Agriculture

26 pages, 12720 KiB

Open AccessArticle

Real-Time Plant Health Detection Using Deep Convolutional Neural Networks

by Mahnoor Khalid, Muhammad Shahzad Sarfraz, Uzair Iqbal, Muhammad Umar Aftab, Gniewko Niedbała and Hafiz Tayyab Rauf

Agriculture 2023, 13(2), 510; https://doi.org/10.3390/agriculture13020510 - 20 Feb 2023

Cited by 15 | Viewed by 7132

Abstract

In the twenty-first century, machine learning is a significant part of daily life for everyone. Today, it is adopted in many different applications, such as object recognition, object classification, and medical purposes. This research aimed to use deep convolutional neural networks for the [...] Read more.

In the twenty-first century, machine learning is a significant part of daily life for everyone. Today, it is adopted in many different applications, such as object recognition, object classification, and medical purposes. This research aimed to use deep convolutional neural networks for the real-time detection of diseases in plant leaves. Typically, farmers are unaware of diseases on plant leaves and adopt manual disease detection methods. Their production often decreases as the virus spreads. However, due to a lack of essential infrastructure, quick identification needs to be improved in many regions of the world. It is now feasible to diagnose diseases using mobile devices as a result of the increase in mobile phone usage globally and recent advancements in computer vision due to deep learning. To conduct this research, firstly, a dataset was created that contained images of money plant leaves that had been split into two primary categories, specifically (i) healthy and (ii) unhealthy. This research collected thousands of images in a controlled environment and used a public dataset with exact dimensions. The next step was to train a deep model to identify healthy and unhealthy leaves. Our trained YOLOv5 model was applied to determine the spots on the exclusive and public datasets. This research quickly and accurately identified even a small patch of disease with the help of YOLOv5. It captured the entire image in one shot and forecasted adjacent boxes and class certainty. A random dataset image served as the model’s input via a cell phone. This research is beneficial for farmers since it allows them to recognize diseased leaves as soon as they noted and take the necessary precautions to halt the disease’s spread. This research aimed to provide the best hyper-parameters for classifying and detecting the healthy and unhealthy parts of leaves in exclusive and public datasets. Our trained YOLOv5 model achieves 93 % accuracy on a test set. Full article

(This article belongs to the Special Issue Digital Innovations in Agriculture)

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23 pages, 10689 KiB

Open AccessArticle

Integrated Metabolome and Transcriptome Analysis Unveils the Underlying Molecular Response of Panax ginseng Plants to the Phytophthora cactorum Infection

by Hong Kan, Shuai Qu, Kai Dong, Shihan Wang, Chen Xu, Yingping Wang and Shuang Hua

Agriculture 2023, 13(2), 509; https://doi.org/10.3390/agriculture13020509 - 20 Feb 2023

Cited by 1 | Viewed by 2213

Abstract

Due to at least 3 years of cultivation, Panax ginseng (ginseng) is susceptible to being attacked by pathogens which severely affect its quality and yield. Compared with other diseases of ginseng, Phytophthora blight caused by Phytophthora cactorum (P. cactorum) can spread [...] Read more.

Due to at least 3 years of cultivation, Panax ginseng (ginseng) is susceptible to being attacked by pathogens which severely affect its quality and yield. Compared with other diseases of ginseng, Phytophthora blight caused by Phytophthora cactorum (P. cactorum) can spread rapidly and destroy almost the entire plant of ginseng, such as leaves, stems, and roots. However, little research was focused on this area, and how P. cactorum affected the metabolic profile of ginseng is still obscure. In the current study, we conducted a comprehensive analysis of metabolomics and transcriptomics to compare the differences in health and P. cactorum-affected ginseng leaves and stems. Metabolome analysis revealed that 110 and 113 significant differential metabolites were observably disturbed separately in ginseng leaves and stems. Transcriptome analysis demonstrated that 6424 and 9508 genes had remarkable variation in ginseng leaves and stems. Using conjoint analysis, we also revealed the changes in pathways “Alanine, aspartate and glutamate metabolism”, “Glycine, serine and threonine metabolism”, and “Biosynthesis of unsaturated fatty acids” and “Plant hormone signal transduction” in ginseng response to the P. cactorum. The current work provides an overview of the alteration of metabolic profile and gene expression profiles in ginseng leaves and stems in response to P. cactorum affection, which may help to further screen out the mechanism of plant-pathogen interaction at the molecular level. Full article

(This article belongs to the Topic Interaction between Plants and Fungi and Oomycetes)

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17 pages, 4663 KiB

Open AccessArticle

The Tradeoff between Maintaining Maize (Zea mays L.) Productivity and Improving Soil Quality under Conservation Tillage Practice in Semi-Arid Region of Northeast China

by Nana Chen, Xin Zhao, Shuxian Dou, Aixing Deng, Chengyan Zheng, Tiehua Cao, Zhenwei Song and Weijian Zhang

Agriculture 2023, 13(2), 508; https://doi.org/10.3390/agriculture13020508 - 20 Feb 2023

Cited by 2 | Viewed by 1732

Abstract

Conservation tillage has received strong support globally to achieve food security and minimize environmental impacts. However, there are comprehensive debates on whether it can achieve the synergy between maintaining crop yields and improving soil quality. To this end, a field experiment under continuous [...] Read more.

Conservation tillage has received strong support globally to achieve food security and minimize environmental impacts. However, there are comprehensive debates on whether it can achieve the synergy between maintaining crop yields and improving soil quality. To this end, a field experiment under continuous maize (Zea mays L.) cropping was conducted in northeast China. The treatment included rotary tillage with straw removal (CK, conventional tillage) and rotary tillage, subsoiling tillage, and no tillage with straw retention (CR, CS, and CN, respectively). Maize yield and a set of soil physio-chemical indicators in relation with soil quality were measured during 2017 to 2021. Results showed that CN significantly reduced the maize yield by 24.9%, 23.1%, and 19.5% on average compared to that with CR, CK, and CS treatments, respectively. CN and CS significantly increased the ratio of >2 mm soil aggregates and soil geometric mean diameter (GMD) in the 0–20 cm soil layer compared those of CK and CR treatments. However, CN and CS treatments had a higher soil bulk density and soil compaction in the 0–20 cm layer compared to those with CK and CR treatments. Soil organic carbon and total nitrogen in the 0–20 cm layer under CN and CS were higher than those with CK by 5.1–15.0% and 8.5–15.7%, whereas soil NH₄⁺ was lower by 9.1–13.9% correspondingly. CN also reduced the soil temperature during the early-growth stage of maize. Importance analysis indicated that soil temperature, bulk density, and available nitrogen were the key factors affecting maize yield. Overall, no tillage with straw mulching could improve soil stability and soil fertility but reduced maize yield. Alternatively, minimum tillage (e.g., subsoiling tillage) with straw mulching might be a suitable practice as it maintains the maize yield and improves soil quality compared to those with conventional tillage practices in the semi-arid region of northeast China in the short term. Full article

(This article belongs to the Topic Plant-Soil Interactions)

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15 pages, 1398 KiB

Open AccessArticle

Land Use and Land Cover Change Determinants in Raya Valley, Tigray, Northern Ethiopian Highlands

by Eskinder Gidey, Oagile Dikinya, Reuben Sebego, Eagilwe Segosebe, Amanuel Zenebe, Said Mussa, Paidamwoyo Mhangara and Emiru Birhane

Agriculture 2023, 13(2), 507; https://doi.org/10.3390/agriculture13020507 - 20 Feb 2023

Cited by 5 | Viewed by 2264

Abstract

Land use and land cover change (LULCC) is the result of both natural and socio-economic determinants. The aim of this study was to model the determinant factors of land cover changes in Raya Valley, Southern Tigray, Ethiopia. Multistage sampling was used to collect [...] Read more.

Land use and land cover change (LULCC) is the result of both natural and socio-economic determinants. The aim of this study was to model the determinant factors of land cover changes in Raya Valley, Southern Tigray, Ethiopia. Multistage sampling was used to collect data from 246 households sampled from lowlands (47), midlands (104), highlands (93), and sub-alpine (2) agro-climatological zone. Descriptive statistics and logit regression model were used to analyze the field survey data. Agricultural land expansion, fuelwood extraction, deforestation, overgrazing and expansion of infrastructure were the proximate causes of LULCC in the study area. Agricultural land expansion (p = 0.084) and wood extraction for fuel and charcoal production (p = 0.01) were the prominent causes for LULCC. Persistent drought (p = 0.001), rapid population growth (p = 0.027), and climate variability (p = 0.013) were the underlying driving factors of LULCC. The determinants of LULCC need to be considered and mitigated to draw robust land use policy for sustainable land management by the smallholder farmers. This study provides important results for designing and implementing scientific land management strategies by policy makers and land managers. Full article

(This article belongs to the Special Issue Agroforestry Planning)

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21 pages, 4075 KiB

Open AccessArticle

Estimating Yield and Economic Losses Induced by Ozone Exposure in South China Based on Full-Coverage Surface Ozone Reanalysis Data and High-Resolution Rice Maps

by Jie Pei, Pengyu Liu, Huajun Fang, Xinyu Gao, Baihong Pan, Haolin Li, Han Guo and Feng Zhang

Agriculture 2023, 13(2), 506; https://doi.org/10.3390/agriculture13020506 - 20 Feb 2023

Cited by 3 | Viewed by 1799

Abstract

Surface ozone (O₃) pollution is an emerging environmental abiotic stress that poses substantial risks to crop yield losses and food security worldwide, and especially in China. However, the O₃-induced detrimental effects on double-season rice have rarely been investigated at [...] Read more.

Surface ozone (O₃) pollution is an emerging environmental abiotic stress that poses substantial risks to crop yield losses and food security worldwide, and especially in China. However, the O₃-induced detrimental effects on double-season rice have rarely been investigated at large scales and over relatively long temporal spans. In this study, we estimated the crop production reductions and associated economic losses for double-season rice across southern China during 2013–2019, using a high spatial resolution surface ozone reanalysis dataset and rice distribution maps, and county-level production data, in combination with a locally derived exposure-response function for rice. Results show that AOT40 (cumulative hourly O₃ exposure above 40 ppb) presented generally increasing trends over growing seasons in 2013–2019, spanning from 4.0 to 7.1 ppm h and 6.1 to 10.5 ppm h for double-early rice and double-late rice, respectively. Moreover, O₃-induced relative yield losses ranged from 4.0% to 6.6% for double-early rice and 6.3% to 11.1% for double-late rice. Over the seven years, ambient O₃ exposure resulted in crop production losses of 1951.5 × 10⁴ tons and economic losses of 8,081.03 million USD in total. To combat the O₃-induced agricultural risks, measures such as stringent precursors emission reductions and breeding O₃-resistant cultivars should be continuously implemented in the future. Full article

(This article belongs to the Special Issue Productivity, Sustainability and Resilience of Rice Production System)

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12 pages, 922 KiB

Open AccessArticle

Competitive Positioning of Mexican Pork in Japan

by Jaciel Ramsés Méndez-León, Dena María Jesús Camarena-Gómez and Lizbeth Salgado-Beltrán

Agriculture 2023, 13(2), 505; https://doi.org/10.3390/agriculture13020505 - 20 Feb 2023

Cited by 1 | Viewed by 1909

Abstract

Historically, Mexico has distinguished itself by its strong participation in exports to the US market; however, the pork sector’s main destination is the Asian market, particularly Japan. Hence, this document aims to show the competitive position of Mexican pork in Japan during the [...] Read more.

Historically, Mexico has distinguished itself by its strong participation in exports to the US market; however, the pork sector’s main destination is the Asian market, particularly Japan. Hence, this document aims to show the competitive position of Mexican pork in Japan during the period of 2000–2020, particularly by using Mexico, the United States, Canada, Denmark, and Chile as selected countries and considering these as the leading purveyors in the supply chain to the Japanese market. To achieve the proposed objective, a competitiveness analysis is developed through the Comparative Export Advantage methodology, strengthening it through the Constant Market Share (CMS). The results convey the growing competitiveness that Mexico is gaining in pork trade for the Japanese market, as well as globally. In addition, this research suggests that Mexican pork producers take the necessary steps toward increasing their level of competitiveness. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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26 pages, 3535 KiB

Open AccessReview

Leveraging on Advanced Remote Sensing- and Artificial Intelligence-Based Technologies to Manage Palm Oil Plantation for Current Global Scenario: A Review

by Mohammad Nishat Akhtar, Emaad Ansari, Syed Sahal Nazli Alhady and Elmi Abu Bakar

Agriculture 2023, 13(2), 504; https://doi.org/10.3390/agriculture13020504 - 20 Feb 2023

Cited by 2 | Viewed by 3763

Abstract

Advanced remote sensing technologies have undoubtedly revolutionized palm oil industry management by bringing business and environmental benefits on a single platform. It is evident from the ongoing trend that remote sensing using satellite and aerial data is able to provide precise and quick [...] Read more.

Advanced remote sensing technologies have undoubtedly revolutionized palm oil industry management by bringing business and environmental benefits on a single platform. It is evident from the ongoing trend that remote sensing using satellite and aerial data is able to provide precise and quick information for huge palm oil plantation areas using high-resolution image processing, which is also recognized by the certification agencies, i.e., the Roundtable on Sustainable Palm Oil (RSPO) and ISCC (International Sustainability and Carbon Certification). A substantial improvement in the palm oil industry could be attained by utilizing the latest Geo-information tools and technologies equipped with AI (Artificial Intelligence) algorithms and image processing, which could help to identify illegal deforestation, tree count, tree height, and the early detection of diseased leaves. This paper reviews some of the latest technologies equipped with remote sensing, AI, and image processing for managing the palm oil plantation. This manuscript also highlights how the distress in the current palm oil industry could be handled by mentioning some of the improvised monitoring systems for palm oil plantation that could in turn increase the yield of palm oil. It is evident from the proposed review that the accuracy of AI algorithms for palm oil detection depends on various factors such as the quality of the training data, the design of the neural network, and the type of detection task. In general, AI models have achieved high accuracy in detecting palm oil tree images, with some studies reporting accuracy levels up to 91%. However, it is important to note that accuracy can still be affected by factors such as variations in lighting conditions and image resolution. Nonetheless, with any AI model, the accuracy of algorithms for palm oil tree detection can be improved by collecting more diverse training data and fine-tuning the model. Full article

(This article belongs to the Special Issue Data-Driven Agricultural Innovations with Artificial Intelligence and Industrial Internet of Things (IIoT))

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22 pages, 1966 KiB

Open AccessArticle

An Application of Partial Least Squares Structural Equation Modeling (PLS-SEM) to Examining Farmers’ Behavioral Attitude and Intention towards Conservation Agriculture in Bangladesh

by Riffat Ara Zannat Tama, Md Mahmudul Hoque, Ying Liu, Mohammad Jahangir Alam and Mark Yu

Agriculture 2023, 13(2), 503; https://doi.org/10.3390/agriculture13020503 - 20 Feb 2023

Cited by 2 | Viewed by 3156

Abstract

Despite being widely advocated as a climate-smart farming system, the adoption of conservation agriculture (CA) among Bangladeshi farmers has remained surprisingly low. Evidence indicates that farmers’ behavior regarding the adoption and continuation of CA is affected by their socioeconomic and psychological factors. This [...] Read more.

Despite being widely advocated as a climate-smart farming system, the adoption of conservation agriculture (CA) among Bangladeshi farmers has remained surprisingly low. Evidence indicates that farmers’ behavior regarding the adoption and continuation of CA is affected by their socioeconomic and psychological factors. This study combined the Technology Acceptance Model (TAM) and Diffusion of Innovation (DOI) theories to examine the socio-psychological determinants of Bangladeshi farmers’ behavior regarding the adoption of CA. The proposed model included both reflective and formative measurements. Based on data collected from 201 CA farmers, this research used a variance-based structural equation modeling (PLS-SEM) approach to test the model. The analysis showed that the components of this integrated model explained more variance (Intention: 48.9%; Attitude: 59.2%) than the original TAM framework (Intention: 45.8%; Attitude: 54.5%). Farmers’ attitudes toward the continuation of CA were most influenced by the Relative Advantage (RA) of CA (β = 0.337). The low level of Complexity (β = 0.225) and Compatibility (β = 0.273) of CA had a significant positive effect on attitude. In a campaign to encourage farmers to act more sustainably, interventions should emphasize CA’s long-term benefits, such as its effects on soil, yield, and the environment. Full article

(This article belongs to the Special Issue Natural Resource and Environmental Economics in Agriculture)

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16 pages, 1449 KiB

Open AccessReview

Urban Gardening in a Changing Climate: A Review of Effects, Responses and Adaptation Capacities for Cities

by Francisco Tomatis, Monika Egerer, Adriana Correa-Guimaraes and Luis Manuel Navas-Gracia

Agriculture 2023, 13(2), 502; https://doi.org/10.3390/agriculture13020502 - 20 Feb 2023

Cited by 3 | Viewed by 8488

Abstract

Climate change is impacting the ecological, social and technological aspects of urban gardens. Gardens experience threats (e.g., water scarcity) but are also responding through adaptation strategies (e.g., selecting drought-resilient plants). A synthetic overview of how urban gardens are affected by climate change and [...] Read more.

Climate change is impacting the ecological, social and technological aspects of urban gardens. Gardens experience threats (e.g., water scarcity) but are also responding through adaptation strategies (e.g., selecting drought-resilient plants). A synthetic overview of how urban gardens are affected by climate change and responding to climate change is unclear. Here, we systematically reviewed articles and book chapters published in the last two decades (2000–2022) to illustrate the relationship between climate change and urban gardening. From 72 documents analyzed with Nvivo Software, we found that there has been an increase in academic publications. Universities from the US (14) and Germany (9) universities are the dominant producers. Evidence shows that climate change can have negative impacts on cities, people and urban food. Suggestions on how to build the adaptation capacity of urban gardens include collecting rainwater, changing plant selection, changing planting times, applying vegetative cover on the soil and other practices. For cities, community and allotment gardens are helpful for adaptation, mitigation and resilience. This includes the capacity to regulate the microclimate, to reduce urban heat island effects and to buffer urban floods, the power to capture carbon, the ability to create social networks and other socio-environmental benefits for urban climate planning. Full article

(This article belongs to the Special Issue Green and Sustainable Agricultural Ecosystem)

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10 pages, 1887 KiB

Open AccessCommunication

Regulation of bta-miRNA29d-3p on Lipid Accumulation via GPAM in Bovine Mammary Epithelial Cells

by Xin Zhao, Jun Li, Shuying Zhao, Lili Chen, Man Zhang, Yi Ma and Dawei Yao

Agriculture 2023, 13(2), 501; https://doi.org/10.3390/agriculture13020501 - 20 Feb 2023

Cited by 2 | Viewed by 1246

Abstract

MicroRNAs (miRNAs) are small RNA molecules consisting of approximately 22 nucleotides that are engaged in the regulation of various bio-processes. There is growing evidence that miR-29 is a key regulator of hepatic lipid metabolism. Mimics and inhibitors of bta-miRNA29d-3p were transiently transfected in [...] Read more.

MicroRNAs (miRNAs) are small RNA molecules consisting of approximately 22 nucleotides that are engaged in the regulation of various bio-processes. There is growing evidence that miR-29 is a key regulator of hepatic lipid metabolism. Mimics and inhibitors of bta-miRNA29d-3p were transiently transfected in bovine mammary epithelial cells (BMECs) to reveal the regulation of bta-miRNA29d-3p on lipid accumulation in BMECs. Results showed that overexpression of bta-miRNA29d-3p significantly inhibited the expression of genes related to triglyceride (TAG) synthesis, namely DGAT1 and mitochondrial glycerol-3-phosphate acyltransferase (GPAM, p < 0.01) and down-regulated TAG levels in cells (p < 0.05). The expression of fatty acid synthesis and desaturation-related genes FASN, SCD1, and ACACA, and transcription factor SREBF1 also decreased. Interference of bta-miRNA29d-3p significantly increased the expression of GPAM, DGAT1, FASN, SCD1, ACACA, and SREBF1 (p < 0.01), and significantly upregulated the concentration of TAG in cells. Furthermore, a luciferase reporter assay confirmed that GPAM is a direct target of bta-miRNA29d-3p. In summary, bta-miRNA29d-3p modulates fatty acid metabolism and TAG synthesis by regulating genes related to lipid metabolism in BMECs and targeting GPAM. Thus, bta-miRNA29d-3p plays an important role in controlling mammary lipid synthesis in cows. Full article

(This article belongs to the Special Issue Breeding, Genetics and Safety Production of Dairy Cattle)

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20 pages, 4207 KiB

Open AccessArticle

On Precision Agriculture: Enhanced Automated Fruit Disease Identification and Classification Using a New Ensemble Classification Method

by Abid Mehmood, Muneer Ahmad and Qazi Mudassar Ilyas

Agriculture 2023, 13(2), 500; https://doi.org/10.3390/agriculture13020500 - 20 Feb 2023

Cited by 4 | Viewed by 2450

Abstract

Fruits are considered among the most nutrient-dense cash crops around the globe. Since fruits come in different types, sizes, shapes, colors, and textures, the manual classification and disease identification of a large quantity of fruit is time-consuming and sluggish, requiring massive human intervention. [...] Read more.

Fruits are considered among the most nutrient-dense cash crops around the globe. Since fruits come in different types, sizes, shapes, colors, and textures, the manual classification and disease identification of a large quantity of fruit is time-consuming and sluggish, requiring massive human intervention. We propose a multilevel fusion method for fruit disease identification and fruit classification that includes intensive fruit image pre-processing, customized image kernels for feature extraction with state-of-the-art (SOTA) deep methods, Gini-index-based controlled feature selection, and a hybrid ensemble method for identification and classification. We noticed certain limitations in the existing literature of adopting a single data source, in terms of limited data sizes, variability in fruit types, variability in quality, and variability in disease type. Therefore, we extensively aggregated and pre-processed multi-fruit data to simulate our proposed ensemble model on comprehensive datasets to cover both fruit classification and disease identification aspects. The multi-fruit imagery data contained regular and augmented images of fruits including apple, apricot, avocado, banana, cherry, fig, grape, guava, kiwi, mango, orange, peach, pear, pineapple, and strawberry. Similarly, we considered normal and augmented images of rotten fruits including beans (two categories), strawberries (seven categories), and tomatoes (three categories). For consistency, we normalized the images and designed an auto-labeling mechanism based on the existing image clusters to label inconsistent data to appropriate classes. Finally, we verified the auto-labeled data with a complete inspection to correctly assign it to the relevant classes. The proposed ensemble classifier outperforms all other classification methods, achieving 100% and 99% accuracy for fruit classification and disease identification. Further, we performed the analysis of variance (ANOVA) test to validate the statistical significance of the classifiers’ outcomes at α = 0.05. We achieved F-values of 32.41 and 11.42 against F-critical values of 2.62 and 2.86, resulting in p-values of 0.00 (<0.05) for fruit classification and disease identification. Full article

(This article belongs to the Special Issue Applications of Data Analysis in Agriculture)

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14 pages, 8180 KiB

Open AccessArticle

Modelling Vineyard Spraying by Precisely Assessing the Duty Cycles of a Blast Sprayer Controlled by Pulse-Width-Modulated Nozzles

by Verónica Saiz-Rubio, Coral Ortiz, Antonio Torregrosa, Enrique Ortí, Montano Pérez, Andrés Cuenca and Francisco Rovira-Más

Agriculture 2023, 13(2), 499; https://doi.org/10.3390/agriculture13020499 - 20 Feb 2023

Cited by 2 | Viewed by 1395

Abstract

The flowrate control of spraying systems with pulse-width-modulated solenoid valves is currently being implemented for precision herbicide application in commodity crops, but solutions for fruit trees set in orchards that require higher pressures are mostly in the development stage. A reason for this [...] Read more.

The flowrate control of spraying systems with pulse-width-modulated solenoid valves is currently being implemented for precision herbicide application in commodity crops, but solutions for fruit trees set in orchards that require higher pressures are mostly in the development stage. A reason for this has been the higher flowrate and pressure requirements of blast sprayers used for dense canopies typical of high value crops. In the present study, the duty cycles preset by an operator were compared to the actual ones estimated from measuring flowrates. A new developed air-assisted orchard sprayer with shelf hollow disc-cone nozzles was studied, such that flowrates and pressures were registered by a computer for different duty cycles commanded by an operator from 10% to 100% in intervals of 10%. In addition to sensor data, visual assessment was carried out via high-speed video images. The results showed that preset duty cycles were always more than 10% lower than the actual DC estimated from measured flowrates. The effective operational range of the duty cycles went from 20% to 80%. In general, the deviations in transitional periods were higher for lower duty cycles, being difficult to determine the real reduction in flowrate during the transition periods. A correction model has been proposed to adjust the preset duty cycles to make sure that the necessary spray flowrate is released as precisely commanded by prescription maps. Further research will be needed to verify the proper implementation of the developed correction model in field applications. Full article

(This article belongs to the Section Agricultural Technology)

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13 pages, 1559 KiB

Open AccessArticle

The Classification of Peaches at Different Ripening Stages Using Machine Learning Models Based on Texture Parameters of Flesh Images

by Ewa Ropelewska and Krzysztof P. Rutkowski

Agriculture 2023, 13(2), 498; https://doi.org/10.3390/agriculture13020498 - 20 Feb 2023

Cited by 2 | Viewed by 2799

Abstract

The ripening stage can affect consumer preference and the market value of peaches. This study was aimed at developing an objective, effective, and fast procedure for distinguishing the different stages of ripeness of peaches using image texture parameters and models built using traditional [...] Read more.

The ripening stage can affect consumer preference and the market value of peaches. This study was aimed at developing an objective, effective, and fast procedure for distinguishing the different stages of ripeness of peaches using image texture parameters and models built using traditional machine learning algorithms. The ripeness classes (distinguished using DA-Meter-based nondestructive VIS/NIR method) 0.1, 0.4, and 0.9 for ‘Redhaven’ peaches and 0.1, 0.4, and 1.0 for ‘Royal Glory’ peaches were considered. Fruit weight, ethylene production, total soluble solids content (SSC), titratable acidity (TA), and fruit firmness (FF) were measured. The slice images for each class were acquired. Selected texture parameters from images in color channels R, G, B, L, a, b, X, Y, and Z were used to develop classification models for distinguishing peach ripening stages in pairs. Models were built for combined textures selected from images in all color channels, individual color spaces, and individual color channels using various machine learning algorithms. The ethylene production and SSC was higher in peaches with a ripeness class of 0.1 than in less ripe fruit. The least ripe fruit of ‘Redhaven’ and ‘Royal Glory’ peaches were characterized by the highest fruit firmness. Furthermore, statistically significant differences in SSC between classes 0.1 and 0.9 of ‘Redhaven’ were observed. For ‘Royal Glory’, statistically significant differences in TA were determined between all classes. These differences may be related to classification performance metrics. In the case of ‘Redhaven’ peaches, two extreme ripeness classes 0.1 (the greatest ripeness) and 0.9 (the least ripeness) were correctly classified with the highest accuracy reaching 100% for models built based on textures selected from all color channels (random forest and Bayes net algorithms) and color space lab (random forest). For individual color channels, the accuracy reached 99% for color channel G (random forest) and color channel a (logistic). The accuracy of classifying ripening stages 0.1 and 0.4 reached 98% for the model built using textures from all color channels and color space lab (Bayes net). The ripening stages 0.4 and 0.9 were distinguished with an accuracy of up to 96% (all color channels, random forest). The classification of ripening stages of ‘Royal Glory’ peaches reached 100% for all pairs, 0.1 vs. 1.0 (all color channels, color spaces RGB, color space lab, color channel G, color channel a), 0.1 vs. 0.4 (all color channels, color space RGB, color space lab), and 0.4 vs. 1.0 (all color channels). The developed procedure can be useful in practice. Distinguishing peaches at different stages of ripeness and the selection of fruit at the optimal stage can be important for consumption and processing. Full article

(This article belongs to the Special Issue Application of Spectroscopy and Sensor Technology in Agricultural Products)

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18 pages, 2163 KiB

Open AccessArticle

Impact of African Swine Fever Epidemic on the Cost Intensity of Pork Production in China

by Zhaohui Yan, Mingli Wang, Xujun Li and Hui Jiang

Agriculture 2023, 13(2), 497; https://doi.org/10.3390/agriculture13020497 - 20 Feb 2023

Cited by 1 | Viewed by 3416

Abstract

China’s African swine fever (ASF) outbreak, which started in 2018, has had a huge and far-reaching impact on China’s hog industry, and it has not been completely eliminated so far. This article analyzes the impact of the ASF epidemic on the costs and [...] Read more.

China’s African swine fever (ASF) outbreak, which started in 2018, has had a huge and far-reaching impact on China’s hog industry, and it has not been completely eliminated so far. This article analyzes the impact of the ASF epidemic on the costs and technical efficiency of hog production in China based on data from the China Agricultural Product Cost–Benefit Compilation (2012–2021) using a stochastic frontier trans-log production function model. The results show that, after the outbreak of the ASF epidemic in China, feed costs, medical and epidemic prevention costs, and other costs of hog production in China increased significantly; the technical efficiency of China’s hog production decreased significantly; large-scale hog farms were the most responsive to and greatly affected by the ASF epidemic; and there are regional differences in the impact of the ASF epidemic on technical efficiency of hog production. Future policies should focus on strengthening the R&D investment and technology promotion capacity of hog production, developing moderate-scale farming, and enhancing regional cooperation to improve technical efficiency of hog production. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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19 pages, 7689 KiB

Open AccessArticle

Non-Destructive Detection of Chicken Freshness Based on Electronic Nose Technology and Transfer Learning

by Yunwei Xiong, Yuhua Li, Chenyang Wang, Hanqing Shi, Sunyuan Wang, Cheng Yong, Yan Gong, Wentian Zhang and Xiuguo Zou

Agriculture 2023, 13(2), 496; https://doi.org/10.3390/agriculture13020496 - 20 Feb 2023

Cited by 8 | Viewed by 2202

Abstract

As a non-destructive detection method, an electronic nose can be used to assess the freshness of meats by collecting and analyzing their odor information. Deep learning can automatically extract features and uncover potential patterns in data, minimizing the influence of subjective factors such [...] Read more.

As a non-destructive detection method, an electronic nose can be used to assess the freshness of meats by collecting and analyzing their odor information. Deep learning can automatically extract features and uncover potential patterns in data, minimizing the influence of subjective factors such as selecting features artificially. A transfer-learning-based model was proposed for the electronic nose to detect the freshness of chicken breasts in this study. First, a 3D-printed electronic nose system is used to collect the odor data from chicken breast samples stored at 4 °C for 1–7 d. Then, three conversion to images methods are used to feed the recorded time series data into the convolutional neural network. Finally, the pre-trained AlexNet, GoogLeNet, and ResNet models are retrained in the last three layers while being compared to classic machine learning methods such as K Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machines (SVM). The final accuracy of ResNet is 99.70%, which is higher than the 94.33% correct rate of the popular machine learning model SVM. Therefore, the electronic nose combined with conversion to images shows great potential for using deep transfer learning methods for chicken freshness classification. Full article

(This article belongs to the Section Digital Agriculture)

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19 pages, 4599 KiB

Open AccessArticle

Variation in Fruit and Seed Morphology of Selected Biotypes and Cultivars of Elaeagnus multiflora Thunb. in North-Eastern Europe

by Anna Bieniek, Arkadiusz Bieniek and Natalia Bielska

Agriculture 2023, 13(2), 495; https://doi.org/10.3390/agriculture13020495 - 19 Feb 2023

Cited by 1 | Viewed by 1852

Abstract

Elaeagnus multiflora Thunb., also known as “cherry silverberry”, “cherry elaeagnus”, and “goumi” has been used for a long time in traditional Chinese medicine as a phytosterol-rich plant. Today, the fruits of this species are also becoming more popular as a “superfood” in Europe, [...] Read more.

Elaeagnus multiflora Thunb., also known as “cherry silverberry”, “cherry elaeagnus”, and “goumi” has been used for a long time in traditional Chinese medicine as a phytosterol-rich plant. Today, the fruits of this species are also becoming more popular as a “superfood” in Europe, but the cultivation of these plants is not yet carried out on a large commercial scale. The aim of this study was to evaluate the yield and morphological quality of the fruit of nine E. multiflora biotypes and two cultivars, ‘Jahidka’ and ‘Sweet Scarlet’, to determine their suitability for cultivation in the climatic conditions of Poland. The lowest yields (an average of 0.49 kg per bush) were recorded in 2021. In this year, the fruits of the biotypes and cultivars were distinguished by the highest mean fruit weight, fruit-to-seed weight ratio, and total soluble solids content. Our research shows that due to the greatest weight of fruits, cultivar ‘Jahidka’ and the biotype B11 can be recommended for cultivation in north-eastern Poland. Biotype B11 was distinguished by the highest yield (an average of 4.02 kg per bush). The smallest share of stone in relation to the weight of the fruit was shown for the cultivars ‘Jahidka’, and biotype B4. Full article

(This article belongs to the Special Issue The Impact of Environmental Factors on Fruit Quality)

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20 pages, 2186 KiB

Open AccessArticle

Assessment of Earthworm Services on Litter Mineralisation and Nutrient Release in Annual and Perennial Energy Crops (Zea mays vs. Silphium perfoliatum)

by Lena Wöhl, Thorsten Ruf, Christoph Emmerling, Jan Thiele and Stefan Schrader

Agriculture 2023, 13(2), 494; https://doi.org/10.3390/agriculture13020494 - 19 Feb 2023

Cited by 2 | Viewed by 1485

Abstract

Abundant and functionally diverse earthworm communities in perennials deliver ecosystem services like increasing nutrient availability by incorporating organic matter. This study aimed to analyse the decomposition of annual and perennial energy crop residues, and the subsequent nutrient release, depending on earthworm functional diversity. [...] Read more.

Abundant and functionally diverse earthworm communities in perennials deliver ecosystem services like increasing nutrient availability by incorporating organic matter. This study aimed to analyse the decomposition of annual and perennial energy crop residues, and the subsequent nutrient release, depending on earthworm functional diversity. In a laboratory experiment, two ecological earthworm groups—anecics (detritivorous Lumbricus terrestris (L.)) and endogeics (geophagous Aporrectodea caliginosa and A. rosea)—were incubated with wilted cup plant (Silphium perfoliatum) and maize (Zea mays) litter for 4 or 8 weeks. Decomposition and consumption rates were calculated. The C, N and P in litter and casts were analysed. Mineralisation was a function of earthworm biomass and the number of individuals. Functional diversity had no beneficial effect. Decomposition was found to be highest in treatments with detritivorous earthworms, i.e., higher earthworm biomass, yet consumption and nutrient turnover in relation to earthworm biomass were higher in treatments with geophages indicating enhanced competition. N limitation became apparent in both litter treatments and was predominant with cup plant litter. N limitation and recalcitrant cell wall compounds affected consumption rates and the egestion of total C and P. While N in casts was lower than expected, P was increased. We observed that the effects manifested at different stages of decomposition of maize and cup plant, highlighting differences in temporal development of decomposition and nutrient turnover between litter types. Our results indicate that earthworms promote decomposition of recalcitrant litter and nutrient turnover, but N limitation may hamper nutrient release. Cup plant systems offer a suitable habitat for soil-dwelling organisms, but management approaches must consider the adequate input of organic matter as an energy and nutrient source to enhance ecosystem service provision. Full article

(This article belongs to the Special Issue Soil Conservation and Plant Nutrition in Sustainable Agriculture)

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21 pages, 5130 KiB

Open AccessArticle

Engineering Design, Kinematic and Dynamic Analysis of High Lugs Rigid Driving Wheel, a Traction Device for Conventional Agricultural Wheeled Tractors

by Hafiz Md-Tahir, Jumin Zhang, Yong Zhou, Muhammad Sultan, Fiaz Ahmad, Jun Du, Amman Ullah, Zawar Hussain and Junfang Xia

Agriculture 2023, 13(2), 493; https://doi.org/10.3390/agriculture13020493 - 19 Feb 2023

Cited by 1 | Viewed by 2461

Abstract

Traction failure on loose terrain is common in conventional agricultural wheeled tractors due to poor traction ability and lower power transfer efficiency of drive wheels, which leads to excessive energy consumption and soil compaction in agriculture. To overcome the problem, this paper presents [...] Read more.

Traction failure on loose terrain is common in conventional agricultural wheeled tractors due to poor traction ability and lower power transfer efficiency of drive wheels, which leads to excessive energy consumption and soil compaction in agriculture. To overcome the problem, this paper presents a new design of a rigid lugged wheel for use in field tillage operations. This wheel was designed according to field operational requirements and also provided with rubber pads for smooth on-road drives. Kinematic and dynamic analysis of new wheel designs were carried out to study how they move, how they interact with the soil, and how they generate drive force in loose terrain soil. The relationship of wheel lug motion trajectories, displacement, and velocity of the wheel relative to field conditions, different travel reduction rates, and lug penetration/wheel sinkage were analyzed. Wheel-terrain interaction and shear stress-shear displacement relationships when the wheel is driven in soft, deformable terrain were studied using classic soil mechanics principles. It is found that the component of thrust in the direction of driving, i.e., driving force, is ranged between 81.52% and 86.17%, while the vertical component is reported to be less than 30% and further decreases to 9%, which is the compaction avoiding factor. The relationships, thus developed, of wheel parameters, soil stress and thrust characteristics, and wheel drive force were derived and revealed that the traction performance, power transfer efficiency, and trafficability of tractors in loose terrain can be improved by using the newly proposed wheel. A finite element method was used to analyze the designed wheel model for structural stability and optimization. The theoretical analysis results of the new drive wheel are convincing, so further tests and field operation research are recommended for sustainable adoption. Full article

(This article belongs to the Topic Emerging Agricultural Engineering Sciences, Technologies, and Applications)

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11 pages, 2421 KiB

Open AccessArticle

Do Glycogen Content and Thermal Preference in Worker Bees Vary Depending on Geographical Origin? A Comparison of Carniolan Honeybees, Central European Honeybees and Caucasian Honeybees

by Przemysław Grodzicki, Joanna Bacia, Katarzyna Piątkowska and Bartosz Piechowicz

Agriculture 2023, 13(2), 492; https://doi.org/10.3390/agriculture13020492 - 19 Feb 2023

Cited by 1 | Viewed by 1238

Abstract

Among the honeybee subspecies, Polish beekeepers most commonly rear three of them, i.e., Apis mellifera carnica, A. m. mellifera and A. m. caucasica. They differ in morphological and physiological features. Our goal was to find a linkage between their thermal behaviour [...] Read more.

Among the honeybee subspecies, Polish beekeepers most commonly rear three of them, i.e., Apis mellifera carnica, A. m. mellifera and A. m. caucasica. They differ in morphological and physiological features. Our goal was to find a linkage between their thermal behaviour and body glycogen content that could be decisive for their wintering perspective. We compared the temperature preference and body glycogen concentration in six honeybee groups of three subspecies obtained from hives in two seasons, on 12 May 2021 (summer bees) and on 20 September 2020 (autumn bees preparing for wintering). In the Carniolan and Central European honeybees, the glycogen content in worker bodies was higher in autumn bees preparing for wintering than in summer bees. The Caucasian honeybee deviated from this pattern. The choice of ambient temperature by a given subspecies depended neither on the season nor the geographical race. Full article

(This article belongs to the Special Issue The Pollinators in Agricultural Ecosystems)

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17 pages, 1179 KiB

Open AccessArticle

Effect of Traditional Spices on the Quality and Antioxidant Potential of Paneer Prepared from Buffalo Milk

by Tahir Mahmood Qureshi, Muhammad Nadeem, Javeria Iftikhar, Salim-ur-Rehman, Sobhy M. Ibrahim, Faizan Majeed and Muhammad Sultan

Agriculture 2023, 13(2), 491; https://doi.org/10.3390/agriculture13020491 - 19 Feb 2023

Cited by 2 | Viewed by 1935

Abstract

This study aims to evaluate the effect of different spices (black pepper, cumin, clove, nigella, cardamom, and cinnamon) on the physicochemical characteristics and microbial quality, as well as antioxidant potential, of paneer during storage. Different types of spices were incorporated into the paneer [...] Read more.

This study aims to evaluate the effect of different spices (black pepper, cumin, clove, nigella, cardamom, and cinnamon) on the physicochemical characteristics and microbial quality, as well as antioxidant potential, of paneer during storage. Different types of spices were incorporated into the paneer at different levels (0.2 and 0.3%). In addition to paneer, the antioxidant potential of spices was also investigated. The results concerning total plate counts (TPC) or yeast and molds (Y & M) (log₁₀ CFU/g) of all treatments were substantially (p < 0.05) increased during storage. Generally, all freshly prepared spicy paneer and control had higher sensory scores for all the sensory characteristics which declined during subsequent storage. All the paneer samples having 0.3% spices showed very slight variations (nonsignificant) in sensory score of all the attributes of their relative samples containing 0.2% spice. The incorporation of spices into the paneer matrix also showed promising results concerning all the above-mentioned attributes revealing antioxidant potential. There was significant (p < 0.05) effect of treatments and storage days on antioxidant potential of paneer. The freshly prepared control paneer (P₀) showed the lowest total phenol (TP), total flavonoids (TF), 2, 2-diphenyl-1-picrylhydrazyl (DPPH), reducing power (RP), and total antioxidant capacity (TAC) values compared to all the spicy paneer (treatments). The freshly prepared control paneer (P₀) showed the lowest antioxidant potential compared to all the spicy paneer (treatments). The maximum antioxidant potential was observed in the paneer having 0.3% clove (P₆). All the spicy paneer showed increasing trend of all the attributes, showing antioxidant potential up to 6 days of storage, but afterwards, the activities were slightly decreased. It may be concluded that spicy paneer would be considered as a functional dairy product with enhanced sensory and antioxidant properties, and shelf stability. Full article

(This article belongs to the Special Issue Advances in Agricultural Engineering Technologies and Application)

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17 pages, 12864 KiB

Open AccessArticle

Automatic Equipment to Increase Sustainability in Agricultural Fertilization

by Mario Martínez García, Silvia Ramos Cabral, Ricardo Pérez Zúñiga and Luis Carlos G. Martínez Rodríguez

Agriculture 2023, 13(2), 490; https://doi.org/10.3390/agriculture13020490 - 19 Feb 2023

Cited by 1 | Viewed by 2131

Abstract

The purpose of the study was to design a device for the dissolution of fertilizers for agricultural use in an automatic and environmentally sustainable way to facilitate the work of farmers. To achieve this goal, an outdated blade design was used, which generates [...] Read more.

The purpose of the study was to design a device for the dissolution of fertilizers for agricultural use in an automatic and environmentally sustainable way to facilitate the work of farmers. To achieve this goal, an outdated blade design was used, which generates turbulent and laminar flows thanks to the angle of inclination of its blades. In tests, the combination of these two flows gave a better result compared to laminar and turbulent flows separately. The best results were achieved by varying the spin and speed, the time between spins, and the rest time. The time it would take to dissolve the mixture was drastically reduced if it were conducted in the traditional way (manually) or compared with commercial mixers. In conclusion, the technique used for the dissolution of agricultural minerals is more effective and reduces time, energy, and effort. This was able to reduce the time necessary to dissolve the fertilizer by 93 percent compared to doing it manually and by 66 percent compared to using commercial mixers, in a solution of 100 L of water per 100 kg of ammonium sulfate. Full article

(This article belongs to the Topic Innovation and Solution for Sustainable Agriculture)

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21 pages, 3448 KiB

Open AccessArticle

Behavioral Analysis of Mowing Workers Based on Hilbert–Huang Transform: An Auxiliary Movement Analysis of Manual Mowing on the Slopes of Terraced Rice Fields

by Bo Wu, Yuan Wu, Ran Dong, Kiminori Sato, Soichiro Ikuno, Shoji Nishimura and Qun Jin

Agriculture 2023, 13(2), 489; https://doi.org/10.3390/agriculture13020489 - 18 Feb 2023

Cited by 4 | Viewed by 1304

Abstract

In the mountainous areas of Japan, the weeds on the slopes of terraced rice paddies still need to be cut by the elderly manually. Therefore, more attention should be given to maintain proper postures while performing mowing actions (especially the pre-cutting actions) to [...] Read more.

In the mountainous areas of Japan, the weeds on the slopes of terraced rice paddies still need to be cut by the elderly manually. Therefore, more attention should be given to maintain proper postures while performing mowing actions (especially the pre-cutting actions) to reduce the risk of accidents. Given that complex mowing actions can be decomposed into different sub-actions, we proposed a joint angular calculation-based body movement analysis model based on the Hilbert–Huang transform to analyze the pre-cutting actions. We found that the two most important sub-actions were fast pre-cutting and slow pre-cutting. Based on field experiments, we analyzed the pre-cutting actions of workers with different experience levels and identified the factors that affected their falling risk (stability). The results showed differences and similarities in the actions’ frequency and amplitude in the sub-actions of workers with different mowing experience, confirmed the influence of body characteristics (body height, etc.) on body stability, and showed that workers should pay attention to their age and ankle part while mowing. The analysis results have identified factors for the mowing workers’ training and the development of equipment for use in complicated geographical conditions. Full article

(This article belongs to the Section Agricultural Technology)

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22 pages, 3976 KiB

Open AccessArticle

Duguetia lanceolata A. St.-Hil. (Annonaceae) Essential Oil: Toxicity against Spodoptera frugiperda (J. E. Smith) (Lepidoptera: Noctuidae) and Selectivity for the Parasitoid Trichogramma pretiosum Riley (Hymenoptera: Trichogrammatidae)

by Mayara Ketllyn de Paula Rosetti, Dejane Santos Alves, Isabela Caroline Luft, Katiane Pompermayer, Andressa Soares Scolari, Gabriela Trindade de Souza e Silva, Murilo Silva de Oliveira, Javier Andrés García Vanegas, Horácio Bambo Pacule, Geraldo Humberto Silva, Denilson Ferreira de Oliveira and Geraldo Andrade Carvalho

Agriculture 2023, 13(2), 488; https://doi.org/10.3390/agriculture13020488 - 18 Feb 2023

Viewed by 1595

Abstract

The fall armyworm (FAW) Spodoptera frugiperda is a polyphagous pest that is difficult to control due to populations resistant to various active ingredients. Thus, the objective of this study was to evaluate the toxicity of essential oils (EOs) from the organs of Annona [...] Read more.

The fall armyworm (FAW) Spodoptera frugiperda is a polyphagous pest that is difficult to control due to populations resistant to various active ingredients. Thus, the objective of this study was to evaluate the toxicity of essential oils (EOs) from the organs of Annona neolaurifolia, Duguetia lanceolata, and Xylopia brasiliensis, against the FAW and its natural enemy, Trichogramma pretiosum. The most active EOs were those from the leaves and stem bark of D. lanceolata, which presented LD₉₀ to S. frugiperda equal to 70.76 and 127.14 µg of EO/larvae, respectively. The major compounds in the EO of D. lanceolata (leaves) were β-caryophyllene and caryophyllene oxide. Although individually inactive against the FAW, when combined, those compounds reduced the insect’s probability of survival. However, the mortality was lower than that caused by EO. This result suggests that other components of EO contribute to the activity against FAW. Furthermore, the EO of the leaves from D. lanceolata presented low toxicity to the egg-larva stage of T. pretiosum, but was toxic to other phases. Thus, EO from D. lanceolata is potentially useful for developing new products to control S. frugiperda. Full article

(This article belongs to the Special Issue Recent Advances in Plant Extracts and Essential Oils as Potential Alternative Biocontrol Products)

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14 pages, 1371 KiB

Open AccessArticle

Use of Gas Chromatography and SPME Extraction for the Differentiation between Healthy and Paenibacillus larvae Infected Colonies of Bee Brood—Preliminary Research

by Bartosz Piechowicz, Aleksandra Kwiatek, Stanisław Sadło, Lech Zaręba, Anna Koziorowska, Daniela Kloc and Maciej Balawejder

Agriculture 2023, 13(2), 487; https://doi.org/10.3390/agriculture13020487 - 18 Feb 2023

Cited by 1 | Viewed by 1586

Abstract

Paenibacillus larvae is a deadly pathogen for bee brood, which can lead to the death of entire colonies. The presence of specific volatile organic compounds (VOCs) in the hive may be related to the occurrence of this bacterium in brood. Compositions of those [...] Read more.

Paenibacillus larvae is a deadly pathogen for bee brood, which can lead to the death of entire colonies. The presence of specific volatile organic compounds (VOCs) in the hive may be related to the occurrence of this bacterium in brood. Compositions of those volatile fractions present in healthy brood from control colonies and the brood without symptoms of infection collected from the colonies infected by P. larvae were compared using gas chromatography coupled with mass spectrometry (GC-MS) and solid phase microextraction (SPME). Among the seven compounds detected and quantified, the relative concentrations of 3-carene and limonene significantly differentiated the brood from healthy and infected colonies. Based on the ratio analysis, the samples were differentiated in terms of the number of emitted VOCs. Full article

(This article belongs to the Special Issue The Pollinators in Agricultural Ecosystems)

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19 pages, 6045 KiB

Open AccessArticle

Extraction of Cropland Spatial Distribution Information Using Multi-Seasonal Fractal Features: A Case Study of Black Soil in Lishu County, China

by Qi Wang, Peng Guo, Shiwei Dong, Yu Liu, Yuchun Pan and Cunjun Li

Agriculture 2023, 13(2), 486; https://doi.org/10.3390/agriculture13020486 - 18 Feb 2023

Cited by 3 | Viewed by 1324

Abstract

Accurate extraction of cropland distribution information using remote sensing technology is a key step in the monitoring, protection, and sustainable development of black soil. To obtain precise spatial distribution of cropland, an information extraction method is developed based on a fractal algorithm integrating [...] Read more.

Accurate extraction of cropland distribution information using remote sensing technology is a key step in the monitoring, protection, and sustainable development of black soil. To obtain precise spatial distribution of cropland, an information extraction method is developed based on a fractal algorithm integrating temporal and spatial features. The method extracts multi-seasonal fractal features from the Landsat 8 OLI remote sensing data. Its efficiency is demonstrated using black soil in Lishu County, Northeast China. First, each pixel’s upper and lower fractal signals are calculated using a blanket covering method based on the Landsat 8 OLI remote sensing data in the spring, summer, and autumn seasons. The fractal characteristics of the cropland and other land-cover types are analyzed and compared. Second, the ninth lower fractal scale is selected as the feature scale to extract the spatial distribution of cropland in Lishu County. The cropland vector data, the European Space Agency (ESA) WorldCover data, and the statistical yearbook from the same period are used to assess accuracy. Finally, a comparative analysis of this study and existing products at different scales is carried out, and the point matching degree and area matching degree are evaluated. The results show that the point matching degree and the area matching degree of cropland extraction using the multi-seasonal fractal features are 90.66% and 96.21%, and 95.33% and 83.52%, respectively, which are highly consistent with the statistical data provided by the local government. The extracted accuracy of cropland is much better than that of existing products at different scales due to the contribution of the multi-seasonal fractal features. This method can be used to accurately extract cropland information to monitor changes in black soil, and it can be used to support the conservation and development of black soil in China. Full article

(This article belongs to the Special Issue Novel Applications of Optical Sensors and Machine Learning in Agricultural Monitoring)

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18 pages, 610 KiB

Open AccessArticle

How Agricultural Farmers Respond to Risks during the COVID-19 Pandemic: An Exploration through the Dual Social Capitals Approach

by Mingsong Hao, Chuntian Lu, Xi Zhou and Jing Xu

Agriculture 2023, 13(2), 485; https://doi.org/10.3390/agriculture13020485 - 17 Feb 2023

Cited by 2 | Viewed by 2089

Abstract

The degree of risk to which agricultural farmers are exposed during the COVID-19 pandemic and how they tackle those difficulties is a critical topic. Although the topic has been paid considerable attention by worldwide scholars, this study intends to compensate for it via [...] Read more.

The degree of risk to which agricultural farmers are exposed during the COVID-19 pandemic and how they tackle those difficulties is a critical topic. Although the topic has been paid considerable attention by worldwide scholars, this study intends to compensate for it via conducting a ground-breaking analysis based on sample survey data. Integrating theoretical perspectives of individual- and collective-level social capitals rooted in sociology, and using NPRM (Nested Poisson Regression Model) to analyze a sample survey data collected in rural China in August 2020, we generated the following findings. (1) The overall risks and damages to agricultural production and management are relatively minimal. Thus, farmers are highly confident in conquering the pandemic and recovering their business. (2) Compared with micro- and macro-level influencing factors, social capital at both levels could greatly help agricultural farmers obtain informal and formal supporting resources (such as encouragement and financial supports), thus helping them to cope with the pandemic shock. (3) Specifically, the acquisition of informal supporting resources is mainly affected by the size of farmers’ ordinary networks (Spring Festival Visiting Network) and the frequency of public activities held in a village; gaining access to formal supporting resources is also influenced by the frequency of public activities, but the state of farmers’ personal connections with official departments plays a crucial role in determining the amount of such resources can be obtained. According to these empirical findings, suggestions on how to suppress the negative effects and lift the positive effects of dual social capitals in the process of responding to risks are proposed. Full article

(This article belongs to the Section Agricultural Economics, Policies and Rural Management)

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15 pages, 2042 KiB

Open AccessArticle

Temporal and Spatial Variations in Soil Elemental Stoichiometry Coupled with Alterations in Agricultural Land Use Types in the Taihu Lake Basin

by Chonggang Liu, Jiangye Li, Wei Sun, Yan Gao, Zhuyun Yu, Yue Dong and Pingxing Li

Agriculture 2023, 13(2), 484; https://doi.org/10.3390/agriculture13020484 - 17 Feb 2023

Cited by 1 | Viewed by 1177

Abstract

Soil elemental stoichiometry, expressed as the ratios of carbon (C), nitrogen (N), and phosphorus (P), regulates the biogeochemical processes of elements in terrestrial ecosystems. Generally, the soil C:N:P stoichiometry characteristics of agricultural ecosystems may be different from those of natural ecosystems, with distinct [...] Read more.

Soil elemental stoichiometry, expressed as the ratios of carbon (C), nitrogen (N), and phosphorus (P), regulates the biogeochemical processes of elements in terrestrial ecosystems. Generally, the soil C:N:P stoichiometry characteristics of agricultural ecosystems may be different from those of natural ecosystems, with distinct temporal and spatial variations along with the alterations of agricultural land use types (LUTs). The balance of soil C, N, and P reflected by their stoichiometry is primarily important to microbial activity and sustainable agricultural development. However, information on soil stoichiometric changes after long-term alterations in land use is still lacking. We characterized the temporal and spatial changes in soil elemental stoichiometry coupled with alterations in agricultural LUTs in the Taihu Lake basin. By using the ArcGIS method and meta-data analysis, our results showed that the C:N, C:P, and N:P ratios of agricultural soil in the Taihu Lake basin were much lower than the well-constrained values based on samples from forest, shrubland, and grassland at a global scale. Generally, these elemental ratios in soils increased from the 1980s to the 2000s, after experiencing changes from agricultural to other land use. The soil C:N:P stoichiometry may have maintained the increasing trend according to the meta-data analysis from the 341 peer-reviewed publications since 2010. Nevertheless, different regions showed inconsistent change patterns, with the Tianmu Mountain area surrounding the downstream of the Taihu Lake basin experiencing a reduction in those ratios. The changes in LUTs and their corresponding management practices were the major drivers shaping the spatial and temporal distributions of soil C:N, C:P, and N:P. Paddy soil generally achieved higher C sequestration potential due to more straw input and a more rapid transfer of straw C into soil C in the upstream of the Taihu Lake basin than other land use types. These results provide valuable information for the agricultural system of intensive cultivation on how their soil elemental stoichiometry characteristics vary temporally and spatially due to the alteration of agricultural land use types. Full article

(This article belongs to the Special Issue Soil Carbon and Microbial Processes in Agriculture Ecosystem)

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11 pages, 3462 KiB

Open AccessArticle

Stimulation of Early Post-Emergence Growth of Alopecurus myosuroides and Apera spica-venti Following Spray Application of ACCase Inhibitors

by Mariola Wrochna, Marta Stankiewicz-Kosyl and Marzena Wińska-Krysiak

Agriculture 2023, 13(2), 483; https://doi.org/10.3390/agriculture13020483 - 17 Feb 2023

Cited by 1 | Viewed by 1175

Abstract

Resistance of blackgrass (Alopecurus myosuroides Huds.) and silky bentgrass (Apera spica-venti (L.) P. Beauv.) to ACCase inhibitors is a serious issue in winter cereals throughout Europe, especially as hormesis induced by herbicides has been observed in some populations. According to the [...] Read more.

Resistance of blackgrass (Alopecurus myosuroides Huds.) and silky bentgrass (Apera spica-venti (L.) P. Beauv.) to ACCase inhibitors is a serious issue in winter cereals throughout Europe, especially as hormesis induced by herbicides has been observed in some populations. According to the literature, growth-stimulating herbicide rates are on the rise. The aim of this study was to assess the responses of A. myosuroides and A. spica-venti, which are potentially resistant to ACCase inhibitors, to fenoxaprop-P-ethyl and pinoxaden applied at rates up to 8 times greater than their registered rates. The reaction of A. myosuroides to fenoxaprop-P-ethyl and pinoxaden resulted in an increase in biomass gain in six and four populations, respectively. In one population of A. myosuroides, this increase was statistically significant (46.4% and 55.3%). All three potentially resistant A. spica-venti populations tested were at least partially stimulated by fenoxaprop-P-ethyl, while pinoxaden only stimulated the APSII population (significant increase of 43.8%). Predictions of the possible impact of herbicides on the reproductive potential of the tested populations allow genotypes to be identified whose reproduction may be stimulated by the herbicides. The results of this study indicate that the tested populations can induce mechanisms that reduce the negative impact of the applied herbicides, with some populations demonstrating the effect of stimulating the accumulation of biomass in the treated plants. Full article

(This article belongs to the Special Issue Management of Weeds and Herbicide Resistance)

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15 pages, 2931 KiB

Open AccessArticle

Identification and Registration of the Novel High-Rhizome-Yielding Variety Bharamputra-1 of Kaempferia galanga L.

by Mohan Lal, Sunita Munda, Twahira Begum and Sudin Kumar Pandey

Agriculture 2023, 13(2), 482; https://doi.org/10.3390/agriculture13020482 - 17 Feb 2023

Cited by 2 | Viewed by 1787

Abstract

Kaempferia galanga is an endangered plant whose recognition as a flavoring agent and perfumery ingredient has increased its demand greatly. Therefore, the present investigation aimed at the identification of high-rhizome-yielding varieties of K. galanga. A total of forty-nine germplasms were collected from different [...] Read more.

Kaempferia galanga is an endangered plant whose recognition as a flavoring agent and perfumery ingredient has increased its demand greatly. Therefore, the present investigation aimed at the identification of high-rhizome-yielding varieties of K. galanga. A total of forty-nine germplasms were collected from different parts of India and planted at CSIR-NEIST, Jorhat experimental farm, during 2013. The two-year evaluation of essential morphological and chemical data was recorded for the selection of superior rhizomes with a high rhizome yield during 2014 and 2015. Subsequently, multi-location field trials were conducted with the selected elite germplasm along with controls using a randomized complete block design, and relevant morphological traits as well as essential oil quality data were recorded for all the lines for three consecutive years during 2016, 2017 and 2018. The essential oil quality was analyzed by using GC/MS. The data obtained were statistically analyzed for stability based on rhizome yield, essential oil yield and days to maturity. A high-rhizome-yielding variety of K. galanga was identified and named Bharamputra-1.Itwas found to be stable in multi-locational trials conducted in Northeast India. The variety showed a mean rhizome yield of 10.01 tones/ha. Stability parameters, namely, βi = 1.13 and σ²di = −0.07 were recorded and found to be superior to those of the other examined varieties. The chemical profiling of the rhizome essential oil of the selected germplasm was also performed using GC/MS, which revealed ethyl p-methoxycinnamate (37.25%), trans-ethyl cinnamate (28.35%), endo-borneol (8.91%), eucalyptol (6.83%), (-)-camphor (3.98%) and 3-carene (3.77%) as the main components. The cultivation of this identified variety could help in the successful commercial cultivation of the crop. Full article

(This article belongs to the Special Issue Advances in Agricultural Techniques of Medicinal and Aromatic Plants)

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13 pages, 3887 KiB

Open AccessCommunication

Evaluation of Abnormal Hypocotyl Growth of Mutant Capsicum annuum Plants

by Bánk Pápai, Zsófia Kovács, Kitti Andrea Tóth-Lencsés, Janka Bedő, Gábor Csilléry, Anikó Veres and Antal Szőke

Agriculture 2023, 13(2), 481; https://doi.org/10.3390/agriculture13020481 - 17 Feb 2023

Cited by 1 | Viewed by 1348

Abstract

Horticulture is a dynamically evolving and an ever-changing sector which needs new ideas, plant materials, and cultivating methods to produce more. Involving different mutants in breeding lines may lead to new opportunities to create new cultivating methods. pcx (procumbent plant) and tti (tortuosa [...] Read more.

Horticulture is a dynamically evolving and an ever-changing sector which needs new ideas, plant materials, and cultivating methods to produce more. Involving different mutants in breeding lines may lead to new opportunities to create new cultivating methods. pcx (procumbent plant) and tti (tortuosa internodi) Capsicum annuum mutant plants, which present abnormal stem growth, were investigated in various in vitro experiments. The pcx breeding line presents highly diverse hypocotyl growth even in the early phenophase, such as normally growing plants and the ‘laying’ habit. On the other hand, tti plants only present their elongated slender stem trait in a more mature phase. In our experiment of reorientation, we used one-sided illumination, where each of the phenotypes sensed and reacted to light, and only the pcx plants exhibited a negative gravitropic response. It was also the result that the tti plants sensed gravity, but the weak structure of the hypocotyls made them incapable of following its direction. Since the pcx plants were the only ones with an ‘antigravitropic’ growth, we used them to evaluate the time course they needed to adapt and follow the gravity vector after reorientation. The pcx plants sensing gravity adapted similarly to controls and started bending after 120 min, but those which presented as ‘anti-gravitropic’ did not respond even after 420 min. Full article

(This article belongs to the Special Issue Crop Seed Dormancy, Germination and Vigour Analysis and Seed Proteomics)

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Agriculture, Volume 13, Issue 2 (February 2023) – 285 articles

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