP postharvest treatment; and Group 3—1-MCP preharvest and postharvest treatment. All apples were subjected to ultra-low oxygen (ULO) storage conducted for 3, 5 or 6 months, while the analyses were conducted directly after ULO storage (simulated shelf life—0 days) and after simulated shelf life (7 days). For firmness, in the case of 1-MCP applied only preharvest (Group 1) and only postharvest (Group 2), before shelf life, the longer ULO storage resulted in obtaining lower values of firmness (p < 0.0001). If 1-MCP was not applied postharvest (Group 0 and Group 1), and short ULO storage was applied (3 and 5 months for Group 0; 3 months for Group 1), after shelf-life lower values of firmness were observed (p < 0.0001). For soluble solids content (SSC), in the case of 1-MCP not applied preharvest (Group 0 and Group 2), before shelf life, and for 1-MCP applied postharvest (Group 2) after shelf life, the longer ULO storage resulted in obtaining lower values of SCC (p < 0.0001). For titratable acidity (TA), in the case of all the studied groups after shelf life, as well as in case of 1-MCP applied only preharvest (Group 1) also before shelf life, the longer ULO storage resulted in obtaining lower values of TA (p < 0.0001). Except for the 1-MCP applied only postharvest (Group 2), in the case of short ULO storage applied (3 and 5 months for Group 0; 5 months for Group 1; 5 months for Group 3), after shelf-life lower values of TA were observed (p < 0.0001). If delayed harvesting must be conducted, applying 1-MCP not only postharvest, but also preharvest, allows obtaining the most stable firmness and SSC, which do not decrease during storage and shelf life. Taking this into account, it may be concluded, that in the case of delayed harvesting, combining 1-MCP applied preharvest and postharvest should be recommended to keep the quality parameters stable during storage and shelf life. Full article
(This article belongs to the Special Issue Effects of Agronomical Practices on Crop Quality and Sensory Profile)
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20 pages, 3299 KiB  
Article
Responsible Mechanisms for the Restriction of Heavy Metal Toxicity in Plants via the Co-Foliar Spraying of Nanoparticles
by Abolghassem Emamverdian, Abazar Ghorbani, Yang Li, Necla Pehlivan, James Barker, Yulong Ding, Guohua Liu and Meisam Zargar
Agronomy 2023, 13(7), 1748; https://doi.org/10.3390/agronomy13071748 - 28 Jun 2023
Cited by 20 | Viewed by 2253
Abstract
Bamboo is nutritionally significant across the world because the shoots are high in calories and nutritional fiber but low in cholesterol. However, recent research has shown that bamboo shoots also contain a substantial quantity of heavy metals, including arsenic (As). Therefore, we explored [...] Read more.
Bamboo is nutritionally significant across the world because the shoots are high in calories and nutritional fiber but low in cholesterol. However, recent research has shown that bamboo shoots also contain a substantial quantity of heavy metals, including arsenic (As). Therefore, we explored whether the co-application of iron oxide nanoparticles (IONPs) and selenium nanoparticles (Se-NPs) would attenuate As toxicity in bamboo plants (Pleioblastus pygmaeus). A greenhouse experiment was performed to investigate plant responses to arsenic toxicity. Bamboo plants exposed to four levels of As (0, 10, 20, and 40 mg L−1) were foliar-sprayed with 60 mg L−1 of Se-NPs and 60 mg L−1 of IONPs alone and in combination. The data indicated that different As concentrations (10, 20, and 40 mg L−1) caused membrane damage and reactive oxide species (ROS) production in bamboo cells, characterized by H2O2, O2•−, MDA, and EL increasing by up to 47%, 54%, 57%, and 65%, respectively, in comparison with a control. The co-application of 60 mg L−1 of Se-NPs + IONP markedly improved the antioxidant enzyme activities (by 75% in SOD, 27% in POD, 52% in CAT, 37% in GR, and 38% in PAL), total flavonoid content (42%), phenolic content (36%), proline (44%), nitric oxide (59%), putrescine (Put) (85%), spermidine (Spd) (53%), relative water content (RWC) (36%), photosynthetic characteristics (27%) in net photosynthesis (Pn) (24% in the intercellular CO2 concentration (Ci), 39% in stomatal conductance (Gs), and 31% in chlorophyll pigments), and ultimately biomass indices and growth. The co-application of Se-NPs + IONPs with 10 and 20 mg L−1 of As raised the TI by 14% and 9% in the shoot and by 18% and 14% in the root, respectively. IONPs and Se-NPs reduced ROS, cell membrane lipoperoxidation, and electrolyte leakage, all contributing to the decrease in oxidative stress by limiting As uptake and translocation. In sum, Se-NPs and IONPs improved bamboo endurance, yet the most effective approach for increasing bamboo’s ability to recover from As toxicity was the concurrent use of 60 mg L−1 of Se-NPs and 60 mg L−1 of IONPs. Our IONP and Se-NP data from single and combined applications offer novel knowledge in improving the tolerance mechanism against As exposure in Pleioblastus pygmaeus. Full article
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18 pages, 6319 KiB  
Article
In-Season Crop Type Detection by Combing Sentinel-1A and Sentinel-2 Imagery Based on the CNN Model
by Mingxiang Mao, Hongwei Zhao, Gula Tang and Jianqiang Ren
Agronomy 2023, 13(7), 1723; https://doi.org/10.3390/agronomy13071723 - 27 Jun 2023
Cited by 6 | Viewed by 1103
Abstract
In-season crop-type maps are required for a variety of agricultural monitoring and decision-making applications. The earlier the crop type maps of the current growing season are obtained, the more beneficial it is for agricultural decision-making and management. With the availability of a large [...] Read more.
In-season crop-type maps are required for a variety of agricultural monitoring and decision-making applications. The earlier the crop type maps of the current growing season are obtained, the more beneficial it is for agricultural decision-making and management. With the availability of a large amount of high spatiotemporal resolution remote sensing data, different data sources are expected to increase the frequency of data acquisition, which can provide more information in the early season. To explore the potential of integrating different data sources, a Dual-1DCNN algorithm was built based on the CNN model in this study. Moreover, an incremental training method was used to attain the network on each data acquisition date and obtain the best detection date for each crop type in the early season. A case study for Hengshui City in China was conducted using time series of Sentinel-1A (S1A) and Sentinel-2 (S2) attained in 2019. To verify this method, the classical methods support vector machine (SVM), random forest (RF), and Mono-1DCNN were implemented. The input for SVM and RF was S1A and S2 data, and the input for Mono-1DCNN was S2 data. The results demonstrated the following: (1) Dual-1DCNN achieved an overall accuracy above 85% at the earliest time.; (2) all four types of models achieved high accuracy (F1s were greater than 90%) on summer maize after sowing one month later; (3) for cotton and common yam rhizomes, Dual-1DCNN performed best, with its F1 reaching 85% within 2 months after cotton sowing, 15 days, 20 days, and 45 days ahead of Mono-1DCNN, SVM, and RF, respectively, and its extraction of the common yam rhizome was achieved 1–2 months earlier than other methods within the acceptable accuracy. These results confirmed that Dual-1DCNN offered significant potential in the in-season detection of crop types. Full article
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10 pages, 3690 KiB  
Article
Melatonin Mitigated Salinity Stress on Alfalfa by Improving Antioxidant Defense and Osmoregulation
by Xiaoqian Guo, Yu Shi, Guanglong Zhu and Guisheng Zhou
Agronomy 2023, 13(7), 1727; https://doi.org/10.3390/agronomy13071727 - 27 Jun 2023
Cited by 4 | Viewed by 1111
Abstract
Melatonin (MT) is a growth regulator and antioxidant that can resist peroxidation damage on plants caused by environmental stresses. In this study, the alleviation effects of melatonin on alfalfa under salt stress were investigated in terms of photosynthesis, antioxidant enzymes, and osmoregulation. The [...] Read more.
Melatonin (MT) is a growth regulator and antioxidant that can resist peroxidation damage on plants caused by environmental stresses. In this study, the alleviation effects of melatonin on alfalfa under salt stress were investigated in terms of photosynthesis, antioxidant enzymes, and osmoregulation. The alfalfa seedlings were cultured in 200 mM NaCl Hoagland solution. Five levels of MT (0, 0.1, 0.2, 0.3, and 0.4 mM) were applied as a foliar spray. Generally, the foliar spray of MT increased root length, root surface area, height, leaf length and width, aerial and root biomass, SPAD readings, the content of proline and soluble protein, and the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). Malonaldehyde (MDA) content was decreased by MT foliar spray. The beneficial effects of MT on alfalfa under salt stress were dosage-dependent, and excessive MT levels inhibited alfalfa growth. The alleviating effects of MT on salt stress were more pronounced at 0.3 mM MT. This study suggested that exogenous MT foliar spray at appropriate levels can ameliorate the adverse effects of salt stress on alfalfa seedlings. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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22 pages, 1934 KiB  
Review
Enhancing Essential Grains Yield for Sustainable Food Security and Bio-Safe Agriculture through Latest Innovative Approaches
by Ghosoon Albahri, Amal A. Alyamani, Adnan Badran, Akram Hijazi, Mohamad Nasser, Marc Maresca and Elias Baydoun
Agronomy 2023, 13(7), 1709; https://doi.org/10.3390/agronomy13071709 - 26 Jun 2023
Cited by 14 | Viewed by 3251
Abstract
A key concern in agriculture is how to feed the expanding population and safeguard the environment from the ill effects of climate change. To feed a growing global population, food production and security are significant problems, as food output may need to double [...] Read more.
A key concern in agriculture is how to feed the expanding population and safeguard the environment from the ill effects of climate change. To feed a growing global population, food production and security are significant problems, as food output may need to double by 2050. Thus, more innovative and effective approaches for increasing agricultural productivity (hence, food production) are required to meet the rising demand for food. The world’s most widely cultivated grains include corn, wheat, and rice, which serve as the foundation for basic foods. This review focuses on some of the key most up-to-date approaches that boost wheat, rice, corn, barley, and oat yields with insight into how molecular technology and genetics may raise the production and resource-efficient use of these important grains. Although red light management and genetic manipulation show maximal grain yield enhancement, other covered strategies including bacterial-nutrient management, solar brightening, facing abiotic stress through innovative agricultural systems, fertilizer management, harmful gas emissions reduction, photosynthesis enhancement, stress tolerance, disease resistance, and varietal improvement also enhance grain production and increase plant resistance to harmful environmental circumstances. This study also discusses the potential challenges of the addressed approaches and possible future perspectives. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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14 pages, 5347 KiB  
Article
Detection of Power Poles in Orchards Based on Improved Yolov5s Model
by Yali Zhang, Xiaoyang Lu, Wanjian Li, Kangting Yan, Zhenjie Mo, Yubin Lan and Linlin Wang
Agronomy 2023, 13(7), 1705; https://doi.org/10.3390/agronomy13071705 - 26 Jun 2023
Cited by 6 | Viewed by 1045
Abstract
During the operation of agricultural unmanned aerial vehicles (UAVs) in orchards, the presence of power poles and wires pose a serious threat to flight safety, and can even lead to crashes. Due to the difficulty of directly detecting wires, this research aimed to [...] Read more.
During the operation of agricultural unmanned aerial vehicles (UAVs) in orchards, the presence of power poles and wires pose a serious threat to flight safety, and can even lead to crashes. Due to the difficulty of directly detecting wires, this research aimed to quickly and accurately detect wire poles, and proposed an improved Yolov5s deep learning object detection algorithm named Yolov5s-Pole. The algorithm enhances the model’s generalization ability and robustness by applying Mixup data augmentation technique, replaces the C3 module with the GhostBottleneck module to reduce the model’s parameters and computational complexity, and incorporates the Shuffle Attention (SA) module to improve its focus on small targets. The results show that when the improved Yolov5s-Pole model was used for detecting poles in orchards, its accuracy, recall, and mAP@50 were 0.803, 0.831, and 0.838 respectively, which increased by 0.5%, 10%, and 9.2% compared to the original Yolov5s model. Additionally, the weights, parameters, and GFLOPs of the Yolov5s-Pole model were 7.86 MB, 3,974,310, and 9, respectively. Compared to the original Yolov5s model, these represent compression rates of 42.2%, 43.4%, and 43.3%, respectively. The detection time for a single image using this model was 4.2 ms, and good robustness under different lighting conditions (dark, normal, and bright) was demonstrated. The model is suitable for deployment on agricultural UAVs’ onboard equipment, and is of great practical significance for ensuring the efficiency and flight safety of agricultural UAVs. Full article
(This article belongs to the Special Issue New Trends in Agricultural UAV Application)
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12 pages, 1736 KiB  
Article
Antioxidant Activity, Phenolic Content, and Antioxidant Gene Expression in Genetic Resources of Sorghum Collected from Australia, Former Soviet Union, USA, Sudan and Guadeloupe
by Ji Won Seo, Da Ye Ham, Jae Geun Lee, Na Young Kim, Myong Jo Kim, Chang Yeon Yu and Eun Soo Seong
Agronomy 2023, 13(7), 1698; https://doi.org/10.3390/agronomy13071698 - 25 Jun 2023
Cited by 2 | Viewed by 916
Abstract
Functionality based on the biological activity of sorghum such as antioxidant activity is known worldwide for its excellence. In this study, we investigated the reactive oxygen species (ROS) scavenging activity, total phenolic and flavonoid contents, phenol compounds, and changes in antioxidant gene expression [...] Read more.
Functionality based on the biological activity of sorghum such as antioxidant activity is known worldwide for its excellence. In this study, we investigated the reactive oxygen species (ROS) scavenging activity, total phenolic and flavonoid contents, phenol compounds, and changes in antioxidant gene expression in sorghum seed cells collected from five countries (Australia, former Soviet Union, USA, Sudan, and Guadeloupe). Sorghum seeds were obtained from 12 genetic resources (K159041, K159042, K159078, K159081, K159088, K159089, K159093, K159097, K159100, K159096, K159048, and K159077). ROS scavenging activity was analyzed using 1,1-diphenyl-2-picrylhydrazyl (DPPH) and 2,20-azinobis 3-ethylbenzothiazoline-6-sulfonate (ABTS). K159097 showed high antioxidant activity values of 33.52 ± 0.70 μg/mL (DPPH) and 271.06 ± 13.41 μg/mL (ABTS), respectively. The reducing power of the resources improved in a concentration-dependent manner, and 10 sorghum resources, except K159078 and K159048, showed high reducing power. K159042 had the highest total phenol content (231 ± 2.17 mg·GAE/g), and K159081 had the highest total flavonoid content (67.71 ± 5.38 mg·QE/g). Among the six phenolic compounds (protocatechuic acid, caffeic acid, p-coumaric acid, ferulic acid, taxifolin, and naringenin) analyzed, the compound with the highest content was taxifolin (203.67 ± 4.99 mg/L in K159093). K159041, K159042, and K159048 had the highest expression levels of superoxide dismutase (SOD), ascorbate peroxidase 1 (APX1), and catalase (CAT), which are indicators of antioxidant activity. An evaluation of the diversity of sorghum provided useful information on antioxidant activity, physicochemical content, and antioxidant gene expression in seed cells, suggesting that sorghum can be used as a biomaterial from natural resources. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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14 pages, 722 KiB  
Article
Market Trends of Medicinal and Aromatic Plants in Italy: Future Scenarios Based on the Delphi Method
by Daniela Spina, Cinzia Barbieri, Roberto Carbone, Manal Hamam, Mario D’Amico and Giuseppe Di Vita
Agronomy 2023, 13(7), 1703; https://doi.org/10.3390/agronomy13071703 - 25 Jun 2023
Cited by 7 | Viewed by 1938
Abstract
The medicinal and aromatic plant (MAP) sector in Italy is a niche sector that is growing in terms of both primary production and consumption. These products seem to be important to address several global challenges, including climate change, biodiversity conservation, drought solutions, product [...] Read more.
The medicinal and aromatic plant (MAP) sector in Italy is a niche sector that is growing in terms of both primary production and consumption. These products seem to be important to address several global challenges, including climate change, biodiversity conservation, drought solutions, product diversification, product innovations, and the development of rural areas (rural tourism in primis). This study utilised the Delphi method to identify key factors and possible strategies that could be adopted for the future (the next 3–5 years) of the national MAP supply chain. The research involved the collaboration of 26 experts. Individual interviews, based on a semi-structured questionnaire, were carried out during the first round of the study. The information and the collected data were then analysed and depicted in a mental map. The Italian MAP sector suffers from competition from lower-cost imported products. Despite this, the experts predicted an expansion of the MAP sector regarding aromatic herbs and certain derivative products, such as dietary supplements, biocides, and essential oils. The experts anticipated the need to increase the adoption of digital innovations, of developing agreements among the actors of the supply chain, and of investing in the training of supply chain actors. Full article
(This article belongs to the Section Farming Sustainability)
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19 pages, 1983 KiB  
Article
Vision-Based White Radish Phenotypic Trait Measurement with Smartphone Imagery
by L. Minh Dang, Kyungbok Min, Tan N. Nguyen, Han Yong Park, O New Lee, Hyoung-Kyu Song and Hyeonjoon Moon
Agronomy 2023, 13(6), 1630; https://doi.org/10.3390/agronomy13061630 - 18 Jun 2023
Cited by 5 | Viewed by 2184
Abstract
White radish is a nutritious and delectable vegetable that is enjoyed globally. Conventional techniques for monitoring radish growth are arduous and time-consuming, encouraging the development of novel methods for quicker measurements and greater sampling density. This research introduces a mathematical model working on [...] Read more.
White radish is a nutritious and delectable vegetable that is enjoyed globally. Conventional techniques for monitoring radish growth are arduous and time-consuming, encouraging the development of novel methods for quicker measurements and greater sampling density. This research introduces a mathematical model working on high-resolution images to measure radish’s biophysical properties automatically. A color calibration was performed on the dataset using a color checker panel to minimize the impact of varying light conditions on the RGB images. Subsequently, a Mask-RCNN model was trained to effectively segment different components of the radishes. The observations of the segmented results included leaf length, leaf width, root width, root length, leaf length to width, root length to width, root shoulder color, and root peel color. The automated real-life measurements of these observations were then conducted and compared with actual results. The validation results, based on a set of white radish samples, demonstrated the models’ effectiveness in utilizing images for quantifying phenotypic traits. The average accuracy of the automated method was confirmed to be 96.2% when compared to the manual method. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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32 pages, 7008 KiB  
Review
Fruit Detection and Recognition Based on Deep Learning for Automatic Harvesting: An Overview and Review
by Feng Xiao, Haibin Wang, Yueqin Xu and Ruiqing Zhang
Agronomy 2023, 13(6), 1625; https://doi.org/10.3390/agronomy13061625 - 16 Jun 2023
Cited by 13 | Viewed by 8159
Abstract
Continuing progress in machine learning (ML) has led to significant advancements in agricultural tasks. Due to its strong ability to extract high-dimensional features from fruit images, deep learning (DL) is widely used in fruit detection and automatic harvesting. Convolutional neural networks (CNN) in [...] Read more.
Continuing progress in machine learning (ML) has led to significant advancements in agricultural tasks. Due to its strong ability to extract high-dimensional features from fruit images, deep learning (DL) is widely used in fruit detection and automatic harvesting. Convolutional neural networks (CNN) in particular have demonstrated the ability to attain accuracy and speed levels comparable to those of humans in some fruit detection and automatic harvesting fields. This paper presents a comprehensive overview and review of fruit detection and recognition based on DL for automatic harvesting from 2018 up to now. We focus on the current challenges affecting fruit detection performance for automatic harvesting: the scarcity of high-quality fruit datasets, fruit detection of small targets, fruit detection in occluded and dense scenarios, fruit detection of multiple scales and multiple species, and lightweight fruit detection models. In response to these challenges, we propose feasible solutions and prospective future development trends. Future research should prioritize addressing these current challenges and improving the accuracy, speed, robustness, and generalization of fruit vision detection systems, while reducing the overall complexity and cost. This paper hopes to provide a reference for follow-up research in the field of fruit detection and recognition based on DL for automatic harvesting. Full article
(This article belongs to the Special Issue Agricultural Unmanned Systems: Empowering Agriculture with Automation)
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12 pages, 1456 KiB  
Article
The Impact of Climatic Factors on the Development Stages of Maize Crop in the Transylvanian Plain
by Alina Șimon, Paula Ioana Moraru, Adrian Ceclan, Florin Russu, Felicia Chețan, Marius Bărdaș, Alin Popa, Teodor Rusu, Adrian Ioan Pop and Ileana Bogdan
Agronomy 2023, 13(6), 1612; https://doi.org/10.3390/agronomy13061612 - 15 Jun 2023
Cited by 6 | Viewed by 2224
Abstract
Climate change has become the biggest global challenge, being a real danger especially for crops and an inevitable threat to food security. This paper presents the results of a study conducted in the Transylvanian Plain during 2012–2021, regarding the influence of climatic factors, [...] Read more.
Climate change has become the biggest global challenge, being a real danger especially for crops and an inevitable threat to food security. This paper presents the results of a study conducted in the Transylvanian Plain during 2012–2021, regarding the influence of climatic factors, such as temperature, rainfall, water reserve in the soil and hours of sunshine, on the development stages and yield of maize. During 2012–2021, the soil water reserve determined for maize cultivation was above the minimum requirements (1734.8 m3 ha−1) in the spring months, but fell below this limit in the months when the water consumption for maize was the highest, but without reaching the withering index (1202.8 m3 ha−1). The hours of sunshine in the maize vegetation period have been significantly reduced from 1655.5 h (2012) to values between 1174.6 and 1296.7 h, with a significant decrease in this parameter being observed. The coefficient of determination (R2 = 0.51) shows the importance of rainfall during the period of emergence of reproductive organs in maize production. During 2019–2021, there was a decreasing trend of temperatures in May compared to the multiannual average of this month, and therefore the processes of emergence and growth of plants in the early stages were affected. During the period of the study, all parameters analyzed (temperature, rainfall, water reserve in the soil, hours of sunshine) deviated from the multiannual average, with negative variations compared to the requirements of maize. Climatic conditions, especially during the growing season, have a significant influence on the yield of a crop, especially when the interaction between several parameters is manifested. Full article
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16 pages, 337 KiB  
Review
Herbicide Resistance: Managing Weeds in a Changing World
by Rita Ofosu, Evans Duah Agyemang, Adrienn Márton, György Pásztor, János Taller and Gabriella Kazinczi
Agronomy 2023, 13(6), 1595; https://doi.org/10.3390/agronomy13061595 - 13 Jun 2023
Cited by 18 | Viewed by 5055
Abstract
Over the years, several agricultural interventions and technologies have contributed immensely towards intensifying food production globally. The introduction of herbicides provided a revolutionary tool for managing the difficult task of weed control contributing significantly towards global food security and human survival. However, in [...] Read more.
Over the years, several agricultural interventions and technologies have contributed immensely towards intensifying food production globally. The introduction of herbicides provided a revolutionary tool for managing the difficult task of weed control contributing significantly towards global food security and human survival. However, in recent times, the successes achieved with chemical weed control have taken a turn, threatening the very existence we have tried to protect. The side effects of conventional farming, particularly the increasing cases of herbicide resistance agricultural weeds, is quite alarming. Global calls for sustainable weed management approaches to be used in food production is mounting. This paper provides detailed information on the molecular biological background of herbicide resistant weed biotypes and highlights the alternative, non-chemical weed management methods which can be used to prevent the development and spreading of herbicide-resistant weeds. Full article
30 pages, 3997 KiB  
Review
Deciphering the Interactions in the Root–Soil Nexus Caused by Urease and Nitrification Inhibitors: A Review
by Sneha Gupta, Sibel Yildirim, Benjamin Andrikopoulos, Uta Wille and Ute Roessner
Agronomy 2023, 13(6), 1603; https://doi.org/10.3390/agronomy13061603 - 13 Jun 2023
Cited by 3 | Viewed by 2405
Abstract
Optimizing nitrogen (N) availability to plants is crucial for achieving maximum crop yield and quality. However, ensuring the appropriate supply of N to crops is challenging due to the various pathways through which N can be lost, such as ammonia (NH3) [...] Read more.
Optimizing nitrogen (N) availability to plants is crucial for achieving maximum crop yield and quality. However, ensuring the appropriate supply of N to crops is challenging due to the various pathways through which N can be lost, such as ammonia (NH3) volatilization, nitrous oxide emissions, denitrification, nitrate (NO3) leaching, and runoff. Additionally, N can become immobilized by soil minerals when ammonium (NH4+) gets trapped in the interlayers of clay minerals. Although synchronizing N availability with plant uptake could potentially reduce N loss, this approach is hindered by the fact that N loss from crop fields is typically influenced by a combination of management practices (which can be controlled) and weather dynamics, particularly precipitation, temperature fluctuations, and wind (which are beyond our control). In recent years, the use of urease and nitrification inhibitors has emerged as a strategy to temporarily delay the microbiological transformations of N-based fertilizers, thereby synchronizing N availability with plant uptake and mitigating N loss. Urease inhibitors slow down the hydrolysis of urea to NH4+ and reduce nitrogen loss through NH3 volatilization. Nitrification inhibitors temporarily inhibit soil bacteria (Nitrosomonas spp.) that convert NH4+ to nitrite (NO2), thereby slowing down the first and rate-determining step of the nitrification process and reducing nitrogen loss as NO3 or through denitrification. This review aims to provide a comprehensive understanding of urease and nitrification inhibitor technologies and their profound implications for plants and root nitrogen uptake. It underscores the critical need to develop design principles for inhibitors with enhanced efficiency, highlighting their potential to revolutionize agricultural practices. Furthermore, this review offers valuable insights into future directions for inhibitor usage and emphasizes the essential traits that superior inhibitors should possess, thereby paving the way for innovative advancements in optimizing nitrogen management and ensuring sustainable crop production. Full article
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21 pages, 2510 KiB  
Review
Thermal Degradation of Bioactive Compounds during Drying Process of Horticultural and Agronomic Products: A Comprehensive Overview
by Ramadan ElGamal, Cheng Song, Ahmed M. Rayan, Chuanping Liu, Salim Al-Rejaie and Gamal ElMasry
Agronomy 2023, 13(6), 1580; https://doi.org/10.3390/agronomy13061580 - 11 Jun 2023
Cited by 12 | Viewed by 3545
Abstract
Over the last few decades, many researchers have investigated in detail the characteristics of bioactive compounds such as polyphenols, vitamins, flavonoids, and glycosides, and volatile compounds in fruits, vegetables and medicinal and aromatic plants that possess beneficial properties, as well as consumer acceptance [...] Read more.
Over the last few decades, many researchers have investigated in detail the characteristics of bioactive compounds such as polyphenols, vitamins, flavonoids, and glycosides, and volatile compounds in fruits, vegetables and medicinal and aromatic plants that possess beneficial properties, as well as consumer acceptance and preference. The main aim of this article is to provide an updated overview of recent research endeavors related to the effects of the drying process on the major bioactive/effective compounds in agricultural products. Particular emphasis was placed on details related to the changes occurring in vitamin C, polyphenols, flavonoids, glycosides and volatile compounds, as well as the antioxidant activity. An analysis of the degradation mechanisms of these compounds showed that vitamin C, phenols, flavonoids and glycosides react with oxygen during the convective drying process under high drying temperatures, and the reaction rate results in degradation in such bioactive compounds due to high reducibility. On the other hand, high temperature results in a short drying time, thus minimizing the degradation of bioactive compounds. The reviewed research works addressing this trend revealed that the ideal drying temperatures for retaining vitamin C, polyphenols, flavonoids, glycosides, volatile compounds and their antioxidant activity were 50–60 °C, 55–60 °C, 60–70 °C, 45–50 °C, 40–50 °C and 50–70 °C, respectively. In conclusion, to maintain plant bioactive components, convective drying at relatively low drying temperatures is strongly recommended. Full article
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17 pages, 5588 KiB  
Article
Estimating Relative Chlorophyll Content in Rice Leaves Using Unmanned Aerial Vehicle Multi-Spectral Images and Spectral–Textural Analysis
by Yuwei Wang, Suiyan Tan, Xingna Jia, Long Qi, Saisai Liu, Henghui Lu, Chengen Wang, Weiwen Liu, Xu Zhao, Longxin He, Jiongtao Chen, Chuanyi Yang, Xicheng Wang, Jiaying Chen, Yijuan Qin, Jie Yu and Xu Ma
Agronomy 2023, 13(6), 1541; https://doi.org/10.3390/agronomy13061541 - 01 Jun 2023
Cited by 5 | Viewed by 2160
Abstract
Leaf chlorophyll content is crucial for monitoring plant growth and photosynthetic capacity. The Soil and Plant Analysis Development (SPAD) values are widely utilized as a relative chlorophyll content index in ecological agricultural surveys and vegetation remote sensing applications. Multi-spectral cameras are a cost-effective [...] Read more.
Leaf chlorophyll content is crucial for monitoring plant growth and photosynthetic capacity. The Soil and Plant Analysis Development (SPAD) values are widely utilized as a relative chlorophyll content index in ecological agricultural surveys and vegetation remote sensing applications. Multi-spectral cameras are a cost-effective alternative to hyperspectral cameras for agricultural monitoring. However, the limited spectral bands of multi-spectral cameras restrict the number of vegetation indices (VIs) that can be synthesized, necessitating the exploration of other options for SPAD estimation. This study evaluated the impact of using texture indices (TIs) and VIs, alone or in combination, for estimating rice SPAD values during different growth stages. A multi-spectral camera was attached to an unmanned aerial vehicle (UAV) to collect remote sensing images of the rice canopy, with manual SPAD measurements taken immediately after each flight. Random forest (RF) was employed as the regression method, and evaluation metrics included coefficient of determination (R2) and root mean squared error (RMSE). The study found that textural information extracted from multi-spectral images could effectively assess the SPAD values of rice. Constructing TIs by combining two textural feature values (TFVs) further improved the correlation of textural information with SPAD. Utilizing both VIs and TIs demonstrated superior performance throughout all growth stages. The model works well in estimating the rice SPAD in an independent experiment in 2022, proving that the model has good generalization ability. The results suggest that incorporating both spectral and textural data can enhance the precision of rice SPAD estimation throughout all growth stages, compared to using spectral data alone. These findings are of significant importance in the fields of precision agriculture and environmental protection. Full article
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27 pages, 4709 KiB  
Article
Effects of Combined Long-Term Straw Return and Nitrogen Fertilization on Wheat Productivity and Soil Properties in the Wheat-Maize-Soybean Rotation System in the Pannonian Plain
by Goran Jaćimović, Vladimir Aćin, Milan Mirosavljević, Ljiljana Brbaklić, Svetlana Vujić, Dušan Dunđerski and Srđan Šeremešić
Agronomy 2023, 13(6), 1529; https://doi.org/10.3390/agronomy13061529 - 31 May 2023
Cited by 3 | Viewed by 1352
Abstract
The study, conducted to evaluate the effects of long-term straw management combined with the application of increasing nitrogen rates on the yield of twenty winter wheat varieties, as well as on soil properties, was carried out in a long-term field trial established in [...] Read more.
The study, conducted to evaluate the effects of long-term straw management combined with the application of increasing nitrogen rates on the yield of twenty winter wheat varieties, as well as on soil properties, was carried out in a long-term field trial established in 1971. The trial was monitored for twenty growing seasons under rainfed conditions in a typical chernozem zone of the southern part of the Pannonian Plain. The cropping system was a winter wheat-maize-soybean rotation. The ten SN-treatments (combinations of straw management (S) and N-fertilization) were as follows: In the plot (treatment) with straw return (S1), seven variants of nitrogen fertilization (0–180 kg N ha−1) were included, while on the plot without straw return (S0) the variants of N-fertilization were 0, 90 and 150 kg N ha−l. Based on the high relative share in the total sum of squares, variance analysis showed that wheat grain yield (GY) was significantly affected by years, SN-treatments, and their interaction, and they can explain the largest part of the total variance of GY. The results showed that straw return integrated with N fertilization could increase wheat yield to varying degrees over 20 years. On average, for all years, the highest GYs were obtained in the treatment S1 and fertilization with 180 and 150 kg N ha−1. The overall results showed that long-term straw returning significantly increased GY by an average of 8.4 ± 4.5%, with a considerable simultaneous increase in yield stability compared to straw removal. In addition, straw incorporation (SI) significantly increased soil humus, total nitrogen (TN), and soil organic carbon (SOC) contents at a soil depth of 0–30 cm by an average of 4.2, 3.8, and 11.3%, respectively. The results of our study have demonstrated that the long-term practice of straw return, in combination with the application of mineral fertilizers, has the potential to serve as a sustainable soil management strategy that is economically viable and environmentally acceptable. However, additional research is required to investigate its interactive effects on both grain yield and soil productivity. Full article
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30 pages, 1652 KiB  
Review
Heavy Metal Contamination in Agricultural Soil: Environmental Pollutants Affecting Crop Health
by Abdur Rashid, Brian J. Schutte, April Ulery, Michael K. Deyholos, Soum Sanogo, Erik A. Lehnhoff and Leslie Beck
Agronomy 2023, 13(6), 1521; https://doi.org/10.3390/agronomy13061521 - 31 May 2023
Cited by 48 | Viewed by 16763
Abstract
Heavy metals and metalloids (HMs) are environmental pollutants, most notably cadmium, lead, arsenic, mercury, and chromium. When HMs accumulate to toxic levels in agricultural soils, these non-biodegradable elements adversely affect crop health and productivity. The toxicity of HMs on crops depends upon factors [...] Read more.
Heavy metals and metalloids (HMs) are environmental pollutants, most notably cadmium, lead, arsenic, mercury, and chromium. When HMs accumulate to toxic levels in agricultural soils, these non-biodegradable elements adversely affect crop health and productivity. The toxicity of HMs on crops depends upon factors including crop type, growth condition, and developmental stage; nature of toxicity of the specific elements involved; soil physical and chemical properties; occurrence and bioavailability of HM ions in the soil solution; and soil rhizosphere chemistry. HMs can disrupt the normal structure and function of cellular components and impede various metabolic and developmental processes. This review evaluates: (1) HM contamination in arable lands through agricultural practices, particularly due to chemical fertilizers, pesticides, livestock manures and compost, sewage-sludge-based biosolids, and irrigation; (2) factors affecting the bioavailability of HM elements in the soil solution, and their absorption, translocation, and bioaccumulation in crop plants; (3) mechanisms by which HM elements directly interfere with the physiological, biochemical, and molecular processes in plants, with particular emphasis on the generation of oxidative stress, the inhibition of photosynthetic phosphorylation, enzyme/protein inactivation, genetic modifications, and hormonal deregulation, and indirectly through the inhibition of soil microbial growth, proliferation, and diversity; and (4) visual symptoms of highly toxic non-essential HM elements in plants, with an emphasis on crop plants. Finally, suggestions and recommendations are made to minimize crop losses from suspected HM contamination in agricultural soils. Full article
(This article belongs to the Topic Effect of Heavy Metals on Plants)
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18 pages, 4880 KiB  
Article
Multi-Scale Correlation between Soil Loss and Natural Rainfall on Sloping Farmland Using the Hilbert–Huang Transform in Southwestern China
by Xiaopeng Shi, Shuqin He, Rui Ma, Zicheng Zheng, Haiyan Yi and Xinlan Liang
Agronomy 2023, 13(6), 1492; https://doi.org/10.3390/agronomy13061492 - 29 May 2023
Cited by 3 | Viewed by 1490
Abstract
The Hilbert–Huang transform (HHT) has been used as a powerful tool for analyzing nonlinear and nonstationary time series. Soil loss is controlled by complicated physical processes and thus fluctuates with nonlinearity and nonstationarity over time. In order to further clarify the relationship between [...] Read more.
The Hilbert–Huang transform (HHT) has been used as a powerful tool for analyzing nonlinear and nonstationary time series. Soil loss is controlled by complicated physical processes and thus fluctuates with nonlinearity and nonstationarity over time. In order to further clarify the relationship between rainfall, surface runoff, and sediment yield, this study adopted the HHT to analyze these characteristics through multiple time scales and investigated their relationship through time-dependent intrinsic correlation (TDIC) in the time series. A six-year study (2015–2020) was conducted on sloping farmlands to explore the relationships between soil loss and rainfall in southwest China. Time series of soil loss and rainfall were identified as the relevant characteristics at different time scales based on the method of HHT. Local correlation between the soil loss and runoff was carried out by the method of TDIC. The original time series of the rainfall, runoff, and soil loss were decomposed into eight intrinsic mode functions (IMFs) and a residue by ensemble empirical mode decomposition (EEMD). The residue indicated that the rainfall and runoff increased and then decreased during the maize-growing season from 2015 to 2020, whereas the soil loss gradually decreased. IMF1 and IMF2 accounted for nearly 80% of the temporal variations in rainfall, runoff, and soil loss, indicating that the variables varied the most at short time scales. The TDIC analysis showed that strong and positive correlations between the soil loss, rainfall, and runoff prevailed over the entire time domain at the scales of IMF1 and IMF2, indicating the rapid response of the soil loss to rainfall and runoff at short time scales. Time-varying correlations were observed at the IMF3–IMF5 scales. At the IMF7 scale, an evident switchover in the nature of the correlation was identified during the years 2018 and 2019; this could be related to a sudden rainstorm under low vegetation coverage conditions. The EEMD-based TDIC tool is an effective means to clarify the relationship between soil loss, rainfall, and runoff. Our results provide a better understanding of the relationship between soil loss and rainfall varied with time at multiple time scales. Short-term heavy rainfall and rapid surface runoff are the important factors causing serious soil and water loss on a short time scale in a mountainous region with yellow soil, which is of great significance for the construction of a regional soil erosion prediction model. Full article
(This article belongs to the Section Farming Sustainability)
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23 pages, 1663 KiB  
Review
Ammonium Phytotoxicity and Tolerance: An Insight into Ammonium Nutrition to Improve Crop Productivity
by Jayabalan Shilpha, Jinnan Song and Byoung Ryong Jeong
Agronomy 2023, 13(6), 1487; https://doi.org/10.3390/agronomy13061487 - 28 May 2023
Cited by 6 | Viewed by 2543
Abstract
Ammonium sensitivity is considered a globally stressful condition that affects overall crop productivity. The major toxic symptom associated with ammonium nutrition is growth retardation, which has been associated with a high energy cost for maintaining ion, pH, and hormone homeostasis and, eventually, the [...] Read more.
Ammonium sensitivity is considered a globally stressful condition that affects overall crop productivity. The major toxic symptom associated with ammonium nutrition is growth retardation, which has been associated with a high energy cost for maintaining ion, pH, and hormone homeostasis and, eventually, the NH3/NH4+ level in plant tissues. While certain species/genotypes exhibit extreme sensitivity to ammonium, other species/genotypes prefer ammonium to nitrate as a form of nitrogen. Some of the key tolerance mechanisms used by the plant to deal with NH4+ toxicity include an enhanced activity of an alternative oxidase pathway in mitochondria, greater NH4+ assimilation plus the retention of the minimum level of NH4+ in leaves, and/or poor response to extrinsic acidification or pH drop. Except for toxicity, ammonium can be considered as an energy-efficient nutrition in comparison to nitrate since it is already in a reduced form for use in amino acid metabolism. Through effective manipulation of the NH4+/NO3  ratio, ammonium nutrition can be used to increase productivity, quality, and resistance to various biotic and abiotic stresses of crops. This review highlights recent advancements in ammonium toxicity and tolerance mechanisms, possible strategies to improve ammonium tolerance, and omics-based understanding of nitrogen use efficiency (NUE) in plants. Full article
(This article belongs to the Topic Plants Nutrients)
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19 pages, 5124 KiB  
Article
WT-YOLOM: An Improved Target Detection Model Based on YOLOv4 for Endogenous Impurity in Walnuts
by Dongdong Wang, Dan Dai, Jian Zheng, Linhui Li, Haoyu Kang and Xinyu Zheng
Agronomy 2023, 13(6), 1462; https://doi.org/10.3390/agronomy13061462 - 25 May 2023
Cited by 3 | Viewed by 1205
Abstract
Since impurities produced during walnut processing can cause serious harm to human health, strict quality control must be carried out during production. However, most detection equipment still uses photoelectric detection technology to automatically sort heterochromatic particles, which is unsuitable for detecting endogenous foreign [...] Read more.
Since impurities produced during walnut processing can cause serious harm to human health, strict quality control must be carried out during production. However, most detection equipment still uses photoelectric detection technology to automatically sort heterochromatic particles, which is unsuitable for detecting endogenous foreign bodies with similar colors. Therefore, this paper proposes an improved YOLOv4 deep learning object detection algorithm, WT-YOLOM, for detecting endogenous impurities in walnuts—namely, oily kernels, black spot kernels, withered kernels, and ground nutshells. In the backbone of the model, a lightweight MobileNet module was used as the encoder for the extraction of features. The spatial pyramid pooling (SPP) structure was improved to spatial pyramid pooling—fast (SPPF), and the model size was further reduced. Loss function was replaced in this model with a more comprehensive SIoU loss. In addition, efficient channel attention (ECA) mechanisms were applied after the backbone feature map to improve the model’s recognition accuracy. This paper compares the recognition speed and accuracy of the WT-YOLOM algorithm with the Faster R-CNN, EfficientDet, CenterNet, and YOLOv4 algorithms. The results showed that the average precision of this model for different kinds of endogenous impurities in walnuts reached 94.4%. Compared with the original model, the size was reduced by 88.6%, and the recognition speed reached 60.1 FPS, which was an increase of 29.0%. The metrics of the WT-YOLOM model were significantly better than those of comparative models and can significantly improve the detection efficiency of endogenous foreign bodies in walnuts. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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17 pages, 6608 KiB  
Article
A Refined Apple Binocular Positioning Method with Segmentation-Based Deep Learning for Robotic Picking
by Huijun Zhang, Chunhong Tang, Xiaoming Sun and Longsheng Fu
Agronomy 2023, 13(6), 1469; https://doi.org/10.3390/agronomy13061469 - 25 May 2023
Cited by 5 | Viewed by 1229
Abstract
An apple-picking robot is now the most widely accepted method in the substitution of low-efficiency and high-cost labor-intensive apple harvesting. Although most current research on apple-picking robots works well in the laboratory, most of them are unworkable in an orchard environment due to [...] Read more.
An apple-picking robot is now the most widely accepted method in the substitution of low-efficiency and high-cost labor-intensive apple harvesting. Although most current research on apple-picking robots works well in the laboratory, most of them are unworkable in an orchard environment due to unsatisfied apple positioning performance. In general, an accurate, fast, and widely used apple positioning method for an apple-picking robot remains lacking. Some positioning methods with detection-based deep learning reached an acceptable performance in some orchards. However, apples occluded by apples, leaves, and branches are ignored in these methods with detection-based deep learning. Therefore, an apple binocular positioning method based on a Mask Region Convolutional Neural Network (Mask R-CNN, an instance segmentation network) was developed to achieve better apple positioning. A binocular camera (Bumblebee XB3) was adapted to capture binocular images of apples. After that, a Mask R-CNN was applied to implement instance segmentation of apple binocular images. Then, template matching with a parallel polar line constraint was applied for the stereo matching of apples. Finally, four feature point pairs of apples from binocular images were selected to calculate disparity and depth. The trained Mask R-CNN reached a detection and segmentation intersection over union (IoU) of 80.11% and 84.39%, respectively. The coefficient of variation (CoV) and positioning accuracy (PA) of binocular positioning were 5.28 mm and 99.49%, respectively. The research developed a new method to fulfill binocular positioning with a segmentation-based neural network. Full article
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19 pages, 7050 KiB  
Article
Spatiotemporal Variations of Reference Evapotranspiration and Its Climatic Driving Factors in Guangdong, a Humid Subtropical Province of South China
by Baoshan Zhao, Dongsheng An, Chengming Yan, Haofang Yan, Ran Kong and Junbo Su
Agronomy 2023, 13(6), 1446; https://doi.org/10.3390/agronomy13061446 - 24 May 2023
Cited by 4 | Viewed by 1199
Abstract
It is of great importance to study the changes in reference evapotranspiration (ET0) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET0 data calculated using the Penman–Monteith method from 37 meteorological stations [...] Read more.
It is of great importance to study the changes in reference evapotranspiration (ET0) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET0 data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET0 and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u2)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET0. The main findings of the study are as follows: (1) the trend in average annual ET0 time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET0. During the same period, air temperature significantly increased, while RH and SD decreased; u2 also decreased. (2) Sensitivity analysis showed that ET0 was more sensitive to RH and T than SD and u2, with ET0 being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET0 variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET0 changes in areas where the “evaporation paradox” occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future. Full article
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18 pages, 5867 KiB  
Article
Research and Design of Hybrid Optimized Backpropagation (BP) Neural Network PID Algorithm for Integrated Water and Fertilizer Precision Fertilization Control System for Field Crops
by Fenglei Zhu, Lixin Zhang, Xue Hu, Jiawei Zhao, Zihao Meng and Yu Zheng
Agronomy 2023, 13(5), 1423; https://doi.org/10.3390/agronomy13051423 - 21 May 2023
Cited by 10 | Viewed by 1780
Abstract
China’s field crops such as cotton, wheat, and tomato have been produced on a large scale, but their cultivation process still adopts more traditional manual fertilization methods, which makes the use of chemical fertilizers in China high and causes waste of fertilizer resources [...] Read more.
China’s field crops such as cotton, wheat, and tomato have been produced on a large scale, but their cultivation process still adopts more traditional manual fertilization methods, which makes the use of chemical fertilizers in China high and causes waste of fertilizer resources and ecological environmental damage. To address the above problems, a hybrid optimization of genetic algorithms and particle swarm optimization (GA–PSO) is used to optimize the initial weights of the backpropagation (BP) neural network, and a hybrid optimization-based BP neural network PID controller is designed to realize the accurate control of fertilizer flow in the integrated water and fertilizer precision fertilization control system for field crops. At the same time, the STM32 microcontroller-based precision fertilizer application control system for integrated water and fertilizer application of large field crops was developed and the performance of the controller was verified experimentally. The results show that the controller has an average maximum overshoot of 5.1% and an average adjustment time of 68.99 s, which is better than the PID and PID control algorithms based on BP neural network (BP–PID) controllers; among them, the hybrid optimization of PID control algorithm based on BP neural network by particle swarm optimization and genetic algorithm(GA–PSO–BP–PID) controller has the best-integrated control performance when the fertilizer application flow rate is 0.6m3/h. Full article
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19 pages, 13348 KiB  
Article
Optimizing Planting Density in Alpine Mountain Strawberry Cultivation in Martell Valley, Italy
by Sebastian Soppelsa, Michael Gasser and Massimo Zago
Agronomy 2023, 13(5), 1422; https://doi.org/10.3390/agronomy13051422 - 21 May 2023
Cited by 2 | Viewed by 1791
Abstract
Optimizing profitability is a challenge that strawberry farmers must face in order to remain competitive. Within this framework, plant density can play a central role. The aim of this two-year study was to investigate how planting density can induce variations in plant growth [...] Read more.
Optimizing profitability is a challenge that strawberry farmers must face in order to remain competitive. Within this framework, plant density can play a central role. The aim of this two-year study was to investigate how planting density can induce variations in plant growth and yield performances in an alpine mountain strawberry cultivation (Martell Valley, South Tyrol, Italy), and consequently quantify the farm profit. Frigo strawberry plants cv. Elsanta were planted in soil on raised beds and subjected to five different planting density levels (30,000 and 45,000 as large spacing; 60,000 as middle spacing; 90,000 and 100,000 plants ha−1 as narrow spacing, corresponding to a plant spacing of 28, 19, 14, 9, and 8.5 cm, respectively). Our findings indicate that the aboveground biomass in plants subjected to low planting density was significantly increased by +50% (end of first year) and even doubled in the second year in comparison with plants in high planting density. Those results were related to higher leaf photosynthetic rate (+12%), and the number of crowns and flower trusses per plant (+40% both) (p < 0.05). The low yield (about 300 g plant−1) observed in the high planting density regime was attributable to smaller fruit size during the first cropping year and to both a reduced number of flowers per plant and fruit size during the second year (p < 0.05). Although the highest yield (more than 400 g plant−1) was obtained with wide plant spacing, the greatest yield per hectare was achieved with high planting densities (28 t ha−1 in comparison with 17 t ha−1 with low plant density level). However, the farm profit must take into account the costs (especially related to the plant material and harvesting costs) that are higher under the high planting density compared with the other density regimes. Indeed, the maximum farm profit was reached with a density of 45,000 plants ha−1 which corresponded to EUR 22,579 ha−1 (over 2 years). Regarding fruit quality, fruits coming from the low plant density level showed a significantly higher color index (+15% more red color) than fruits from high plant density (p < 0.05). In conclusion, our results suggest that a middle planting density can be a fair compromise in terms of plant growth, yield, and farm profit. Full article
(This article belongs to the Special Issue Cropping Systems and Agronomic Management Practices of Field Crops)
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17 pages, 6199 KiB  
Article
Detection and Counting of Small Target Apples under Complicated Environments by Using Improved YOLOv7-tiny
by Li Ma, Liya Zhao, Zixuan Wang, Jian Zhang and Guifen Chen
Agronomy 2023, 13(5), 1419; https://doi.org/10.3390/agronomy13051419 - 20 May 2023
Cited by 13 | Viewed by 2337
Abstract
Weather disturbances, difficult backgrounds, the shading of fruit and foliage, and other elements can significantly affect automated yield estimation and picking in small target apple orchards in natural settings. This study uses the MinneApple public dataset, which is processed to construct a dataset [...] Read more.
Weather disturbances, difficult backgrounds, the shading of fruit and foliage, and other elements can significantly affect automated yield estimation and picking in small target apple orchards in natural settings. This study uses the MinneApple public dataset, which is processed to construct a dataset of 829 images with complex weather, including 232 images of fog scenarios and 236 images of rain scenarios, and proposes a lightweight detection algorithm based on the upgraded YOLOv7-tiny. In this study, a backbone network was constructed by adding skip connections to shallow features, using P2BiFPN for multi-scale feature fusion and feature reuse at the neck, and incorporating a lightweight ULSAM attention mechanism to reduce the loss of small target features, focusing on the correct target and discard redundant features, thereby improving detection accuracy. The experimental results demonstrate that the model has an mAP of 80.4% and a loss rate of 0.0316. The mAP is 5.5% higher than the original model, and the model size is reduced by 15.81%, reducing the requirement for equipment; In terms of counts, the MAE and RMSE are 2.737 and 4.220, respectively, which are 5.69% and 8.97% lower than the original model. Because of its improved performance and stronger robustness, this experimental model offers fresh perspectives on hardware deployment and orchard yield estimation. Full article
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22 pages, 3168 KiB  
Article
The Influence of Humic Acids and Nitrophenols on Metabolic Compounds and Pesticide Behavior in Wheat under Biotic Stress
by Piotr Iwaniuk, Stanisław Łuniewski, Piotr Kaczyński and Bożena Łozowicka
Agronomy 2023, 13(5), 1378; https://doi.org/10.3390/agronomy13051378 - 15 May 2023
Cited by 10 | Viewed by 1419
Abstract
Organic biostimulators support wheat growth in unfavorable conditions; however, to date, multifactorial assessments of their role in the plant–pesticide–pathogen system have been poorly investigated. The goal of this study was to evaluate the changes in the metabolite profile (protein, carbohydrate, phenolic compounds, acid [...] Read more.
Organic biostimulators support wheat growth in unfavorable conditions; however, to date, multifactorial assessments of their role in the plant–pesticide–pathogen system have been poorly investigated. The goal of this study was to evaluate the changes in the metabolite profile (protein, carbohydrate, phenolic compounds, acid phosphatases, and amino acids) and the antioxidant potential (antioxidant enzymes) of wheat that is infested with F. culmorum and exposed to humic acids, nitrophenols, and six pesticides. Additionally, the concentration of the mycotoxins in the wheat grain and the dissipation time of the six pesticides in the wheat plants were determined. In this multifactorial experiment, we explored differentiated activities of humic acids and nitrophenols in wheat metabolism during fungal pathogenesis and pesticide protection. Nitrophenols decreased oxidative stress through induced catalase activity. In contrast, humic acids contributed to the highest enhancement of the total level of carbohydrates (27%) in the inoculated wheat. Both biostimulators reduced the mycotoxin concentration (DON, 3-AcDON, 15-AcDON, NIV) by 32% and nitrophenols increased the concentration of amino acids (13%). Unexpectedly, humic acids and nitrophenols shortened the degradation time (DT50) of spiroxamine by up to 60% in inoculated wheat. The overall results of this study provide novel information on the changes in wheat metabolites, antioxidant defense, and pesticide dissipation in the pesticide–biostimulator–pathogen system. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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23 pages, 4024 KiB  
Article
A Remote-Sensing-Assisted Estimation of Water Use in Rice Paddy Fields: A Study on Lis Valley, Portugal
by Susana Ferreira, Juan Manuel Sánchez and José Manuel Gonçalves
Agronomy 2023, 13(5), 1357; https://doi.org/10.3390/agronomy13051357 - 12 May 2023
Cited by 2 | Viewed by 1838
Abstract
Rice culture is one of the most important crops in the world, being the most consumed cereal grain (755 million tons in 2020). Since rice is usually produced under flooding conditions and water performs several essential functions for the crop, estimating its water [...] Read more.
Rice culture is one of the most important crops in the world, being the most consumed cereal grain (755 million tons in 2020). Since rice is usually produced under flooding conditions and water performs several essential functions for the crop, estimating its water needs is essential. Remote sensing techniques have shown effectiveness in estimating and monitoring the water use in crop fields. An estimation from satellite data is a challenge, but could be very useful, in order to spatialize local estimates and operationalize production models. This study intended to derive an approach to estimate the actual crop evapotranspiration (ETa) in rice paddies from a temporal series of satellite images. The experimental data were obtained in the Lis Valley Irrigation District (central coast of Portugal), during the 2019 to 2021 rice growing seasons. The average seasonal ETa (FAO56) resulted 586 ± 23 mm and the water productivity (WP) was 0.47 ± 0.03 kg m−3. Good correlations were found between the crop coefficients (Kc) proposed by FAO and the NDVI evolution in the control rice fields, with R2 ranging between 0.71 and 0.82 for stages II+III (development + middle) and between 0.76 and 0.82 for stage IV (late). The results from the derived RS-assisted method were compared to the ETa values obtained from the surface energy balance model METRIC, showing an average estimation error of ±0.8 mm d−1, with a negligible bias. The findings in this work are promising and show the potential of the RS-assisted method for monitoring ETa and water productivity, capturing the local and seasonal variability in rice growing, and then predicting the rice yield, being a useful and free tool available to farmers. Full article
(This article belongs to the Special Issue Water Saving in Irrigated Agriculture)
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18 pages, 662 KiB  
Article
Effect of Nitrogen Fertilization and Inoculation with Bradyrhizobium japonicum on Nodulation and Yielding of Soybean
by Ewa Szpunar-Krok, Dorota Bobrecka-Jamro, Wojciech Pikuła and Marta Jańczak-Pieniążek
Agronomy 2023, 13(5), 1341; https://doi.org/10.3390/agronomy13051341 - 10 May 2023
Cited by 5 | Viewed by 2018
Abstract
Legumes’ nutrition relies on two sources of nitrogen (N): mineral N from soil, and biological N fixation (BNF). The aim of this study was to verify the effect of bacterial inoculation, as well as to compare it with the effect of different mineral [...] Read more.
Legumes’ nutrition relies on two sources of nitrogen (N): mineral N from soil, and biological N fixation (BNF). The aim of this study was to verify the effect of bacterial inoculation, as well as to compare it with the effect of different mineral N fertilization on the main nodulation characteristics, yield components and seed yield of two soybean (Glycine max (L.) Merr.) cultivars in the conditions of south-eastern Poland. A randomized block design was used with four replications and combining the application rates of mineral N (0, 30 and 60 kg·ha−1), and seed inoculation with Bradyrhizobium japonicum (HiStick® Soy and Nitragina) were applied for two soybean cultivars (Aldana, Annushka). It has been shown that inoculation of B. japonicum increases the nodulation on plant roots, yield components and seed yield, but no significant effect of the bacterial preparation used on the seed yield was observed. The application of 30 kg N·ha−1 did not result in a significant reduction in the number and weight of nodules, including on the main root and lateral roots, compared to seeds inoculated and not fertilized with N, as observed under a dose of 60 kg N·ha−1, but resulted in an increase in the number of pods and the number and weight of seeds per plant. For both soybean cultivars, the best combination was nitrogen fertilization at 30 kg N·ha−1 and seed inoculation with B. japonicum, regardless of the bacterial preparation used. Full article
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12 pages, 1108 KiB  
Article
Optimizing Organic Carrot (Daucus carota var. sativus) Yield and Quality Using Fish Emulsions, Cyanobacterial Fertilizer, and Seaweed Extracts
by Allison Wickham and Jessica G. Davis
Agronomy 2023, 13(5), 1329; https://doi.org/10.3390/agronomy13051329 - 10 May 2023
Cited by 5 | Viewed by 1940
Abstract
Liquid fertilizers are often used in the middle of the growing season in an attempt to enhance organic carrot (Daucus carota var. sativus) yield and quality, although their effect on plant performance is unproven. The impact of liquid organic fertilizers and foliar [...] Read more.
Liquid fertilizers are often used in the middle of the growing season in an attempt to enhance organic carrot (Daucus carota var. sativus) yield and quality, although their effect on plant performance is unproven. The impact of liquid organic fertilizers and foliar seaweed applications on carrot yield and quality characteristics were evaluated on certified organic land at the Colorado State University Horticulture Field Research Center in Fort Collins, CO, USA, in 2014 and 2015. Hydrolyzed and non-hydrolyzed fish fertilizer and cyanobacterial fertilizer (cyano-fertilizer) treatments were applied through a drip irrigation system at prescribed N rates about every 10 days throughout the growing season. Each treatment, including the unfertilized control, was repeated with the addition of concentrated organic seaweed extract, containing phytohormones, applied foliarly at the manufacturer’s recommended rates. The cyano-fertilizer treatment resulted in longer carrots in 2014 and the highest carrot yield in both years, with it consistently yielding equal to or greater than either hydrolyzed or non-hydrolyzed fish fertilizer. The foliar seaweed applications had no effect on carrot yield in either year. The cyano-fertilizer performed comparably to the other fertilizers, suggesting that cyano-fertilizer could be a viable alternative to organic liquid fish fertilizers. Full article
(This article belongs to the Special Issue Application of Organic Amendments in Agricultural Production)
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24 pages, 3061 KiB  
Article
Effect of Low Temperature on Photosynthetic Physiological Activity of Different Photoperiod Types of Strawberry Seedlings and Stress Diagnosis
by Nan Jiang, Zaiqiang Yang, Hanqi Zhang, Jiaqing Xu and Chunying Li
Agronomy 2023, 13(5), 1321; https://doi.org/10.3390/agronomy13051321 - 08 May 2023
Cited by 7 | Viewed by 2301
Abstract
During the early growth stage of plants, low temperatures can alter cell permeability, reduce photosynthetic capacity, and have adverse effects on crop growth, development, and yield. Different strawberry cultivars have varying cold tolerance. In this study, we investigated the changes in cell permeability [...] Read more.
During the early growth stage of plants, low temperatures can alter cell permeability, reduce photosynthetic capacity, and have adverse effects on crop growth, development, and yield. Different strawberry cultivars have varying cold tolerance. In this study, we investigated the changes in cell permeability and photosynthetic activity of short-day and long-day types of strawberry cultivars under varying degrees of low-temperature stress, and evaluated the extent of cellular damage using photosynthetic and chlorophyll fluorescence parameters. The experiment utilized short-day strawberry cultivars ‘Toyonoka’ and ‘Red Face’, and long-day strawberry cultivars ‘Selva’ and ‘Sweet Charlie’ seedlings. Low-temperature treatments were set at −20, −15, −10, −5, 0, 5, and 10 °C for 12 h. The research demonstrated that short-day strawberries had greater tolerance to low temperatures, and all four strawberry cultivars began to experience low-temperature stress when the temperature was below 5 °C. A temperature range of 0 to −10 °C played a crucial role in causing severe cold damage to the strawberries. The low-temperature stress levels were constructed based on electrolyte leakage, with photosynthetic physiological characteristics serving as references. The study proves that the photosynthetic and chlorophyll fluorescence parameters can serve as effective probes for diagnosing low-temperature stress in strawberry seedlings, and their combination provides higher accuracy in identifying stress levels than any single type of parameter. Full article
(This article belongs to the Special Issue Photosynthetic Adaptability of Crops under Environmental Change)
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18 pages, 4301 KiB  
Article
Detection of Litchi Leaf Diseases and Insect Pests Based on Improved FCOS
by Jiaxing Xie, Xiaowei Zhang, Zeqian Liu, Fei Liao, Weixing Wang and Jun Li
Agronomy 2023, 13(5), 1314; https://doi.org/10.3390/agronomy13051314 - 07 May 2023
Cited by 8 | Viewed by 2480
Abstract
Litchi leaf diseases and pests can lead to issues such as a decreased Litchi yield, reduced fruit quality, and decreased farmer income. In this study, we aimed to explore a real-time and accurate method for identifying Litchi leaf diseases and pests. We selected [...] Read more.
Litchi leaf diseases and pests can lead to issues such as a decreased Litchi yield, reduced fruit quality, and decreased farmer income. In this study, we aimed to explore a real-time and accurate method for identifying Litchi leaf diseases and pests. We selected three different orchards for field investigation and identified five common Litchi leaf diseases and pests (Litchi leaf mite, Litchi sooty mold, Litchi anthracnose, Mayetiola sp., and Litchi algal spot) as our research objects. Finally, we proposed an improved fully convolutional one-stage object detection (FCOS) network for Litchi leaf disease and pest detection, called FCOS for Litch (FCOS-FL). The proposed method employs G-GhostNet-3.2 as the backbone network to achieve a model that is lightweight. The central moment pooling attention (CMPA) mechanism is introduced to enhance the features of Litchi leaf diseases and pests. In addition, the center sampling and center loss of the model are improved by utilizing the width and height information of the real target, which effectively improves the model’s generalization performance. We propose an improved localization loss function to enhance the localization accuracy of the model in object detection. According to the characteristics of Litchi small target diseases and pests, the network structure was redesigned to improve the detection effect of small targets. FCOS-FL has a detection accuracy of 91.3% (intersection over union (IoU) = 0.5) in the images of five types of Litchi leaf diseases and pests, a detection rate of 62.0/ms, and a model parameter size of 17.65 M. Among them, the detection accuracy of Mayetiola sp. and Litchi algal spot, which are difficult to detect, reached 93.2% and 92%, respectively. The FCOS-FL model can rapidly and accurately detect five common diseases and pests in Litchi leaf. The research outcome is suitable for deployment on embedded devices with limited resources such as mobile terminals, and can contribute to achieving real-time and precise identification of Litchi leaf diseases and pests, providing technical support for Litchi leaf diseases’ and pests’ prevention and control. Full article
(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland)
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16 pages, 1142 KiB  
Article
Digestate Not Only Affects Nutrient Availability but Also Soil Quality Indicators
by Ana María García-López, Antonio Delgado, Ofélia Anjos and Carmo Horta
Agronomy 2023, 13(5), 1308; https://doi.org/10.3390/agronomy13051308 - 06 May 2023
Cited by 6 | Viewed by 1760
Abstract
Digestate contains many essential nutrients for crops, including nitrogen (N) and phosphorus (P), and it can alter the biogeochemical cycle of nutrients and soil functionality. This work aimed to assess the fertilizing effects of digestate on chemical and biological soil properties in a [...] Read more.
Digestate contains many essential nutrients for crops, including nitrogen (N) and phosphorus (P), and it can alter the biogeochemical cycle of nutrients and soil functionality. This work aimed to assess the fertilizing effects of digestate on chemical and biological soil properties in a field experiment in eastern Portugal with two horticultural crops involving nine treatments: control without fertilization; mineral N fertilization with 85 kg ha−1; fertilization with digestate (DG) with increasing N rates (85, 170, 255, or 340 kg N ha−1); and fertilization with different combinations of digestate plus mineral N (DG at 85 or 170 kg N plus 60 kg mineral N ha–1 or DG at 170 kg N plus 25 kg mineral N ha–1). In addition to N, digestate supplied significant amounts of P, Ca, K, and Mg and significantly increased soil Olsen P, mineral N, and organic C. At high doses, it decreased phosphatase and β-glucosidase activities, as well as fungi and bacterial biomass, compared to the control or mineral N fertilization, and it also negatively affected soil P and C cycling capacity and microbial biomass. The organic to total N ratio and the N to P ratio in digestate are crucial properties for evaluating its agronomic management as fertilizer. Full article
(This article belongs to the Special Issue Soil Conservation Methods for Maintaining Farmlands' Fertility)
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17 pages, 2610 KiB  
Article
Assessing Within-Field Variation in Alfalfa Leaf Area Index Using UAV Visible Vegetation Indices
by Keegan Hammond, Ruth Kerry, Ryan R. Jensen, Ross Spackman, April Hulet, Bryan G. Hopkins, Matt A. Yost, Austin P. Hopkins and Neil C. Hansen
Agronomy 2023, 13(5), 1289; https://doi.org/10.3390/agronomy13051289 - 30 Apr 2023
Cited by 4 | Viewed by 1564
Abstract
This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between [...] Read more.
This study examines the use of leaf area index (LAI) to inform variable-rate irrigation (VRI) for irrigated alfalfa (Medicago sativa). LAI is useful for predicting zone-specific evapotranspiration (ETc). One approach toward estimating LAI is to utilize the relationship between LAI and visible vegetation indices (VVIs) using unmanned aerial vehicle (UAV) imagery. This research has three objectives: (1) to measure and describe the within-field variation in LAI and canopy height for an irrigated alfalfa field, (2) to evaluate the relationships between the alfalfa LAI and various VVIs with and without field average canopy height, and (3) to use UAV images and field average canopy height to describe the within-field variation in LAI and the potential application to VRI. The study was conducted in 2021–2022 in Rexburg, Idaho. Over the course of the study, the measured LAI varied from 0.23 m2 m−2 to 11.28 m2 m−2 and canopy height varied from 6 cm to 65 cm. There was strong spatial clustering in the measured LAI but the spatial patterns were dynamic between dates. Among eleven VVIs evaluated, the four that combined green and red wavelengths but excluded blue wavelengths showed the most promise. For all VVIs, adding average canopy height to multiple linear regression improved LAI prediction. The regression model using the modified green–red vegetation index (MGRVI) and canopy height (R2 = 0.93) was applied to describe the spatial variation in the LAI among VRI zones. There were significant (p < 0.05) but not practical differences (<15%) between pre-defined zones. UAV imagery coupled with field average canopy height can be a useful tool for predicting LAI in alfalfa. Full article
(This article belongs to the Special Issue Imaging Technology for Detecting Crops and Agricultural Products-II)
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13 pages, 2368 KiB  
Article
The Impact of Foliar Fertilization on the Physiological Parameters, Yield, and Quality Indices of the Soybean Crop
by Marius Bărdaş, Teodor Rusu, Florin Russu, Alina Șimon, Felicia Chețan, Ovidiu Adrian Ceclan, Raluca Rezi, Alin Popa and Mihai Marcel Cărbunar
Agronomy 2023, 13(5), 1287; https://doi.org/10.3390/agronomy13051287 - 29 Apr 2023
Cited by 3 | Viewed by 1938
Abstract
Presented research was carried out in 2021 and 2022 on the Felix soybean variety at the Agricultural Research and Development Station Turda, located in the Transylvanian Plain, Romania. In this experiment, complex fertilizer NPK 20:20:0 was applied as a basic fertilizer in a [...] Read more.
Presented research was carried out in 2021 and 2022 on the Felix soybean variety at the Agricultural Research and Development Station Turda, located in the Transylvanian Plain, Romania. In this experiment, complex fertilizer NPK 20:20:0 was applied as a basic fertilizer in a dose of 200 kg ha−1 at the sowing stage, to which foliar fertilizer Agro Argentum Forte treatment was added in different doses and at different application stages. The main purpose of the study was to identify the suitable stages of foliar application in soybean cultivation for effective vegetative development, yield, and quality purposes. The impacts of the fertilization system and the climatic conditions on the physiological parameters, assimilation, yield, and quality were evaluated. Technology showed that the physiological parameters were positively influenced, following the foliar fertilization with Agro Argentum Forte, with average assimilation values recorded above 23.0 μmol CO2 m−2s−1 in the year 2021 and 22.4 μmol CO2 m−2s−1 in the year 2022. Soybean crop was influenced by climatic conditions and the application of foliar fertilizers in different phases of growth and development, obtaining higher yields, as well as higher protein and oil content. The soybean yield and quality indices (protein, oil, and mass of a thousand seeds) were higher in 2021 than in 2022 for the variants treated with foliar fertilizers compared to the control, resulting in an improvement in seed quality in 2021 with a yield of 3560 kg ha−1, while 2022 saw a lower yield of 1805 kg ha−1. The application of basic mineral fertilizers in combination with foliar fertilization had a significantly positive impact on the quality indicators of soybean seeds. The highest yields were achieved when the foliar treatment was applied in the early pod formation stage. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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22 pages, 3254 KiB  
Article
Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models
by Chandan Kumar, Partson Mubvumba, Yanbo Huang, Jagman Dhillon and Krishna Reddy
Agronomy 2023, 13(5), 1277; https://doi.org/10.3390/agronomy13051277 - 28 Apr 2023
Cited by 11 | Viewed by 2581
Abstract
Timely and cost-effective crop yield prediction is vital in crop management decision-making. This study evaluates the efficacy of Unmanned Aerial Vehicle (UAV)-based Vegetation Indices (VIs) coupled with Machine Learning (ML) models for corn (Zea mays) yield prediction at vegetative (V6) and [...] Read more.
Timely and cost-effective crop yield prediction is vital in crop management decision-making. This study evaluates the efficacy of Unmanned Aerial Vehicle (UAV)-based Vegetation Indices (VIs) coupled with Machine Learning (ML) models for corn (Zea mays) yield prediction at vegetative (V6) and reproductive (R5) growth stages using a limited number of training samples at the farm scale. Four agronomic treatments, namely Austrian Winter Peas (AWP) (Pisum sativum L.) cover crop, biochar, gypsum, and fallow with sixteen replications were applied during the non-growing corn season to assess their impact on the following corn yield. Thirty different variables (i.e., four spectral bands: green, red, red edge, and near-infrared and twenty-six VIs) were derived from UAV multispectral data collected at the V6 and R5 stages to assess their utility in yield prediction. Five different ML algorithms including Linear Regression (LR), k-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Regression (SVR), and Deep Neural Network (DNN) were evaluated in yield prediction. One-year experimental results of different treatments indicated a negligible impact on overall corn yield. Red edge, canopy chlorophyll content index, red edge chlorophyll index, chlorophyll absorption ratio index, green normalized difference vegetation index, green spectral band, and chlorophyll vegetation index were among the most suitable variables in predicting corn yield. The SVR predicted yield for the fallow with a Coefficient of Determination (R2) and Root Mean Square Error (RMSE) of 0.84 and 0.69 Mg/ha at V6 and 0.83 and 1.05 Mg/ha at the R5 stage, respectively. The KNN achieved a higher prediction accuracy for AWP (R2 = 0.69 and RMSE = 1.05 Mg/ha at V6 and 0.64 and 1.13 Mg/ha at R5) and gypsum treatment (R2 = 0.61 and RMSE = 1.49 Mg/ha at V6 and 0.80 and 1.35 Mg/ha at R5). The DNN achieved a higher prediction accuracy for biochar treatment (R2 = 0.71 and RMSE = 1.08 Mg/ha at V6 and 0.74 and 1.27 Mg/ha at R5). For the combined (AWP, biochar, gypsum, and fallow) treatment, the SVR produced the most accurate yield prediction with an R2 and RMSE of 0.36 and 1.48 Mg/ha at V6 and 0.41 and 1.43 Mg/ha at the R5. Overall, the treatment-specific yield prediction was more accurate than the combined treatment. Yield was most accurately predicted for fallow than other treatments regardless of the ML model used. SVR and KNN outperformed other ML models in yield prediction. Yields were predicted with similar accuracy at both growth stages. Thus, this study demonstrated that VIs coupled with ML models can be used in multi-stage corn yield prediction at the farm scale, even with a limited number of training data. Full article
(This article belongs to the Special Issue Crop Yield Estimation through Remote Sensing Data)
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20 pages, 5864 KiB  
Article
Spatial Analysis of Soil Moisture and Turfgrass Health to Determine Zones for Spatially Variable Irrigation Management
by Ruth Kerry, Ben Ingram, Keegan Hammond, Samantha R. Shumate, David Gunther, Ryan R. Jensen, Steve Schill, Neil C. Hansen and Bryan G. Hopkins
Agronomy 2023, 13(5), 1267; https://doi.org/10.3390/agronomy13051267 - 28 Apr 2023
Cited by 2 | Viewed by 1045
Abstract
Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research [...] Read more.
Irrigated turfgrass is a major crop in urban areas of the drought-stricken Western United States. A considerable proportion of irrigation water is wasted through the use of conventional sprinkler systems. While smart sprinkler systems have made progress in reducing temporal mis-applications, more research is needed to determine the most appropriate variables for accurately and cost-effectively determining spatial zones for irrigation application. This research uses data from ground and drone surveys of two large sports fields. Surveys were conducted pre-, within and towards the end of the irrigation season to determine spatial irrigation zones. Principal components analysis and k-means classification were used to develop zones using several variables individually and combined. The errors associated with uniform irrigation and different configurations of spatial zones are assessed to determine comparative improvements in irrigation efficiency afforded by spatial irrigation zones. A determination is also made as to whether the spatial zones can be temporally static or need to be re-determined periodically. Results suggest that zones based on spatial soil moisture surveys and simple observations of whether the grass felt wet or dry are better than those based on NDVI, other variables and several variables in combination. In addition, due to the temporal variations observed in spatial patterns, ideally zones should be re-evaluated periodically. However, a less labor-intensive solution is to determine temporally static zones based on patterns in soil moisture averaged from several surveys. Of particular importance are the spatial patterns observed prior to the start of the irrigation season as they reflect more temporally stable variation that relates to soil texture and topography rather than irrigation management. Full article
(This article belongs to the Special Issue The Importance of Soil Spatial Variability in Precision Agriculture)
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30 pages, 3919 KiB  
Review
SRI 2.0 and Beyond: Sequencing the Protean Evolution of the System of Rice Intensification
by Norman Uphoff
Agronomy 2023, 13(5), 1253; https://doi.org/10.3390/agronomy13051253 - 28 Apr 2023
Cited by 5 | Viewed by 2143
Abstract
As the System of Rice Intensification (SRI) has evolved in many ways and in several directions over the past two decades, this review follows the software-naming convention of labeling SRI’s different and subsequent versions as SRI 2.0, 3.0, 4.0, etc. In agroecology as [...] Read more.
As the System of Rice Intensification (SRI) has evolved in many ways and in several directions over the past two decades, this review follows the software-naming convention of labeling SRI’s different and subsequent versions as SRI 2.0, 3.0, 4.0, etc. In agroecology as with software, variants are not necessarily linear and can establish new directions as well as the further evolution of existing ones. This overview reviews how rainfed SRI, direct-seeded SRI, mechanized SRI, and other modifications of the initial SRI methodology have emerged since 2000, and how versions of SRI have been improvised to improve the production of other crops beyond rice, like wheat, finger millet, maize, and sugar cane. SRI thinking and practices are also being incorporated into diversified farming systems, broadening the logic and impact of SRI beyond monoculture rice cultivation, and SRI methods are also being used to achieve broader objectives like the reduction of greenhouse gas emissions and the conservation of biodiversity. SRI observations and research have been contributing to the crop and soil sciences by focusing attention on plant roots and soil ecology and by showing how crop management can elicit more desirable phenotypes from a given genotype. Cooperation regarding SRI among farmers, civil-society actors, scientists, private sector agents, governments, and funding agencies has begun introducing noteworthy changes within the agricultural sector, and this collaboration is expected to deepen and expand. Full article
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34 pages, 1330 KiB  
Article
Effect of Climatic Conditions, and Agronomic Practices Used in Organic and Conventional Crop Production on Yield and Nutritional Composition Parameters in Potato, Cabbage, Lettuce and Onion; Results from the Long-Term NFSC-Trials
by Leonidas Rempelos, Marcin Barański, Enas Khalid Sufar, Jenny Gilroy, Peter Shotton, Halima Leifert, Dominika Średnicka-Tober, Gultekin Hasanaliyeva, Eduardo A. S. Rosa, Jana Hajslova, Vera Schulzova, Ismail Cakmak, Levent Ozturk, Kirsten Brandt, Chris Seal, Juan Wang, Christoph Schmidt and Carlo Leifert
Agronomy 2023, 13(5), 1225; https://doi.org/10.3390/agronomy13051225 - 26 Apr 2023
Cited by 8 | Viewed by 2162
Abstract
Background: There is increasing evidence that the reliance on synthetic chemical pesticides and mineral fertilizers in agriculture has significant negative environmental and/or health impacts and poses a risk for future food security. Systematic reviews/meta-analyses showed that organic production systems, which omit the use [...] Read more.
Background: There is increasing evidence that the reliance on synthetic chemical pesticides and mineral fertilizers in agriculture has significant negative environmental and/or health impacts and poses a risk for future food security. Systematic reviews/meta-analyses showed that organic production systems, which omit the use of agrochemicals, produce crops with lower yields, but superior nutritional composition. However, the agronomic parameters responsible for differences in crop yields and nutritional quality are poorly understood. Methods: Here we report results for four field vegetable crops from the Nafferton Factorial Systems Comparison (NFSC) trial. This long-term factorial field experiment was designed to (i) identify effects of growing season/climatic variation, and contrasting rotational designs, crop protection protocols and fertilization regimes used in organic and conventional systems on crop health, yield and nutritional parameters and (ii) estimate the relative importance of climatic and agronomic drivers for crop health, yield and nutritionally relevant quality parameters. Quality parameters monitored in harvested products, included phenolic, glucosinolate, vitamin C, vitamin B9, carotenoid, cadmium (Cd), nickel (Ni), lead (Pb) and glycoalkaloid concentrations. Results: Climatic conditions during the growing season were found to have a larger impact on crop yield and quality than the agronomic factors (pre-crop, crop protection, fertilization) studied. However, the (i) interactions between growing season with contrasting climatic conditions and agronomic factors identified by ANOVA for crop health, yield and quality parameters and (ii) the associations between the three climatic drivers (precipitation, temperature, radiation) and crop yield and quality parameters differed substantially between the four crop plant species. Among the agronomic factors, fertilization had a substantially larger impact compared with both pre-crop and crop protection. Specifically, crop yields were found to be significantly increased by the use of (i) conventional fertilization and crop protection methods in potato, (ii) conventional fertilization, but organic crop protection methods in cabbage, and (iii) conventional fertilization regimes in lettuce, while none of the agronomic factors had a significant effect on onion yields. When important crop pest and diseases were assessed, (i) conventional crop protection resulted in significantly lower late blight severity in potato, while (ii) organic crop protection resulted in lower bird damage and cabbage root fly (CRF) incidence in cabbages, and Sclerotinia incidence in lettuce and (iii) organic fertilization resulted in lower CRF and Sclerotinia incidence in cabbage and lettuce respectively. When concentrations of nutritionally relevant phytochemicals were compared, organic fertilization resulted in significantly higher phenolic concentrations in potato, cabbage and lettuce, higher glucosinolate and carotenoid concentrations in cabbage, higher vitamin C concentrations in potato and cabbage and higher vitamin B9 concentrations in potato and lettuce—but lower concentrations of toxic glycoalkaloids in potato. Significant effects of crop protection protocols on phytochemical concentrations were only detected in cabbage with conventional crop protection resulting in higher glucosinolate and vitamin B9 concentrations. When toxic metal concentrations were compared, organic fertilization resulted in significantly lower Cd concentrations in all four crops and lower Ni concentrations in potato, cabbage and onion. Significant effects of crop protection were only detected in cabbage, where organic crop protection resulted in lower Ni concentrations. Pb concentrations were not affected by any of the agronomic factors. The potential implications of results for improving (i) strategies to reduce the use of non-renewable resources and environmental impacts of vegetable production and (ii) the productivity of organic and other low-input vegetable production systems without compromising food quality are discussed. Conclusions: The study confirms that organic vegetable production protocols result in higher concentrations of phenolics and other nutritionally desirable phytochemicals, but lower concentrations of the toxic metals Cd and Ni in harvested products. It also demonstrates, for the first time, that this is primarily due to differences in fertilization regimes. The finding that in three of the four crops (cabbage, lettuce and onion) the application of synthetic chemical crop protection products had no measurable positive impact on crop health and yield should be considered in the context of the growing concern about health impacts of pesticide use in field vegetable crops. Full article
(This article belongs to the Collection Innovative Organic and Regenerative Agricultural Production)
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23 pages, 6372 KiB  
Article
High-Throughput Canopy and Belowground Phenotyping of a Set of Peanut CSSLs Detects Lines with Increased Pod Weight and Foliar Disease Tolerance
by Davis Gimode, Ye Chu, Corley C. Holbrook, Daniel Fonceka, Wesley Porter, Iliyana Dobreva, Brody Teare, Henry Ruiz-Guzman, Dirk Hays and Peggy Ozias-Akins
Agronomy 2023, 13(5), 1223; https://doi.org/10.3390/agronomy13051223 - 26 Apr 2023
Cited by 2 | Viewed by 1329
Abstract
We deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. [...] Read more.
We deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. A combination of aerial imaging and manual scoring showed that CSSL 100, CSSL 84, CSSL 111, and CSSL 15 had remarkably low tomato spotted wilt virus (TSWV) incidence, a devastating disease in South Georgia, USA. The four lines also performed well under leaf spot pressure. The vegetative indices showed strong correlations of up to 0.94 with visual disease scores, indicating that aerial phenotyping is a reliable way of selecting under disease pressure. Since the yield components of peanut are below the soil surface, we deployed ground penetrating radar (GPR) technology to detect pods non-destructively. Moderate correlations of up to 0.5 between pod weight and data acquired from GPR signals were observed. Both the manually acquired pod data and GPR variables highlighted the three lines, CSSL 84, CSSL 100, and CSSL 111, as the best-performing lines, with pod weights comparable to the cultivated check Tifguard. Through the combined application of manual and HTP techniques, this study reinforces the premise that chromosome segments from peanut wild relatives may be a potential source of valuable agronomic traits. Full article
(This article belongs to the Special Issue Omics Approaches for Crop Improvement)
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25 pages, 11777 KiB  
Review
Review of the Underutilized Indigenous Portulacaria afra (Spekboom) as a Sustainable Edible Food Source
by Alba du Toit, Rozanne MacDonald, Elmay Steyn, Zamancwane P. Mahlanza, Ayanda B. Zulu and Maryna de Wit
Agronomy 2023, 13(5), 1206; https://doi.org/10.3390/agronomy13051206 - 25 Apr 2023
Cited by 3 | Viewed by 2255
Abstract
Southern Africa faces numerous challenges, such as increasing biodiversity loss and environmental degradation. Additionally, poor and vulnerable communities suffer from undernourishment and are food insecure. Therefore, Southern Africa must adopt inclusive, sustainable food systems that support food security, even under harsh climatic conditions. [...] Read more.
Southern Africa faces numerous challenges, such as increasing biodiversity loss and environmental degradation. Additionally, poor and vulnerable communities suffer from undernourishment and are food insecure. Therefore, Southern Africa must adopt inclusive, sustainable food systems that support food security, even under harsh climatic conditions. Wild edible plants can potentially strengthen South African communities’ diets, as they are nutritious, freely available and adapted to survive in marginal conditions. Portulacaria afra, colloquially known as spekboom, is an indigenous succulent to South Africa. This edible plant is resilient even when exposed to weather extremes and is exceptionally easy to grow. Spekboom can potentially contribute to food security since food-insecure communities can access the plant in a socially acceptable way. However, spekboom awaits culinary development to increase its consumption. This review presents the current knowledge of spekboom. As there is limited published research, the review aims to stimulate research in food science and nutrition on this undervalued plant and introduce it as a new food and ingredient. Full article
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36 pages, 1102 KiB  
Review
Breeding Wheat for Powdery Mildew Resistance: Genetic Resources and Methodologies—A Review
by Theresa Bapela, Hussein Shimelis, Tarekegn Terefe, Salim Bourras, Javier Sánchez-Martín, Dimitar Douchkov, Francesca Desiderio and Toi John Tsilo
Agronomy 2023, 13(4), 1173; https://doi.org/10.3390/agronomy13041173 - 20 Apr 2023
Cited by 4 | Viewed by 3444
Abstract
Powdery mildew (PM) of wheat caused by Blumeria graminis f. sp. tritici is among the most important wheat diseases, causing significant yield and quality losses in many countries worldwide. Considerable progress has been made in resistance breeding to mitigate powdery mildew. Genetic host [...] Read more.
Powdery mildew (PM) of wheat caused by Blumeria graminis f. sp. tritici is among the most important wheat diseases, causing significant yield and quality losses in many countries worldwide. Considerable progress has been made in resistance breeding to mitigate powdery mildew. Genetic host resistance employs either race-specific (qualitative) resistance, race-non-specific (quantitative), or a combination of both. Over recent decades, efforts to identify host resistance traits to powdery mildew have led to the discovery of over 240 genes and quantitative trait loci (QTLs) across all 21 wheat chromosomes. Sources of PM resistance in wheat include landraces, synthetic, cultivated, and wild species. The resistance identified in various genetic resources is transferred to the elite genetic background of a well-adapted cultivar with minimum linkage drag using advanced breeding and selection approaches. In this effort, wheat landraces have emerged as an important source of allelic and genetic diversity, which is highly valuable for developing new PM-resistant cultivars. However, most landraces have not been characterized for PM resistance, limiting their use in breeding programs. PM resistance is a polygenic trait; therefore, the degree of such resistance is mostly influenced by environmental conditions. Another challenge in breeding for PM resistance has been the lack of consistent disease pressure in multi-environment trials, which compromises phenotypic selection efficiency. It is therefore imperative to complement conventional breeding technologies with molecular breeding to improve selection efficiency. High-throughput genotyping techniques, based on chip array or sequencing, have increased the capacity to identify the genetic basis of PM resistance. However, developing PM-resistant cultivars is still challenging, and there is a need to harness the potential of new approaches to accelerate breeding progress. The main objective of this review is to describe the status of breeding for powdery mildew resistance, as well as the latest discoveries that offer novel ways to achieve durable PM resistance. Major topics discussed in the review include the genetic basis of PM resistance in wheat, available genetic resources for race-specific and adult-plant resistance to PM, important gene banks, and conventional and complimentary molecular breeding approaches, with an emphasis on marker-assisted selection (MAS). Full article
(This article belongs to the Special Issue Crop Powdery Mildew—Series II)
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16 pages, 6361 KiB  
Communication
Hybrid CNN-SVM Classifier Approaches to Process Semi-Structured Data in Sugarcane Yield Forecasting Production
by Debnath Bhattacharyya, Eali Stephen Neal Joshua, N. Thirupathi Rao and Tai-hoon Kim
Agronomy 2023, 13(4), 1169; https://doi.org/10.3390/agronomy13041169 - 20 Apr 2023
Cited by 4 | Viewed by 1757
Abstract
Information communication technology (ICT) breakthroughs have boosted global social and economic progress. Most rural Indians rely on agriculture for income. The growing population requires modern agricultural practices. ICT is crucial for educating farmers on how to be environmentally friendly. It helps them create [...] Read more.
Information communication technology (ICT) breakthroughs have boosted global social and economic progress. Most rural Indians rely on agriculture for income. The growing population requires modern agricultural practices. ICT is crucial for educating farmers on how to be environmentally friendly. It helps them create more food by solving a variety of challenges. India’s sugarcane crop is popular and lucrative. Long-term crops that require water do not need specific soil. They need water; the ground should always have adequate water due to the link between cane growth and evaporation. This research focuses on forecasting soil moisture and classifying sugarcane output; sugarcane has so many applications that it must be categorized. This research examines these claims: The first phase model predicts soil moisture using two-level ensemble classifiers. Secondly, to boost performance, the proposed ensemble model integrates the Gaussian probabilistic method (GPM), the convolutional neural network (CNN), and support vector machines (SVM). The suggested approach aims to correctly anticipate future soil moisture measurements affecting crop growth and cultivation. The proposed model is 89.53% more accurate than conventional neural network classifiers. The recommended models’ outcomes will assist farmers and agricultural authorities in boosting production. Full article
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15 pages, 476 KiB  
Article
The Impact of Rotational Pasture Management for Farm-Bred Fallow Deer (Dama dama) on Fodder Quality in the Context of Animal Welfare
by Mariusz Kulik, Katarzyna Tajchman, Antoni Lipiec, Maciej Bąkowski, Aleksandra Ukalska-Jaruga, Francisco Ceacero, Monika Pecio and Żaneta Steiner-Bogdaszewska
Agronomy 2023, 13(4), 1155; https://doi.org/10.3390/agronomy13041155 - 19 Apr 2023
Cited by 2 | Viewed by 1638
Abstract
Extensive breeding of farmed cervids, similarly to other livestock, affects the vegetation of grasslands in different seasons. For this reason, the impact of the rotational grazing of fallow deer on the chemical and species composition of the pasture sward was assessed, along with [...] Read more.
Extensive breeding of farmed cervids, similarly to other livestock, affects the vegetation of grasslands in different seasons. For this reason, the impact of the rotational grazing of fallow deer on the chemical and species composition of the pasture sward was assessed, along with the possibility of using these animals for grasslands conservation. The species composition of the pastures was analysed through the botanical-weight method. A quality index and mineral concentration test by inductively coupled plasma mass spectrometry were used to evaluate the feed. The highest proportion of valuable grasses, such as Dactylis glomerata, Poa pratensis and Lolium perenne, was recorded in the summer pens (65.7–66.1%), while the smallest proportion was recorded in the control area (46.1%). The estimated yield potential was relatively large, from 5.74 to 7.02 t ha−1 dry matter. The lowest total protein content occurred in the control area in the spring and autumn. The summer pens, including the sown one, had a better fodder quality, depending on the species composition. All pens were characterised by a high production potential and similar floristic composition, without the participation of undesirable plant species, which confirms the hypothesis that, under extensive grazing conditions, fallow deer can be used for grassland conservation. Full article
(This article belongs to the Special Issue Advance in Grassland Productivity and Sustainability)
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19 pages, 3862 KiB  
Article
Modeling Soil Organic Carbon Dynamics of Arable Land across Scales: A Simplified Assessment of Alternative Management Practices on the Level of Administrative Units
by Felix Witing, Martin Volk and Uwe Franko
Agronomy 2023, 13(4), 1159; https://doi.org/10.3390/agronomy13041159 - 19 Apr 2023
Cited by 3 | Viewed by 1250
Abstract
Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale [...] Read more.
Regional assessments of soil organic carbon (SOC) trends and the carbon sequestration potential of alternative management practices (AMP) are highly relevant for developing climate change mitigation strategies for the agricultural sector. Such studies could benefit from simplified SOC modeling approaches on the scale of administrative units as this often corresponds to the level of policy-making and data availability. However, there is a risk of systematic errors in such scaling operations. To overcome this problem, we performed a scaling experiment where we simulated the SOC dynamics of the arable soils of the State of Saxony (Germany) across a series of scales using the CANDY Carbon Balance (CCB) model. Specifically, we developed model set-ups on four different administrative levels (NUTS1, NUTS2, NUTS3, and LAU) and evaluated the simulation results of the upscaled models against a 500 m grid-based reference model. Furthermore, we quantified the carbon sequestration potential of selected AMP scenarios (addressing field grass, cover crops, and conservation tillage) across all scales. The upscaled model set-ups adequately simulated the SOC trends of Saxon arable land compared to the grid-based reference simulation (scaling error: 0.8–3.8%), while providing significant benefits for model application, data availability and runtime. The carbon sequestration potential of the AMP scenarios (1.33 Mt C until 2050) was slightly overestimated (+0.07–0.09 Mt C) by the upscaled model set-ups. Regardless of the scale of model set-up, we showed that the use of aggregated statistical input data could lead to a systematic underestimation of SOC trends. LAU and NUTS3 levels were shown to be a suitable compromise for effectively quantifying SOC dynamics and allowed for an acceptable spatial prioritization of AMPs. Such simplified, scale-adapted assessments are valuable for cross-regional comparisons and for communication to and among decision-makers, and might provide a quantitative basis for discussions on the effectiveness of AMPs in various stakeholder processes. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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20 pages, 1930 KiB  
Article
Screening Canola Genotypes for Resistance to Ammonium Toxicity
by Omar Ali Shaban Al-Awad, Kit Stasia Prendergast, Alan Robson and Zed Rengel
Agronomy 2023, 13(4), 1150; https://doi.org/10.3390/agronomy13041150 - 18 Apr 2023
Cited by 2 | Viewed by 1018
Abstract
Soil ammonium toxicity can decrease plant growth, and many crop species have low resistance to ammonium, including canola, an economically important crop. Different genotypes may differ in their resistance to ammonium toxicity, and therefore determining if there are genotypes that exhibit variation in [...] Read more.
Soil ammonium toxicity can decrease plant growth, and many crop species have low resistance to ammonium, including canola, an economically important crop. Different genotypes may differ in their resistance to ammonium toxicity, and therefore determining if there are genotypes that exhibit variation in their ability to tolerate soil ammonium is a research priority. Here, we evaluate how soil ammonium impacts canola root and shoot growth and characterise differences among canola genotypes in regard to resistance to ammonium toxicity. In the first experiment, eight ammonium chloride treatments and five calcium nitrate treatments were tested for their impact on the canola genotype Crusher TT, where high application (60 mg N/kg soil) significantly decreased the dry weight of canola shoots and roots and acidified the soil from pHCaCl2 5.9 to 5.6. In the second experiment, 30 canola genotypes were screened at selected concentrations of NH4+-N, using nitrate as the control. There was wide variation among genotypes in sensitivity to high NH4+-N application. Genotypes G16, G26, and G29 had greater shoot dry weights and the highest shoot N concentration of all genotypes, and G16, G26, and G28 had root dry weight up to 35% higher at high soil NH4+-N compared with other genotypes. In contrast, genotypes G3, G13, and G30 showed the largest reduction in shoot weight, and genotypes G13, G23, and G30 showed the largest reduction in root weight at high NH4+-N application. Residual NH4+-N/kg soil in soil was higher for sensitive than resistant genotypes, suggesting lower NH4+-N use in the former. These results reveal the potential for selecting canola genotypes that are resistant to high NH4+-N concentrations in soil. Full article
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13 pages, 2926 KiB  
Article
Wheat Response and Weed-Suppressive Ability in the Field Application of a Nanoencapsulated Disulfide (DiS-NH2) Bioherbicide Mimic
by Aurelio Scavo, Francisco J. R. Mejías, Nuria Chinchilla, José M. G. Molinillo, Stefan Schwaiger, Sara Lombardo, Francisco A. Macías and Giovanni Mauromicale
Agronomy 2023, 13(4), 1132; https://doi.org/10.3390/agronomy13041132 - 16 Apr 2023
Cited by 2 | Viewed by 1316
Abstract
Improving the efficacy of bioherbicides to overcome weed resistance phenomena is one of the main challenges within agriculture. Organic encapsulation is attracting attention as an alternative and eco-friendly tool, mainly in organic farming. In this research, for the first time, across three different [...] Read more.
Improving the efficacy of bioherbicides to overcome weed resistance phenomena is one of the main challenges within agriculture. Organic encapsulation is attracting attention as an alternative and eco-friendly tool, mainly in organic farming. In this research, for the first time, across three different wheat field trials, we tested the weed-suppressive ability (WSA) and crop response of a nanoparticle formulation of DiS-NH2 (2,2′-disulfanediyldianiline) applied as post-emergence foliar herbicide, both at standard (T1, 0.75 g m−2) and double dosages (T2, 1.5 g m−2), compared to no weeding (NC) and chemical weed control (PC). Averaged over locations, T2 showed the highest WSA (51.3%), followed by T1 (40.9%) and PC (33.5%). T2 induced also a wheat grain yield and a plant height comparable to PC (3185 kg ha−1 and 67.7 cm vs. 3153 kg ha−1 and 67.7 cm, respectively). Moreover, compared to NC, T2 increased the number of spikes m−2 (+19%) and the number of kernel spikes−1 (+26%). Similar results were observed for T1, which caused also a significant reduction in non-vitreous kernels (‒40%). These promising results suggest that the nanoencapsulated DiS-NH2 could be a good candidate as a post-emergence bioherbicide in wheat crop production. Full article
(This article belongs to the Special Issue The Future of Weed Science—Novel Approaches to Weed Management)
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25 pages, 1894 KiB  
Review
Vermicompost: Enhancing Plant Growth and Combating Abiotic and Biotic Stress
by Sami ur Rehman, Federica De Castro, Alessio Aprile, Michele Benedetti and Francesco Paolo Fanizzi
Agronomy 2023, 13(4), 1134; https://doi.org/10.3390/agronomy13041134 - 16 Apr 2023
Cited by 25 | Viewed by 14281
Abstract
Extensive application of agrochemicals for crop production and protection has negatively affected soil health, crop productivity, and the environment. Organic amendments have been proposed as an efficient alternative for enhancing soil and plant health. Vermicompost amendment offers a sustainable approach to plant nutrition, [...] Read more.
Extensive application of agrochemicals for crop production and protection has negatively affected soil health, crop productivity, and the environment. Organic amendments have been proposed as an efficient alternative for enhancing soil and plant health. Vermicompost amendment offers a sustainable approach to plant nutrition, improving soil health and fertility. This review aims to provide key insights into the potential of vermicompost to boost crop production and protect crops from biotic and abiotic stresses without harming the environment. The role played by earthworms in improving organic matter decomposition, soil fertility, and soil microorganisms’ activity is also discussed here. The value of vermicompost is its promotion of plant growth based on its enrichment with all essential nutrients, beneficial microbes, and plant growth hormones. This review analyzes how vermicompost regulates plant growth and its role in mitigating abiotic stresses such as soil salinity and drought, as well as biotic stresses such as diseases and insect pests attack. The beneficial effects of hormones and humic substances present in vermicompost are also discussed in this review. In fact, due to its properties, vermicompost can be a good substitute for chemical fertilizers and pesticides and its usage could contribute to producing healthy, contaminant-free food for the growing population without negatively affecting the environment. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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14 pages, 1963 KiB  
Article
Irrigation Zone Delineation and Management with a Field-Scale Variable Rate Irrigation System in Winter Wheat
by Elisa A. Flint, Bryan G. Hopkins, Jeffery D. Svedin, Ruth Kerry, Matthew J. Heaton, Ryan R. Jensen, Colin S. Campbell, Matt A. Yost and Neil C. Hansen
Agronomy 2023, 13(4), 1125; https://doi.org/10.3390/agronomy13041125 - 15 Apr 2023
Cited by 3 | Viewed by 1642
Abstract
Understanding spatial and temporal dynamics of soil water within fields is critical for effective variable rate irrigation (VRI) management. The objectives of this study were to develop VRI zones, manage irrigation rates within VRI zones, and examine temporal differences in soil volumetric water [...] Read more.
Understanding spatial and temporal dynamics of soil water within fields is critical for effective variable rate irrigation (VRI) management. The objectives of this study were to develop VRI zones, manage irrigation rates within VRI zones, and examine temporal differences in soil volumetric water content (VWC) from irrigation events via soil sensors across zones. Five irrigation zones were delineated after two years (2016 and 2017) of yield and evapotranspiration (ET) data collection. Soil sensors were placed within each zone to give real time data of VWC values and assist in irrigation decisions within a 23 ha field of winter wheat (Triticum aestivum ‘UI Magic’) near Grace, Idaho, USA (2019). Cumulative irrigation rates among zones ranged from 236 to 298 mm. Although a statistical comparison could not be made, the irrigation rates were 0.6 to 21% less than an estimated uniform grower standard practice (GSP) irrigation approach. Based on soil sensor data, crop water stress was avoided with VRI management in all but Zone 3. Thus, this simple approach to VRI zone delineation and VWC monitoring has the potential to reduce irrigation, such as this study, on average by 12% and should be evaluated in other site-years to assess its viability. Full article
(This article belongs to the Special Issue The Importance of Soil Spatial Variability in Precision Agriculture)
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