Agriculture

21 pages, 2594 KiB

Open AccessEditor’s ChoiceReview

A Review on Hydroponics and the Technologies Associated for Medium- and Small-Scale Operations

by Roberto S. Velazquez-Gonzalez, Adrian L. Garcia-Garcia, Elsa Ventura-Zapata, Jose Dolores Oscar Barceinas-Sanchez and Julio C. Sosa-Savedra

Agriculture 2022, 12(5), 646; https://doi.org/10.3390/agriculture12050646 - 29 Apr 2022

Cited by 69 | Viewed by 52656

Abstract

According to the Food and Agriculture Organization of the United Nations, the world population will reach nine billion people in 2050, of which 75% will live in urban settlements. One of the biggest challenges will be meeting the demand for food, as farmland [...] Read more.

According to the Food and Agriculture Organization of the United Nations, the world population will reach nine billion people in 2050, of which 75% will live in urban settlements. One of the biggest challenges will be meeting the demand for food, as farmland is being lost to climate change, water scarcity, soil pollution, among other factors. In this context, hydroponics, an agricultural method that dispenses with soil, provides a viable alternative to address this problem. Although hydroponics has proven its effectiveness on a large scale, there are still challenges in implementing this technique on a small scale, specifically in urban and suburban settings. Also, in rural communities, where the availability of suitable technologies is scarce. Paradigms such as the Internet of Things and Industry 4.0, promote Precision Agriculture on a small scale, allowing the control of variables such as pH, electrical conductivity, temperature, among others, resulting in higher production and resource savings. Full article

(This article belongs to the Topic Grand Challenges of Advanced Technologies in Sustainable Agriculture 4.0: Future Farming, Harvesting and Preservation)

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13 pages, 1289 KiB

Open AccessEditor’s ChoiceArticle

Comparison of Yield and Yield Components of Several Crops Grown under Agro-Photovoltaic System in Korea

by Hyun Jo, Sovetgul Asekova, Mohammad Amin Bayat, Liakat Ali, Jong Tae Song, Yu-Shin Ha, Dong-Hyuck Hong and Jeong-Dong Lee

Agriculture 2022, 12(5), 619; https://doi.org/10.3390/agriculture12050619 - 27 Apr 2022

Cited by 19 | Viewed by 4649

Abstract

Renewable energy generation has attracted growing interest globally. The agro-photovoltaic (APV) system is a new alternative to conventional photovoltaic power plants, which can simultaneously generate renewable energy and increase agricultural productivity by the use of solar panels on the same farmland. The optimization [...] Read more.

Renewable energy generation has attracted growing interest globally. The agro-photovoltaic (APV) system is a new alternative to conventional photovoltaic power plants, which can simultaneously generate renewable energy and increase agricultural productivity by the use of solar panels on the same farmland. The optimization of crop yields and assessment of their environmental sensitivity under the solar panels have not yet been evaluated with various crop species. This study aimed to evaluate the agronomic performances and crop yields under the APV system and the open field with crop species such as rice, onion, garlic, rye, soybean, adzuki bean, monocropping corn, and mixed planting of corn with soybean in South Korea. The results indicated that there was statistically no negative impact of the APV system on the forage yield of rye and corn over two years, suggesting that forage crops under the APV system were suitable to producing forage yield for livestock. In addition, the measured forage quality of rye was not significantly different between the open field and the APV system. However, rice yield was statistically reduced under the APV system. The yield of legume crops and vegetables in this study did not show consistent statistical results in two years. For further study, crop yield trials will still be required for rice, soybean, adzuki bean, onion, and garlic for multiple years under the APV system. Full article

(This article belongs to the Special Issue Precision Agriculture Adoption Strategies)

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24 pages, 1224 KiB

Open AccessEditor’s ChoiceReview

Use of Botanical Pesticides in Agriculture as an Alternative to Synthetic Pesticides

by Patrick Maada Ngegba, Gaofeng Cui, Muhammad Zaryab Khalid and Guohua Zhong

Agriculture 2022, 12(5), 600; https://doi.org/10.3390/agriculture12050600 - 24 Apr 2022

Cited by 77 | Viewed by 28443

Abstract

Pest management is being confronted with immense economic and environmental issues worldwide because of massive utilization and over-reliance on pesticides. The non-target toxicity, residual consequence, and challenging biodegradability of these synthetic pesticides have become a serious concern, which urgently requires the alternative and [...] Read more.

Pest management is being confronted with immense economic and environmental issues worldwide because of massive utilization and over-reliance on pesticides. The non-target toxicity, residual consequence, and challenging biodegradability of these synthetic pesticides have become a serious concern, which urgently requires the alternative and prompt adoption of sustainable and cost-effective pest control measures. Increasing attention in environmental safety has triggered interest in pest control approaches through eco-friendly plant-based pesticides. Botanical pesticidal constituents are effective against myriads of destructive pests and diseases. More importantly, they are widely available, inexpensive, accessible, rapidly biodegradable, and have little toxicity to beneficiary agents. The phytochemical compositions in diverse plant species are responsible for their varying mechanisms of action against pests and diseases. However, difficulties in their formulation and insufficient appropriate chemical data have led to a low level of acceptance and adoption globally. Therefore, the review seeks to highlight the status, phytochemical compositions, insecticidal mechanisms, and challenges of plant-based pesticide usage in sustainable agricultural production. Full article

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23 pages, 10450 KiB

Open AccessEditor’s ChoiceArticle

Motion Planning of the Citrus-Picking Manipulator Based on the TO-RRT Algorithm

by Cheng Liu, Qingchun Feng, Zuoliang Tang, Xiangyu Wang, Jinping Geng and Lijia Xu

Agriculture 2022, 12(5), 581; https://doi.org/10.3390/agriculture12050581 - 21 Apr 2022

Cited by 12 | Viewed by 2639

Abstract

The working environment of a picking robot is complex, and the motion-planning algorithm of the picking manipulator will directly affect the obstacle avoidance effect and picking efficiency of the manipulator. In this study, a time-optimal rapidly-exploring random tree (TO-RRT) algorithm is proposed. First, [...] Read more.

The working environment of a picking robot is complex, and the motion-planning algorithm of the picking manipulator will directly affect the obstacle avoidance effect and picking efficiency of the manipulator. In this study, a time-optimal rapidly-exploring random tree (TO-RRT) algorithm is proposed. First, this algorithm controls the target offset probability of the random tree through the potential field and introduces a node-first search strategy to make the random tree quickly escape from the repulsive potential field. Second, an attractive step size and a “step-size dichotomy” are proposed to improve the directional search ability of the random tree outside the repulsive potential field and solve the problem of an excessively large step size in extreme cases. Finally, a regression superposition algorithm is used to enhance the ability of the random tree to explore unknown space in the repulsive potential field. In this paper, independent experiments were carried out in MATLAB, MoveIt!, and real environments. The path-planning speed was increased by

99.73 %

, the path length was decreased by

17.88 %

, and the number of collision detections was reduced by

99.08 %

. The TO-RRT algorithm can be used to provide key technical support for the subsequent design of picking robots. Full article

(This article belongs to the Special Issue Robots and Autonomous Machines for Agriculture Production)

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18 pages, 3577 KiB

Open AccessEditor’s ChoiceArticle

Regression-Based Correction and I-PSO-Based Optimization of HMCVT’s Speed Regulating Characteristics for Agricultural Machinery

by Zhun Cheng and Zhixiong Lu

Agriculture 2022, 12(5), 580; https://doi.org/10.3390/agriculture12050580 - 21 Apr 2022

Cited by 14 | Viewed by 1577

Abstract

To improve the speed regulating characteristics of continuously variable transmission for agricultural machinery, in order to meet the engineering and technical requirements of precision agriculture and intelligent agriculture, the paper researches and proposes a method combining the analysis of speed regulating characteristics, regression-based [...] Read more.

To improve the speed regulating characteristics of continuously variable transmission for agricultural machinery, in order to meet the engineering and technical requirements of precision agriculture and intelligent agriculture, the paper researches and proposes a method combining the analysis of speed regulating characteristics, regression-based correction, and the improved particle swarm optimization (I-PSO) algorithm. First, the paper analyzes the degree of deviation between the linearization degree and the theoretical value of the speed regulating characteristics of the variable-pump constant-motor system of agricultural machinery according to the measurement results of the bench test. Next, the paper corrects the speed regulating characteristics and compares the regression results based on four models. Finally, the paper proposes a design method for the expected speed regulating characteristics of agricultural machinery and it completes the optimization of speed regulating characteristics and the matching of transmission parameters with the I-PSO algorithm. Results indicate that the speed regulating characteristics of the variable-pump constant-motor system show high linearization (with a coefficient of determination of 0.9775). The theoretical and measured values of the speed regulating characteristics have a certain deviation (with a coefficient of determination of 0.8934). Therefore, correcting the speed regulating characteristics of the variable-pimp constant-motor system is highly necessary. In addition, the second reciprocal function model proposed has the highest correction precision (with a coefficient of determination of 0.9978). The I-PSO algorithm is applicable to the design and application of hydro-mechanical continuously variable transmission (HMCVT) for agricultural machinery. The new method proposed can improve the HMCVT’s speed regulating characteristics efficiently and quickly. It also ensures that the speed regulating characteristics are highly consistent with the expected design characteristics (with a mean error of 1.73%). Thus, the research offers a theoretical direction and design basis for the research and development of continuously variable transmission units in agricultural machinery. Full article

(This article belongs to the Special Issue Design and Application of Agricultural Equipment in Tillage System)

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17 pages, 1743 KiB

Open AccessEditor’s ChoicePerspective

The Role of Beekeeping in the Generation of Goods and Services: The Interrelation between Environmental, Socioeconomic, and Sociocultural Utilities

by Olatz Etxegarai-Legarreta and Valeriano Sanchez-Famoso

Agriculture 2022, 12(4), 551; https://doi.org/10.3390/agriculture12040551 - 12 Apr 2022

Cited by 15 | Viewed by 10074

Abstract

Honey bees and beekeeping belong to a large enterprise where the managers are the beekeepers, the workers are the bees, and the products generated are ecosystem goods and services, mostly intangible. Evidence for a reduction in the number of pollinating insects in the [...] Read more.

Honey bees and beekeeping belong to a large enterprise where the managers are the beekeepers, the workers are the bees, and the products generated are ecosystem goods and services, mostly intangible. Evidence for a reduction in the number of pollinating insects in the planet due to causes that are still being studied has put the spotlight on beekeeping activity and bees (wild and managed) due to their extraordinary capacity to contribute to pollination. The aim of the present work was to detect, identify, and analyze the set of environmental, socioeconomic, and sociocultural utilities (goods and services) generated by honey bees and beekeeping in order to identify possible interrelationships between them. The aim was to demonstrate that these utilities, far from being watertight, are interconnected, which will help to increase their value and highlight their positive externalities (genetic diversity and landscape, among others). This research begins with an overview of some seminal articles, published mainly in the last three years, which were searched following a review using keywords in major databases. After reading the seminal articles and others that were referenced, we analyzed the main utilities generated by honey bees and the possible relationships between them. The main contribution of our results is the determination that the generated utilities are interrelated, which could contribute to increasing their value. In addition, we found that, of the three interrelated dimensions, the socioeconomic dimension encompasses the environmental and sociocultural dimensions. The article ends by proposing future lines of research. Full article

(This article belongs to the Section Farm Animal Production)

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21 pages, 4932 KiB

Open AccessEditor’s ChoiceArticle

Design and Performance Test of a Jujube Pruning Manipulator

by Bin Zhang, Xuegeng Chen, Huiming Zhang, Congju Shen and Wei Fu

Agriculture 2022, 12(4), 552; https://doi.org/10.3390/agriculture12040552 - 12 Apr 2022

Cited by 12 | Viewed by 2580

Abstract

To solve the problems of poor working conditions and high labor intensity for artificially pruning jujube trees, a pruning scheme using a manipulator is put forward in the present paper. A pruning manipulator with five degrees of freedom for jujube trees is designed. [...] Read more.

To solve the problems of poor working conditions and high labor intensity for artificially pruning jujube trees, a pruning scheme using a manipulator is put forward in the present paper. A pruning manipulator with five degrees of freedom for jujube trees is designed. The key components of the manipulator are designed and the dimension parameters of each joint component are determined. The homogeneous transformation of the DH parameter method is used to solve the kinematic equation of the jujube pruning manipulator, and the kinematic theoretical model of the manipulator is established. Finally, the relative position and attitude relationship among the coordinate systems is obtained. A three-dimensional mathematical simulation model of the jujube pruning manipulator is established, based on MATLAB Robotics Toolbox. The Monte Carlo method is used to carry out the manipulator workspace simulation, and the results of the simulation analysis show that the working space of the manipulator is −600~800 mm, −800~800 mm, and −200~1800 mm in the X, Y, and Z direction, respectively. It can be concluded that the geometric size of the jujube pruning manipulator meets the needs of jujube pruning in a dwarf and densely planted jujube garden. Then, based on the high-speed camera technology, the performance test of the manipulator is carried out. The results show that the positioning error of the manipulator at different pruning points of jujube trees is less than 10 mm, and the pruning success rate of a single jujube tree is higher than 85.16%. This study provides a theoretical basis and technical support for the intelligent pruning of jujube trees in an orchard. Full article

(This article belongs to the Special Issue Robots and Autonomous Machines for Agriculture Production)

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18 pages, 30348 KiB

Open AccessEditor’s ChoiceArticle

Green Banana Maturity Classification and Quality Evaluation Using Hyperspectral Imaging

by Xuan Chu, Pu Miao, Kun Zhang, Hongyu Wei, Han Fu, Hongli Liu, Hongzhe Jiang and Zhiyu Ma

Agriculture 2022, 12(4), 530; https://doi.org/10.3390/agriculture12040530 - 8 Apr 2022

Cited by 26 | Viewed by 6933

Abstract

Physiological maturity of bananas is of vital importance in determination of their quality and marketability. This study assessed, with the use of a Vis/NIR hyperspectral imaging (400–1000 nm), the feasibility in differentiating six maturity levels (maturity level 2, 4, and 6 to 9) [...] Read more.

Physiological maturity of bananas is of vital importance in determination of their quality and marketability. This study assessed, with the use of a Vis/NIR hyperspectral imaging (400–1000 nm), the feasibility in differentiating six maturity levels (maturity level 2, 4, and 6 to 9) of green dwarf banana and characterizing their quality changes during maturation. Spectra were extracted from three zones (pedicel, middle and apex zone) of each banana finger, respectively. Based on spectra of each zone, maturity identification models with high accuracy (all over 91.53% in validation set) were established by partial least squares discrimination analysis (PLSDA) method with raw spectra. A further generic PLSDA model with an accuracy of 94.35% for validation was created by the three zones’ spectra pooled to omit the effect of spectra acquisition position. Additionally, a spectral interval was selected to simplify the generic PLSDA model, and an interval PLSDA model was built with an accuracy of 85.31% in the validation set. For characterizing some main quality parameters (soluble solid content, SSC; total acid content, TA; chlorophyll content and total chromatism, ΔE*) of banana, full-spectra partial least squares (PLS) models and interval PLS models were, respectively, developed to correlate those parameters with spectral data. In full-spectra PLS models, high coefficients of determination (R²) were 0.74 for SSC, 0.68 for TA, and fair of 0.42 as well as 0.44 for chlorophyll and ΔE*. The performance of interval PLS models was slightly inferior to that of the full-spectra PLS models. Results suggested that models for SSC and TA had an acceptable predictive ability (R² = 0.64 and 0.59); and models for chlorophyll and ΔE* (R² = 0.34 and 0.30) could just be used for sample screening. Visualization maps of those quality parameters were also created by applying the interval PLS models on each pixel of the hyperspectral image, the distribution of quality parameters in which were basically consistent with the actual measurement. This study proved that the hyperspectral imaging is a useful tool to assess the maturity level and quality of dwarf bananas. Full article

(This article belongs to the Special Issue Sensors Applied to Agricultural Products)

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15 pages, 10221 KiB

Open AccessEditor’s ChoiceArticle

Simulation and Experiment of Spiral Soil Separation Mechanism of Compound Planter Based on Discrete Element Method (DEM)

by Lianjie Han, Wei Yuan, Jinjin Yu, Jiajun Jin, Dongshen Xie, Xiaobo Xi, Yifu Zhang and Ruihong Zhang

Agriculture 2022, 12(4), 511; https://doi.org/10.3390/agriculture12040511 - 4 Apr 2022

Cited by 11 | Viewed by 2307

Abstract

In order to solve the problems of blocking the drainage ditch and reducing the soil flatness caused by soil accumulation when using compound planter with plowshare to ditch, a spiral soil separation mechanism (SSSM) is designed. The SSSM is analyzed. In order to [...] Read more.

In order to solve the problems of blocking the drainage ditch and reducing the soil flatness caused by soil accumulation when using compound planter with plowshare to ditch, a spiral soil separation mechanism (SSSM) is designed. The SSSM is analyzed. In order to obtain the optimal parameters of the SSSM, based on the discrete element method, the multifactor test is carried out with the embedded depth, pitch, and rotation speed of the spiral blade as the test factors and the soil separation distance and uniformity as the evaluation index. The optimal parameters are the embedded depth 49 mm, pitch 331 mm, and rotation speed of the spiral blade 318 r min⁻¹. The field experiment is carried out with these parameters, with soil separation distance 900 mm and standard deviation of soil height 7.8 mm, which is consistent with the simulation results. No blockage of drainage ditch was found, which shows that this device can effectively solve the problem. This study can provide a reference for the design of soil separation equipment using spiral soil separation device. Full article

(This article belongs to the Special Issue Design and Application of Agricultural Equipment in Tillage System)

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21 pages, 3885 KiB

Open AccessEditor’s ChoiceArticle

Effects of Kaolin and Shading Net on the Ecophysiology and Berry Composition of Sauvignon Blanc Grapevines

by Eleonora Cataldo, Maddalena Fucile and Giovan Battista Mattii

Agriculture 2022, 12(4), 491; https://doi.org/10.3390/agriculture12040491 - 31 Mar 2022

Cited by 14 | Viewed by 2865

Abstract

Rising temperatures in most viticultural regions are associated with a higher incidence of drastic weather circumstances such as heatwaves. The consequences are reflected in qualitative and quantitative white grapes characteristics. In fact, there is an enhancement in alcohol content and a jeopardized reduction [...] Read more.

Rising temperatures in most viticultural regions are associated with a higher incidence of drastic weather circumstances such as heatwaves. The consequences are reflected in qualitative and quantitative white grapes characteristics. In fact, there is an enhancement in alcohol content and a jeopardized reduction in the aromatic potential. We performed a scientific test to assuage the bump of heatwaves and exposure of grapes on Vitis vinifera cv. “Sauvignon Blanc” with exposed vines (untreated) or with kaolin foliar treatment or with partial fruit-zone shading (shading net 30 and 70%). This work aimed to evaluate the effects of shading net (SD-30% and SD-70%) and foliar kaolin (K) treatment on physiology, technological maturity, and thiolic precursors in Italy during the 2020–2021 seasons. For this purpose, four treatments were established: SD-30% (green artificial shading net at 30%), SD-70% (green artificial shading net at 70%), K (foliar kaolin), and CTRL (no application). During the two vintages, single-leaf gas exchange appraisal, leaf temperature, berry temperature, chlorophyll fluorescence, pre-dawn, and leaf water potential were measured. Moreover, berry weight, pH, °Brix, acidity (technological maturity specifications), and the following thiolic precursors were analyzed: 3-S-glutathionylhexan-1-ol (Glut-3MH), S-4-(4-methylpentan-2-one)-L-cysteine (Cys-4MMP), and 3-S-cysteinylhexan-1-ol (Cys-3MH). SD-70% and K denoted less negative water potential, a lower berry temperature, and a higher level of all precursors than the other treatments. Acidity and sugar parameters indicated significant differences among treatments. The lower berry weight and the lower tartaric acidity were found in the CTRL treatment. In comparison, SD-70% and K showed lower and more balanced sugar contents. As a result of global warming, color shading net and kaolin have been demonstrated to be good practices to counterpoise the divergence between aromatic and technological maturity in Sauvignon Blanc grapevines. Full article

(This article belongs to the Section Agricultural Product Quality and Safety)

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30 pages, 12098 KiB

Open AccessEditor’s ChoiceArticle

A Spatial Feature-Enhanced Attention Neural Network with High-Order Pooling Representation for Application in Pest and Disease Recognition

by Jianlei Kong, Hongxing Wang, Chengcai Yang, Xuebo Jin, Min Zuo and Xin Zhang

Agriculture 2022, 12(4), 500; https://doi.org/10.3390/agriculture12040500 - 31 Mar 2022

Cited by 71 | Viewed by 7532

Abstract

With the development of advanced information and intelligence technologies, precision agriculture has become an effective solution to monitor and prevent crop pests and diseases. However, pest and disease recognition in precision agriculture applications is essentially the fine-grained image classification task, which aims to [...] Read more.

With the development of advanced information and intelligence technologies, precision agriculture has become an effective solution to monitor and prevent crop pests and diseases. However, pest and disease recognition in precision agriculture applications is essentially the fine-grained image classification task, which aims to learn effective discriminative features that can identify the subtle differences among similar visual samples. It is still challenging to solve for existing standard models troubled by oversized parameters and low accuracy performance. Therefore, in this paper, we propose a feature-enhanced attention neural network (Fe-Net) to handle the fine-grained image recognition of crop pests and diseases in innovative agronomy practices. This model is established based on an improved CSP-stage backbone network, which offers massive channel-shuffled features in various dimensions and sizes. Then, a spatial feature-enhanced attention module is added to exploit the spatial interrelationship between different semantic regions. Finally, the proposed Fe-Net employs a higher-order pooling module to mine more highly representative features by computing the square root of the covariance matrix of elements. The whole architecture is efficiently trained in an end-to-end way without additional manipulation. With comparative experiments on the CropDP-181 Dataset, the proposed Fe-Net achieves Top-1 Accuracy up to 85.29% with an average recognition time of only 71 ms, outperforming other existing methods. More experimental evidence demonstrates that our approach obtains a balance between the model’s performance and parameters, which is suitable for its practical deployment in precision agriculture art applications. Full article

(This article belongs to the Special Issue Application of Decision Support Systems in Agriculture)

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23 pages, 7811 KiB

Open AccessEditor’s ChoiceArticle

Investigating Flood Impact on Crop Production under a Comprehensive and Spatially Explicit Risk Evaluation Framework

by Xi Wang, Zhanyan Liu and Huili Chen

Agriculture 2022, 12(4), 484; https://doi.org/10.3390/agriculture12040484 - 30 Mar 2022

Cited by 14 | Viewed by 22730

Abstract

Due to the projected increased frequency of occurrence of extreme flood events, it is becoming increasingly important to pay attention to agricultural flood management. The middle and lower reaches of the Yangtze River Basin (MLYRB), as one of the most important agricultural areas [...] Read more.

Due to the projected increased frequency of occurrence of extreme flood events, it is becoming increasingly important to pay attention to agricultural flood management. The middle and lower reaches of the Yangtze River Basin (MLYRB), as one of the most important agricultural areas in the world, frequently suffer from the ravages of long-duration extreme flood events. Comprehensive flood risk evaluation can provide important support for effective management strategies by focusing on the combination of flood hazard and the consequences of flooding in areas exposed to the inundation. Previous satellite-based flood disturbance detection methods intended for use in single-cropping agricultural systems cannot be applied to the MLYRB with multi-cropping practices and long-duration flood events. Additionally, comprehensive agricultural flood risk evaluations traditionally neglect the characteristics of the impact of flooding with strong spatial and temporal variability. Thus, in this research, an integrated disturbance index (IDI) was developed to detect the impact of flood disturbance on crop growth, aiming to acquire a map of crop damage condition for a multi-cropping agricultural system with long-duration flood events that is spatially explicit and has a sufficiently high spatial resolution. A coupled hydrological and 2D hydraulic model parallelized using the GPU approach was employed to simulate flood flows, aiming at deriving sufficient meaningful detail at the local scale in terms of flood inundation patterns and processes over the whole natural watershed. Additionally, a spatial map of the combined effects of flood hazard and the consequences of flooding was used to investigate the relationship between flood characteristics and associated loss extent with the random forest model. The comprehensive evaluation framework was applied for the 2010 flood event in the MLYRB. The evaluation results indicate that the detection results based on IDI are consistent with the governmental statistics, the most hard-hit areas in related reports, and the spatial characteristics of river floods. The coupled hydrological–hydraulic model offers a clear picture of the flood characteristics over the whole basin, while simultaneously ensuring a sufficiently high spatial resolution. Our findings show that flood duration is the most important predictor in predicting crop damage extent. Full article

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16 pages, 5143 KiB

Open AccessEditor’s ChoiceArticle

Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5

by Yue Gu, Shucai Wang, Yu Yan, Shijie Tang and Shida Zhao

Agriculture 2022, 12(4), 485; https://doi.org/10.3390/agriculture12040485 - 30 Mar 2022

Cited by 20 | Viewed by 4583

Abstract

The behavior of cage-reared ducks is an important index to judge the health status of laying ducks. For the automatic recognition task of cage-reared duck behavior based on machine vision, by comparing the detection performance of YoloV4 (you only look once), YoloV5, and [...] Read more.

The behavior of cage-reared ducks is an important index to judge the health status of laying ducks. For the automatic recognition task of cage-reared duck behavior based on machine vision, by comparing the detection performance of YoloV4 (you only look once), YoloV5, and Faster-RCNN, this work selected the YoloV5 target detection network with the best performance to identify the three behaviors related to avoidance after a cage-reared duck emergency. The recognition average precision was 98.2% (neck extension), 98.5% (trample), and 98.6% (spreading wings), respectively, and the detection speed was 20.7 FPS. Based on this model, in this work, 10 duck cages were randomly selected, and each duck cage recorded video for 3 min when there were breeders walking in the duck house and no one was walking for more than 20 min. By identifying the generation time and frequency of neck extension out of the cage, trample, and wing spread, it was concluded that the neck extension, trampling, and wing spread behaviors of laying ducks increase significantly when they feel panic and fear. The research provides an efficient, intelligent monitoring method for the behavior analysis of cage-rearing of ducks and provides a basis for the health status judgment and behavior analysis of unmonitored laying ducks in the future. Full article

(This article belongs to the Section Farm Animal Production)

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17 pages, 2418 KiB

Open AccessEditor’s ChoiceArticle

Cytpchrome P450 CYP4G68 Is Associated with Imidacloprid and Thiamethoxam Resistance in Field Whitefly, Bemisia tabaci (Hemiptera: Gennadius)

by Jinjin Liang, Jing Yang, Jinyu Hu, Buli Fu, Peipan Gong, Tianhua Du, Hu Xue, Xuegao Wei, Shaonan Liu, Mingjiao Huang, Cheng Yin, Yao Ji, Chao He, Wen Xie, Ran Wang, Xin Yang and Youjun Zhang

Agriculture 2022, 12(4), 473; https://doi.org/10.3390/agriculture12040473 - 27 Mar 2022

Cited by 18 | Viewed by 2833

Abstract

The superfamily cytochrome P450s is involved in the evolution of insecticide resistance. However, whether CYP4G68, a differentially expressed gene identified from our transcriptomics analysis, confers resistance to the world’s heavily used insecticide class neonicotinoids is unknown. Hence, we explored the role of [...] Read more.

The superfamily cytochrome P450s is involved in the evolution of insecticide resistance. However, whether CYP4G68, a differentially expressed gene identified from our transcriptomics analysis, confers resistance to the world’s heavily used insecticide class neonicotinoids is unknown. Hence, we explored the role of CYP4G68 in conferring imidacloprid and thiamethoxam resistance in Bemisia tabaci. The species B. tabaci MED developed low-to-high resistance to imidacloprid and thiamethoxam. Exposure to imidacloprid and thiamethoxam significantly increased the expression of CYP4G68. Moreover, quantitative real-time PCR analysis demonstrated that CYP4G68 was remarkably overexpressed in imidacloprid-resistant and thiamethoxam-resistant strains compared to susceptible strains. Further correlation analysis showed that CYP4G68 expression was significantly positively correlated with the associated resistance level in various strains of B. tabaci. These results suggest that the enhanced expression of CYP4G68 appears to mediate imidacloprid and thiamethoxam resistance in B. tabaci. Additionally, silencing CYP4G68 via RNA interference strongly increased the susceptibility of B. tabaci MED to imidacloprid and thiamethoxam. Collectively, this work revealed that CYP4G68 plays a vital role in imidacloprid and thiamethoxam resistance in B. tabaci MED. These findings will not only advance our understanding of the role of P450s in insecticide resistance but also provide a great potential target for the sustainable control of destructive insect pests such as whiteflies. Full article

(This article belongs to the Special Issue Sustainable Use of Pesticides)

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19 pages, 4325 KiB

Open AccessEditor’s ChoiceArticle

Influence of Organic and Mineral Fertilizers on Soil Organic Carbon and Crop Productivity under Different Tillage Systems: A Meta-Analysis

by Mohamed Allam, Emanuele Radicetti, Valentina Quintarelli, Verdiana Petroselli, Sara Marinari and Roberto Mancinelli

Agriculture 2022, 12(4), 464; https://doi.org/10.3390/agriculture12040464 - 25 Mar 2022

Cited by 20 | Viewed by 4676

Abstract

The intensive use of mineral (M) fertilizers may cause harm the environment via leaching or greenhouse gas emissions, destroy soil fertility as a consequence of loss of soil organic matter, and, due to their high price, they are economically unviable for producers. It [...] Read more.

The intensive use of mineral (M) fertilizers may cause harm the environment via leaching or greenhouse gas emissions, destroy soil fertility as a consequence of loss of soil organic matter, and, due to their high price, they are economically unviable for producers. It is widely accepted that organic (O) fertilizers may deal with pressing challenges facing modern agriculture, even if farmers need to improve their knowledge for applying in fertilization programs. A meta-analysis approach has been adopted to evaluate the effects on soil organic carbon (SOC) and crop yield of O fertilizers, applied alone or in combination with mineral fertilizers (MO) under conventional (CT), reduced (RT), and no-tillage (NT) regimes. The analysis was performed in different climatic conditions, soil properties, crop species, and irrigation management. Organic fertilizers have a positive influence in increasing SOC compared with M (on average 12.9%), even if high values were observed under NT (20.6%). The results highlighted the need for flexible and environment-specific systems when considering organic fertilization subjected to different tillage regimes. Similarly, MO application showed a better crop yield response in CT and RT under coarse soils when compared with M fertilizer applied alone (on average 13.4 and 12.7%, respectively), while in medium-textured soils, CT and RT yielded better than NT under O fertilizers (9.5 and 11.2 vs. 2.5%, respectively). Among the crop species, legumes performed better when O fertilizers were adopted than M fertilizers (on average 15.2%), while among the other crop species, few differences were detected among the fertilization programs. Under irrigated systems, RT and NT led to higher productivity than CT, especially under MO treatments (on average 9.2 vs. 3.4%, respectively). The results highlighted the importance of the environmental and agronomical factors and how their understanding could affect the impact of these conservation farming practices on crop productivity to improve the sustainability of the farming system in a specific region. Full article

(This article belongs to the Special Issue Soil Quality and Health to Assess Agro-Ecosystems Services)

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5 pages, 211 KiB

Open AccessEditor’s ChoiceEditorial

Fertilizer Use, Soil Health and Agricultural Sustainability

by Pavel Krasilnikov, Miguel Angel Taboada and Amanullah

Agriculture 2022, 12(4), 462; https://doi.org/10.3390/agriculture12040462 - 25 Mar 2022

Cited by 40 | Viewed by 24293

Abstract

Due to the growing population and consequent pressure of use, agricultural soils must maintain adequate levels of quantity and quality to produce food, fiber, and energy, without falling victim to a negative impact on their balance of nutrients, health, or their ability to [...] Read more.

Due to the growing population and consequent pressure of use, agricultural soils must maintain adequate levels of quantity and quality to produce food, fiber, and energy, without falling victim to a negative impact on their balance of nutrients, health, or their ability to function [...] Full article

(This article belongs to the Special Issue Fertilizer Use, Soil Health and Agricultural Sustainability)

21 pages, 8048 KiB

Open AccessEditor’s ChoiceArticle

Temperature Effects on the Shoot and Root Growth, Development, and Biomass Accumulation of Corn (Zea mays L.)

by Charles Hunt Walne and Kambham Raja Reddy

Agriculture 2022, 12(4), 443; https://doi.org/10.3390/agriculture12040443 - 22 Mar 2022

Cited by 21 | Viewed by 7603

Abstract

Temperature is a critical environmental factor regulating plant growth and yield. Corn is a major agronomic crop produced globally over a vast geographic region, and highly variable climatic conditions occur spatially and temporally throughout these regions. Current literature lacks a comprehensive study comparing [...] Read more.

Temperature is a critical environmental factor regulating plant growth and yield. Corn is a major agronomic crop produced globally over a vast geographic region, and highly variable climatic conditions occur spatially and temporally throughout these regions. Current literature lacks a comprehensive study comparing the effects of temperature on above versus below-ground growth and development and biomass partitioning of corn measured over time. An experiment was conducted to quantify the impact of temperature on corn’s early vegetative growth and development. Cardinal temperatures (T_min, T_opt, and T_max) were estimated for different aspects of above- and below-ground growth processes. Plants were subjected to five differing day/night temperature treatments of 20/12, 25/17, 30/22, 35/27, and 40/32 °C using sun-lit controlled environment growth chambers for four weeks post-emergence. Corn plant height, leaves, leaf area, root length, surface area, volume, numbers of tips and forks, and plant component part dry weights were measured weekly. Cardinal temperatures were estimated, and the relationships between parameters and temperature within these cardinal limits were estimated using a modified beta function model. Cardinal temperature limits for whole plant dry weight production were 13.5 °C (T_min), 30.5 °C (T_opt), and 38 °C (T_max). Biomass resources were prioritized to the root system at low temperatures and leaves at high temperatures. Root growth displayed the lowest optimum temperature compared to root development, shoot growth, and shoot development. The estimated cardinal temperatures and functional algorithms produced in this study, which include both above and below-ground aspects of plant growth, could be helpful to update crop models and could be beneficial to estimate corn growth under varying temperature conditions. These results could also be applicable when considering management decisions for maximizing field production and implementing emerging precision agriculture technology. Full article

(This article belongs to the Special Issue Physiological and Ecological Characteristics, and Sustainable Production of High Yield Maize)

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13 pages, 2805 KiB

Open AccessEditor’s ChoiceArticle

Preliminary Findings of Polypropylene Carbonate (PPC) Plastic Film Mulching Effects on the Soil Microbial Community

by Jing Liang, Jiafan Zhang, Zongmu Yao, Shouyang Luo, Lei Tian, Chunjie Tian and Yu Sun

Agriculture 2022, 12(3), 406; https://doi.org/10.3390/agriculture12030406 - 14 Mar 2022

Cited by 12 | Viewed by 2857

Abstract

The farmland residual film pollution caused by traditional PE film has an adverse impact on crops and the environment. Polypropylene carbonate (PPC) film is a fully biodegradable film that can alleviate “white pollution”. In this study, the soil physicochemical properties and the composition [...] Read more.

The farmland residual film pollution caused by traditional PE film has an adverse impact on crops and the environment. Polypropylene carbonate (PPC) film is a fully biodegradable film that can alleviate “white pollution”. In this study, the soil physicochemical properties and the composition and function of the soil community of FM (PPC film mulching) and CK (no film) treatments were determined to explore the effect of PPC film mulching on soil and the soil microbial community. Furthermore, the microorganisms at different time periods during the degradation of PPC mulch film were also analyzed. The results showed that film mulching increased soil pH but decreased the contents of EC and SOC, and there was no significant difference in the contents of AP and AK. The relative abundance of the phyla Acidobacteria was increased with film mulching, and the relative abundance of the genera MB_A2_108 also increased in the film mulched soil. Among the soil physicochemical properties, pH and SOC were the most important factors leading to changes in the composition of the bacterial and fungal communities. PPC film mulching had no significant effect on soil microbial community abundance and diversity. In addition, Pseudomonas, Flavobacterium, and Rhizobacter were dominant in the degradation of PPC film. Our research results provide a scientific theoretical basis for soil safety and the large-scale use of PPC biodegradable mulching films and a research foundation for the degradation of PPC plastics. Full article

(This article belongs to the Section Agricultural Soils)

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15 pages, 527 KiB

Open AccessEditor’s ChoiceArticle

Occurrence of Mycotoxins in Grass and Whole-Crop Cereal Silages—A Farm Survey

by Katariina Manni, Sari Rämö, Marcia Franco, Marketta Rinne and Arto Huuskonen

Agriculture 2022, 12(3), 398; https://doi.org/10.3390/agriculture12030398 - 12 Mar 2022

Cited by 13 | Viewed by 2723

Abstract

Mycotoxin incidence in forage may heavily affect the amount of toxins consumed by cattle. However, many studies have focused on mycotoxin occurrence in cereals and there are less studies of forages, particularly of grass silages. For determining the occurrence of mycotoxins in farm [...] Read more.

Mycotoxin incidence in forage may heavily affect the amount of toxins consumed by cattle. However, many studies have focused on mycotoxin occurrence in cereals and there are less studies of forages, particularly of grass silages. For determining the occurrence of mycotoxins in farm silages under Northern European conditions in Finland, 37 grass silage and 6 whole-crop cereal silage batches were analysed separately for surface, core and, if present, visibly mouldy spots. Mycotoxins were found in 92% of the samples. All mouldy samples contained mycotoxins. Beauvericin was the most common mycotoxin in grass silages and roquefortine C in whole-crop cereal silages. In mouldy samples, beauvericin, mycophenolic acid and roquefortine C were the most common mycotoxins in the grass silage and mycophenolic acid in the whole-crop cereal silage. Aflatoxins were not found in any of the samples. On average, all samples contained more than one type of mycotoxin. Concentrations of mycotoxins varied considerably from very low to very high values. The results of this survey indicate that silage-fed ruminants can be exposed to a broad range of mycotoxins. The absence of visible moulds does not always indicate mycotoxin-free feed. All moulded samples contained mycotoxins and some at very high concentrations, and they contained more different types of mycotoxins than samples without visible mould. Thus, feeding mouldy feeds to animals should be avoided. Full article

(This article belongs to the Special Issue Forage Quality, Conservation and Evaluation in Ruminant Production Systems)

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13 pages, 803 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

The Digital Applications of “Agriculture 4.0”: Strategic Opportunity for the Development of the Italian Citrus Chain

by Alessandro Scuderi, Giovanni La Via, Giuseppe Timpanaro and Luisa Sturiale

Agriculture 2022, 12(3), 400; https://doi.org/10.3390/agriculture12030400 - 12 Mar 2022

Cited by 28 | Viewed by 5153

Abstract

Contemporary agriculture is increasingly oriented toward the synergistic adoption of technologies such as the Internet of Things, Internet of Farming, big data analytics, and blockchain to combine resource protection and economic, social, and environmental sustainability. In Italy, the market growth potential of “Agriculture [...] Read more.

Contemporary agriculture is increasingly oriented toward the synergistic adoption of technologies such as the Internet of Things, Internet of Farming, big data analytics, and blockchain to combine resource protection and economic, social, and environmental sustainability. In Italy, the market growth potential of “Agriculture 4.0” and “Farming 4.0” solutions is very high, but the adoption of the related technological innovations is still low. Italian companies are increasingly aware of the opportunities offered by the 4.0 paradigm, but there are still cultural and technological limits to the full development of the phenomenon. This research aims to contribute to knowledge that will improve the propensity of agricultural operators to adopt the digital solutions of “Agriculture 4.0” by demonstrating its potential, along with its limits. To this end, an integrated methodological approach was adopted, built with focus groups and multicriteria analysis, to define and assess the possible future scenarios resulting from the implementation of digital transformation. The results show an increased focus on solutions that allow the integration of new tools to support those already used in the business organization and at a sustainable cost. To enable the development of “Agriculture 4.0”, we propose that it is necessary to invest in training operators in the supply chain, and above all, raising awareness among farmers, who it is essential fully appreciate the potential benefits of the 4.0 revolution. Full article

(This article belongs to the Special Issue Agricultural Food Marketing, Economics and Policies)

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18 pages, 806 KiB

Open AccessEditor’s ChoiceReview

Methyl Benzoate as a Promising, Environmentally Safe Insecticide: Current Status and Future Perspectives

by Md. Munir Mostafiz, Errol Hassan and Kyeong-Yeoll Lee

Agriculture 2022, 12(3), 378; https://doi.org/10.3390/agriculture12030378 - 8 Mar 2022

Cited by 16 | Viewed by 6190

Abstract

The widespread use of synthetic chemical pesticides beginning in the late 1930s has contributed to the development of insecticide resistance of many important species of pest insects and plants. Recent trends in pesticide development have emphasized the use of more environmentally benign control [...] Read more.

The widespread use of synthetic chemical pesticides beginning in the late 1930s has contributed to the development of insecticide resistance of many important species of pest insects and plants. Recent trends in pesticide development have emphasized the use of more environmentally benign control methods that take into consideration environmental, food safety, and human health. Biopesticides (e.g., naturally occurring pesticidal compounds) are alternative pest management tools that normally have no negative impact on human health or the environment. Here we review methyl benzoate, a relatively new botanical insecticide that occurs naturally as a metabolite in plants, and whose odor is an attractant to some insects. Since 2016, many studies have shown that methyl benzoate is an effective pesticide against a range of different agricultural, stored product, and urban insect pests. Methyl benzoate has several important modes of action, including as a contact toxicant, a fumigant, an ovicidal toxin, an oviposition deterrent, a repellent, and an attractant. In this review, we summarize various modes of action of methyl benzoate and its toxicity or control potential against various kinds of arthropods, including agricultural pests and their natural enemies, and pollinators. We conclude that methyl benzoate is a very promising candidate for use in integrated pest management under either greenhouse or field conditions. Full article

(This article belongs to the Special Issue Sustainable Pest Management in Agriculture)

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13 pages, 609 KiB

Open AccessEditor’s ChoiceArticle

Chitosan as an Adjuvant to Improve Isopyrazam Azoxystrobin against Leaf Spot Disease of Kiwifruit and Enhance Its Photosynthesis, Quality, and Amino Acids

by Qiuping Wang, Haitao Li, Yang Lei, Yue Su and Youhua Long

Agriculture 2022, 12(3), 373; https://doi.org/10.3390/agriculture12030373 - 7 Mar 2022

Cited by 14 | Viewed by 2341

Abstract

Leaf spot disease caused by Lasiodiplodia theobromae is one of the most serious fungal diseases of kiwifruit production. In this work, the co-application of isopyrazam·azoxystrobin and chitosan against leaf spot disease in kiwifruit and its effects on disease resistance, photosynthesis, yield, quality, and [...] Read more.

Leaf spot disease caused by Lasiodiplodia theobromae is one of the most serious fungal diseases of kiwifruit production. In this work, the co-application of isopyrazam·azoxystrobin and chitosan against leaf spot disease in kiwifruit and its effects on disease resistance, photosynthesis, yield, quality, and amino acids of kiwifruit were investigated. The results show that isopyrazam·azoxystrobin exhibited a superior bioactivity against L. theobromae with an EC₅₀ value of 0.1826 mg kg⁻¹. The foliar application of chitosan could effectively enhance isopyrazam·azoxystrobin against leaf spot disease with a field control efficacy of 86.83% by spraying 29% isopyrazam·azoxystrobin suspension concentrate (SC) 1500 time + chitosan 100-time liquid, which was significantly (p < 0.05) higher than 78.70% of 29% isopyrazam·azoxystrobin SC 1000-time liquid. The co-application of isopyrazam·azoxystrobin and chitosan effectively enhanced soluble protein, resistance enzymes’ activity in kiwifruit leaves, and reduced their malonaldehyde (MDA), as well as reliably improved their photosynthetic characteristics. Simultaneously, their co-application was more effective in promoting growth, quality, and amino acids of kiwifruit fruits compared to isopyrazam·azoxystrobin or chitosan alone. This study highlights that the co-application of isopyrazam·azoxystrobin and chitosan can be used as a green, safe, and efficient approach for controlling leaf spot disease of kiwifruit and reducing the application of chemical fungicides. Full article

(This article belongs to the Special Issue Plant Protection and Biostimulation by Natural Compounds and Beneficial Microorganisms)

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18 pages, 2833 KiB

Open AccessEditor’s ChoiceArticle

The Influence of Country Risks on the International Agricultural Trade Patterns Based on Network Analysis and Panel Data Method

by Qingru Sun, Meiyi Hou, Shuaiwei Shi, Liwei Cui and Zenglei Xi

Agriculture 2022, 12(3), 361; https://doi.org/10.3390/agriculture12030361 - 3 Mar 2022

Cited by 13 | Viewed by 3060

Abstract

The pattern of international agricultural trade is undergoing profound changes. The influence of country risks on the international agricultural trade pattern is prominent. In this paper, we comprehensively analyze the international agricultural trade patterns and explore the influence of country risks on them. [...] Read more.

The pattern of international agricultural trade is undergoing profound changes. The influence of country risks on the international agricultural trade pattern is prominent. In this paper, we comprehensively analyze the international agricultural trade patterns and explore the influence of country risks on them. Specifically, we first construct an international agricultural trade network (IATN) based on complex network theory. Second, we analyze each country’s diversity of import sources and the position of countries in the IATN using the Herfindahl–Hirschman Index (HHI) and network indicators, such as in-degree, out-degree, weighted in-degree, weighted out-degree, and betweenness centrality. Third, this paper explores the influence of different types of country risks, including economic risk and political risk, on international agricultural trade patterns using the panel regression method. The results show that countries played different roles and occupied different positions in the international agricultural trade pattern; notably, the United States occupied a core position, while Japan and Mexico had insufficient diversity in import sources. Moreover, based on the panel regression method, we find that political risks have a positive impact on the agricultural trade pattern, while an unstable economic environment could inhibit the agricultural trade pattern in various countries. This study could provide references for countries to implement agricultural trade policies regarding country risks to ensure stable agricultural trade relations and national food security. Full article

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

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20 pages, 2992 KiB

Open AccessEditor’s ChoiceArticle

A Novel 10-Parameter Motor Efficiency Model Based on I-SA and Its Comparative Application of Energy Utilization Efficiency in Different Driving Modes for Electric Tractor

by Zhun Cheng, Huadong Zhou and Zhixiong Lu

Agriculture 2022, 12(3), 362; https://doi.org/10.3390/agriculture12030362 - 3 Mar 2022

Cited by 18 | Viewed by 2539

Abstract

To build a more accurate motor efficiency model with a strong generalization ability in order to evaluate and improve the efficiency characteristics of electric vehicles, this paper researches motor efficiency modeling based on the bench tests of two motor efficiencies with differently rated [...] Read more.

To build a more accurate motor efficiency model with a strong generalization ability in order to evaluate and improve the efficiency characteristics of electric vehicles, this paper researches motor efficiency modeling based on the bench tests of two motor efficiencies with differently rated powers. This paper compares and analyzes three motor efficiency modeling methods and finds that, when the measured values in motor efficiency tests are insufficient, the bilinear interpolation method and radial basis kernel function neural networks have poor generalization abilities in full working conditions, and the precision of polynomial regression is limited. On this basis, this paper proposes a new modeling method combining correlation analysis, polynomial regression, and an improved simulated annealing (I-SA) algorithm. Using the mean and the standard deviation of the mean absolute percentage error of the 5-fold Cross Validation (CV) of 100 random tests as the evaluation indices of the precision of the motor efficiency model, and based on the motor efficiency models with verified precision, this paper makes a comparative analysis on the full vehicle efficiency of electric tractors of three types of drive in five working conditions. Research results show that the proposed novel method has a high modeling precision of motor efficiency; tractors with a dual motor coupling drive system have optimal economic performance. Full article

(This article belongs to the Special Issue Design and Application of Agricultural Equipment in Tillage System)

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18 pages, 3118 KiB

Open AccessEditor’s ChoiceArticle

Influence of Climate Variability and Soil Fertility on the Forage Quality and Productivity in Azorean Pastures

by Catarina D. Melo, Cristiana S. A. M. Maduro Dias, Sophie Wallon, Alfredo E. S. Borba, João Madruga, Paulo A. V. Borges, Maria T. Ferreira and Rui B. Elias

Agriculture 2022, 12(3), 358; https://doi.org/10.3390/agriculture12030358 - 2 Mar 2022

Cited by 16 | Viewed by 3109

Abstract

This work aimed to determine and compare the effect of elevation and season on the productivity and the nutritive value of pastures in the Azores (Terceira Island). Forage was collected and analysed for dry matter (DM), crude protein (CP), neutral detergent fibre (NDF), [...] Read more.

This work aimed to determine and compare the effect of elevation and season on the productivity and the nutritive value of pastures in the Azores (Terceira Island). Forage was collected and analysed for dry matter (DM), crude protein (CP), neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), ether extract (EE), mineral ash (Ash), dry matter digestibility (DMD) and organic matter digestibility (OMD). The net productivity (NP) was higher in the low elevation pasture A (1.80 g m⁻²), lower in pasture B (0.98 g m⁻²) and peaked in the winter in both pastures A (3.57 g m⁻²) and B (2.33 g m⁻²) and during the summer in the high elevation pasture C (2.15 g m⁻²). The soil chemical proprieties varied significantly among the three pastures. The highest soil pH, available P, K, Ca and Mg were recorded in pasture A. Positive correlations were observed between all soil parameters analysed and NP, except for the OM content. The DM, PB and EE changed significantly with elevation, while all nutritive parameters (except CP, EE and Ash) increased significantly along the growth season. Environmental factors influenced the nutritive parameters and productivity, suggesting that climate change might have significant impacts on forage production and quality. Full article

(This article belongs to the Topic Soil Fertility and Plant Nutrition for Sustainable Agriculture)

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22 pages, 4197 KiB

Open AccessEditor’s ChoiceArticle

N₂O Emission and Nitrification/Denitrification Bacterial Communities in Upland Black Soil under Combined Effects of Early and Immediate Moisture

by Lei Wang, Da-Cheng Hao, Sisi Fan, Hongtu Xie, Xuelian Bao, Zhongjun Jia and Lianfeng Wang

Agriculture 2022, 12(3), 330; https://doi.org/10.3390/agriculture12030330 - 25 Feb 2022

Cited by 10 | Viewed by 3394

Abstract

Soil moisture is the major factor influencing microbial properties and nitrous oxide (N₂O) production. Agricultural soils can be probed under wetting, wet/dry alternating, and constant moisture conditions to evaluate the combined effects of early (previous) and immediate (current) moisture on N [...] Read more.

Soil moisture is the major factor influencing microbial properties and nitrous oxide (N₂O) production. Agricultural soils can be probed under wetting, wet/dry alternating, and constant moisture conditions to evaluate the combined effects of early (previous) and immediate (current) moisture on N₂O emission and nitrification/denitrification. In view of the water history of upland black soil, five moisture regimes comprising different antecedent and present water holding capacity (WHC) levels were set up in the microcosm study. The 20% WHC was adopted as the initial legacy moisture, while three immediate water statuses include constant WHC, dry-wet cycle, and incremental moisture. Quantitative PCR and 16S rRNA amplicon sequencing were used to assess the impact of current and previous moisture on the bacterial community composition and abundance of nitrification/denitrification genes (amoA, nirS, and nosZ); the soil physicochemical properties, and N₂O emission were monitored. The N₂O production and nitrifying-denitrifying microbial communities were influenced by the antecedent moisture and pattern of the dry-wet cycle. The nitrifying-denitrifying microbial communities, especially members of β-/γ-Proteobacteria, Bacteroidetes and Gemmatimonadetes, in black soil were important in explaining the variation of N₂O production. The key taxonomic groups in response to the moisture alteration, e.g., Acidobacteria, Sphingobacteriia, Deltaproteobacteria, Methylobacterium, Gemmatimonas and Pseudarthrobacter, etc., were also highlighted. The soil nitrate, ammonium nitrogen, N₂O emission, nitrification/denitrification and mineralization were profoundly impacted by water regimes and showed statistically significant correlation with specific bacterial genera; the nitrite/nitrate reduction to ammonium could be boosted by high moisture. Both nitrifier denitrification and heterotrophic denitrification could be enhanced substantially when the black soil moisture was increased to above 60% WHC. These findings help evaluate the effects of the water mode on the N₂O emission from black soil, as well as the associated impacts on both soil fertility and the global environment. Full article

(This article belongs to the Special Issue Advanced Research of Soil Microbial Functional Diversity)

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16 pages, 1814 KiB

Open AccessEditor’s ChoiceArticle

Data Management and Integration of Low Power Consumption Embedded Devices IoT for Transforming Smart Agriculture into Actionable Knowledge

by El Mehdi Ouafiq, Rachid Saadane and Abdellah Chehri

Agriculture 2022, 12(3), 329; https://doi.org/10.3390/agriculture12030329 - 24 Feb 2022

Cited by 26 | Viewed by 4268

Abstract

Smart agriculture today uses a wide range of wireless communication technologies. Low Power Consumption Embedded Devices (LPCED), such as the Internet of Things (IoT) and Wireless Sensor Networks, make it possible to work over great distances at a reduced cost but with limited [...] Read more.

Smart agriculture today uses a wide range of wireless communication technologies. Low Power Consumption Embedded Devices (LPCED), such as the Internet of Things (IoT) and Wireless Sensor Networks, make it possible to work over great distances at a reduced cost but with limited transferable data volumes. However, data management (DM) in intelligent agriculture is still not well understood due to the fact that there are not enough scientific publications available on this. Though data management (DM) benefits are factual and substantial, many challenges must be addressed in order to fully realize the DM’s potential. The main difficulties are data integration complexities, the lack of skilled personnel and sufficient resources, inadequate infrastructure, and insignificant data warehouse architecture. This work proposes a comprehensive architecture that includes big data technologies, IoT components, and knowledge-based systems. We proposed an AI-based architecture for smart farming. This architecture called, Smart Farming Oriented Big-Data Architecture (SFOBA), is designed to guarantee the system’s durability and the data modeling in order to transform the business needs for smart farming into analytics. Furthermore, the proposed solution is built on a pre-defined big data architecture that includes an abstraction layer of the data lake that handles data quality, following a data migration strategy in order to ensure the data’s insights. Full article

(This article belongs to the Special Issue Applications of Sensor Technology to Agri-Food Systems)

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18 pages, 638 KiB

Open AccessEditor’s ChoiceArticle

Green Finance, Chemical Fertilizer Use and Carbon Emissions from Agricultural Production

by Lili Guo, Shuang Zhao, Yuting Song, Mengqian Tang and Houjian Li

Agriculture 2022, 12(3), 313; https://doi.org/10.3390/agriculture12030313 - 22 Feb 2022

Cited by 50 | Viewed by 5151

Abstract

This study aimed to understand green finance’s impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root [...] Read more.

This study aimed to understand green finance’s impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root and cointegration test), the latest causal test, impulse response, and variance decomposition analysis. Examined the long-term equilibrium relationship between green finance, fertilizer use, and agricultural carbon emissions. The results show: fertilizer consumption and agricultural carbon emissions have a positive correlation. However, green finance can significantly reduce agricultural carbon emissions. The causal test confirmed the bidirectional causal relationship between agricultural carbon emissions and fertilizer use. At the same time, verified one-way causality from green finance to both of them. Interpret the results of impulse response and variance decomposition analysis: among the changes in agricultural carbon emissions, chemical fertilizers contributed 2.45%, green finance contributed 4.34%. In addition, the contribution rate of green finance to chemical fertilizer changes reached 11.37%. Green finance will make a huge contribution to reducing fertilizer use and agricultural carbon emissions within a decade. The research conclusions provide an important scientific basis for China’s provinces (cities) to formulate carbon emission reduction policies. China has initially formed a policy system and market environment to support the development of green finance, in 2020, the “dual carbon” goal was formally proposed. In 2021, the national “14th Five-Year Plan” and the 2035 Vision Goals emphasized the importance of green finance. It plays an important supporting role in carbon emission reduction goals, and green finance has become an important pillar of national strategic goals. Full article

(This article belongs to the Special Issue Agricultural Safety and Health Culture)

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17 pages, 530 KiB

Open AccessEditor’s ChoiceArticle

Impacts of Technology Training Provided by Agricultural Cooperatives on Farmers’ Adoption of Biopesticides in China

by Yuying Liu, Ruiling Shi, Yiting Peng, Wei Wang and Xinhong Fu

Agriculture 2022, 12(3), 316; https://doi.org/10.3390/agriculture12030316 - 22 Feb 2022

Cited by 28 | Viewed by 3588

Abstract

As pesticide abuse becomes increasingly serious worldwide, it is necessary to pay attention to the biopesticide adoption behavior of agricultural producers. It is worth verifying whether agricultural cooperatives, as training organizations sharing the same social network with farmers, can promote the adoption of [...] Read more.

As pesticide abuse becomes increasingly serious worldwide, it is necessary to pay attention to the biopesticide adoption behavior of agricultural producers. It is worth verifying whether agricultural cooperatives, as training organizations sharing the same social network with farmers, can promote the adoption of biopesticides through their technology diffusion function. Therefore, based on survey data of 837 citrus producers in Sichuan Province, China, the IV-probit regression model and a mediation effects model were used to empirically test the impact of technical training on farmers’ adoption of biopesticides in addition to its mechanism, considering the farmers’ perception of technology as the mediation variable. The results show that (a) participation in technical training can significantly enhance the probability of the adoption of biopesticides; (b) farmers’ perceptions of biopesticides’ economic and health benefits play a partial mediating role in the relationship; and (c) technical training has more significant effects on biopesticides adoption behavior for a household with higher-educated household heads, lower household total income, and smaller household size, relative to their counterparts. This study provides evidence for establishing relevant policy to encourage the full adoption of the technical training function of agricultural cooperatives and popularize the use of biopesticides. Full article

(This article belongs to the Special Issue Ecological Restoration and Rural Economic Development)

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17 pages, 2518 KiB

Open AccessEditor’s ChoiceReview

The Role of FAIR Data towards Sustainable Agricultural Performance: A Systematic Literature Review

by Basharat Ali and Peter Dahlhaus

Agriculture 2022, 12(2), 309; https://doi.org/10.3390/agriculture12020309 - 21 Feb 2022

Cited by 20 | Viewed by 4207

Abstract

Feeding a growing global population requires improving agricultural production in the face of multidimensional challenges; and digital agriculture is increasingly seen as a strategy for better decision making. Agriculture and agricultural supply chains are increasingly reliant on data, including its access and provision [...] Read more.

Feeding a growing global population requires improving agricultural production in the face of multidimensional challenges; and digital agriculture is increasingly seen as a strategy for better decision making. Agriculture and agricultural supply chains are increasingly reliant on data, including its access and provision from the farm to the consumer. Far-reaching data provision inevitably needs the adoption of FAIR (Findable, Accessible, Interoperable, and Reusable) that offer data originators and depository custodians with a set of guidelines to safeguard a progressive data availability and reusability. Through a systematic literature review it is apparent that although FAIR data principles can play a key role in achieving sustainable agricultural operational and business performance, there are few published studies on how they have been adopted and used. The investigation examines: (1) how FAIR data assimilate with the sustainability framework; and (2) whether the use of FAIR data by the agriculture industry, has an impact on agricultural performance. The work identifies a social science research gap and suggests a method to guide agriculture practitioners in identifying the specific barriers in making their data FAIR. By troubleshooting the barriers, the value propositions of adopting FAIR data in agriculture can be better understood and addressed. Full article

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

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16 pages, 2420 KiB

Open AccessEditor’s ChoiceArticle

The Changes in Soil Microorganisms and Soil Chemical Properties Affect the Heterogeneity and Stability of Soil Aggregates before and after Grassland Conversion

by Cheng Ren, Kesi Liu, Pengpeng Dou, Jiahuan Li and Kun Wang

Agriculture 2022, 12(2), 307; https://doi.org/10.3390/agriculture12020307 - 21 Feb 2022

Cited by 15 | Viewed by 2978

Abstract

The conversion of grasslands to croplands is common in the agro-pastoral ecotone and brings potential risks to soil health and environmental safety. As the forming unit of soil structure, the status of soil aggregates determines soil health and is affected by multiple factors. [...] Read more.

The conversion of grasslands to croplands is common in the agro-pastoral ecotone and brings potential risks to soil health and environmental safety. As the forming unit of soil structure, the status of soil aggregates determines soil health and is affected by multiple factors. This study investigated the changes in soil aggregate and main related factors in conversion grasslands with different managed years. Grassland conversion ages were selected as experimental treatments, which included unmanaged grassland, 3 years, 10 years, 30 years, and 50 years since grassland conversion. After grassland conversion, the proportion of large macro-aggregates with a particle size of >2 mm in the 0–10 cm soil layer decreased, small macro-aggregates with a particle size of 2–0.25 mm and micro-aggregates with a particle size of 0.25–0.053 mm increased, while aggregates with a particle size of <0.053 mm had no significant change. Soil chemical properties, most microorganisms and the soil aggregate stability indices MWD and GMD decreased at the early stage (<30 years) of the managed grasslands. After about 50 years of cultivation, soil chemical properties and microorganisms returned to equal or higher levels compared to unmanaged grasslands. However, the stability of aggregates (mean weight diameter (MWD) and geometric mean diameter (GMD)) did not recover to the initial state. MWD and GMD were positively correlated with most bacterial factors (total phospholipid fatty acids (PLFAs), bacteria, Gram-positive bacteria, Gram-negative bacteria, actinomycetes and arbuscular mycorrhizal fungi (AMF)) and some soil chemical properties (carbon, nitrogen and polysaccharides). According to the partial least square structural equation model, soil organic carbon, total nitrogen and phosphorus in the 0–10 cm soil layer explained 33.0% of the variance in MWD by influencing microorganisms. These results indicated that the stability of aggregates was directly driven by microorganisms and indirectly affected by soil organic carbon, total nitrogen and phosphorus. Full article

(This article belongs to the Section Agricultural Soils)

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24 pages, 5508 KiB

Open AccessEditor’s ChoiceReview

Variable Rate Seeding in Precision Agriculture: Recent Advances and Future Perspectives

by Egidijus Šarauskis, Marius Kazlauskas, Vilma Naujokienė, Indrė Bručienė, Dainius Steponavičius, Kęstutis Romaneckas and Algirdas Jasinskas

Agriculture 2022, 12(2), 305; https://doi.org/10.3390/agriculture12020305 - 21 Feb 2022

Cited by 18 | Viewed by 8570

Abstract

The main objective of this study was to analyze variable rate seeding (VRS) methods and critically evaluate their suitability and effectiveness for the challenges under field conditions. A search was performed using scientific databases and portals by identifying for analysis and evaluation 92 [...] Read more.

The main objective of this study was to analyze variable rate seeding (VRS) methods and critically evaluate their suitability and effectiveness for the challenges under field conditions. A search was performed using scientific databases and portals by identifying for analysis and evaluation 92 VRS methodologies, their impact and economic benefits depending on the main parameters of the soil and environment. The results of the review identified that VRS could adapt the appropriate seeding rate for each field zone, which was based on site-specific data layers of soil texture, ECa, pH and yield maps. Then, remotely detected images or other data which identify yield-limiting factors were identified. The site-specific sowing method (with a variable sowing rate for each field area) allows the optimization of crop density to obtain the best agronomic and economic results. Various proximal and remote sensor systems, contact and contactless equipment, mapping and VRS modeling technologies are currently used to determine soil and crop variability. VRS depends on the field characteristics’ sowing equipment capabilities, the planned harvest, soil productivity and machine technology interactions with the environment. When forecasting the effective payback of a VRS over the desired period, the farm size should on average be at least 150 ha. In future studies, to achieve the best solutions and optimal methods, it is important to test, evaluate and put into practice the latest methodologies on farms, to perform complex assessments of changes in sensor, soil, plant and environmental parameters. Full article

(This article belongs to the Special Issue Agricultural Structures and Mechanization)

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12 pages, 2824 KiB

Open AccessEditor’s ChoiceArticle

Improved Multi-Plant Disease Recognition Method Using Deep Convolutional Neural Networks in Six Diseases of Apples and Pears

by Yeong Hyeon Gu, Helin Yin, Dong Jin, Ri Zheng and Seong Joon Yoo

Agriculture 2022, 12(2), 300; https://doi.org/10.3390/agriculture12020300 - 21 Feb 2022

Cited by 16 | Viewed by 3187

Abstract

Plant diseases are a major concern in the agricultural sector; accordingly, it is very important to identify them automatically. In this study, we propose an improved deep learning-based multi-plant disease recognition method that combines deep features extracted by deep convolutional neural networks and [...] Read more.

Plant diseases are a major concern in the agricultural sector; accordingly, it is very important to identify them automatically. In this study, we propose an improved deep learning-based multi-plant disease recognition method that combines deep features extracted by deep convolutional neural networks and k-nearest neighbors to output similar disease images via query image. Powerful, deep features were leveraged by applying fine-tuning, an existing method. We used 14,304 in-field images with six diseases occurring in apples and pears. As a result of the experiment, the proposed method had a 14.98% higher average similarity accuracy than the baseline method. Furthermore, the deep feature dimensions were reduced, and the image processing time was shorter (0.071–0.077 s) using the proposed 128-sized deep feature-based model, which processes images faster, even for large-scale datasets. These results confirm that the proposed deep learning-based multi-plant disease recognition method improves both the accuracy and speed when compared to the baseline method. Full article

(This article belongs to the Section Digital Agriculture)

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16 pages, 1108 KiB

Open AccessEditor’s ChoiceReview

Recent Advances in Probiotic Application in Animal Health and Nutrition: A Review

by Sarayu Bhogoju and Samuel Nahashon

Agriculture 2022, 12(2), 304; https://doi.org/10.3390/agriculture12020304 - 21 Feb 2022

Cited by 30 | Viewed by 9796

Abstract

Biotechnological advances in animal health and nutrition continue to play a significant role in the improvement of animal health, growth, and production performance. These biotechnological advancements, especially the use of direct-fed microbials, also termed probiotics, those genetically modified and otherwise, have minimized many [...] Read more.

Biotechnological advances in animal health and nutrition continue to play a significant role in the improvement of animal health, growth, and production performance. These biotechnological advancements, especially the use of direct-fed microbials, also termed probiotics, those genetically modified and otherwise, have minimized many challenges facing livestock production around the world. Such advancements result in healthy animals and animal products, such as meat, for a growing population worldwide. Increasing demand for productivity, healthy animals, and consumer food safety concerns, especially those emanating from excessive use of antibiotics or growth promoters, are a driving force for investing in safer alternatives, such as probiotics. The advent of vastly diverse pathogens and bacterial organisms, some of which have acquired antimicrobial resistance due to therapeutic use of these antibiotics, has had a negative impact on the animal and food industries. Probiotics have been chosen as substitutes to counter this excessive use of antibiotics and antibiotic resistance. Over the last decade, probiotics have gained recognition, increased in importance, and stimulated growing interest in the animal health and nutrition industry. Probiotics are considered to be favorable live microorganisms by the host organism by maintaining microbial homeostasis and healthy gut, and can be a viable alternative to antibiotics in addition to providing other growth-promoting properties. Even though various studies describe the modes of action of probiotics, more research is needed to illuminate the exact mechanism of action of probiotics and how they benefit the host. This review describes the importance of probiotics in animal health, nutrition, and in growth and production performance. It also provides a thorough review of recent advances in probiotics research and application in animal health and nutrition and future directions on probiotic research to enhance animal performance. Full article

(This article belongs to the Special Issue Improvement and Innovation in the Nutritional Quality and Technologies of Animal Feed)

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16 pages, 605 KiB

Open AccessEditor’s ChoicePerspective

Digital Technology-and-Services-Driven Sustainable Transformation of Agriculture: Cases of China and the EU

by Tianyu Qin, Lijun Wang, Yanxin Zhou, Liyue Guo, Gaoming Jiang and Lei Zhang

Agriculture 2022, 12(2), 297; https://doi.org/10.3390/agriculture12020297 - 18 Feb 2022

Cited by 34 | Viewed by 6569

Abstract

China’s sustainable development goals and carbon neutrality targets cannot be achieved without revolutionary transitions of the agricultural sector. The rapid development of digital technologies is believed to play a huge role in this revolution. The ongoing prevention and control of COVID-19 has greatly [...] Read more.

China’s sustainable development goals and carbon neutrality targets cannot be achieved without revolutionary transitions of the agricultural sector. The rapid development of digital technologies is believed to play a huge role in this revolution. The ongoing prevention and control of COVID-19 has greatly boosted the penetration of digital technology services in all areas of society, and sustainable transformation driven by digital technologies and services is rapidly becoming an area of innovation and research. Studies have shown that the rapid advancement of digitalization is also accompanied by a series of new governance challenges and problems: (1) unclear strategic orientation and inadequate policy and regulatory responses; (2) various stakeholders have not formed a sustainable community of interest; (3) information explosion is accompanied by information fragmentation and digital divide between countries and populations within countries. Meanwhile, current research has focused more on the role of digital services in urban governance and industrial development and lacks systematic research on its role in sustainable agricultural and rural development. To address the realities faced by different stakeholders in the process of digital transformation of agriculture, this paper aims to propose an inclusive analytical framework based on the meta-governance theory to identify and analyze the demand, supply, actor networks, and incentives in the digital technology-and-services-driven sustainable agricultural transformation, starting from the goals and connotations of sustainable agricultural and rural transformation and the interactions among different stakeholders in governing information flows. This analytical framework is further applied to analyze the cases of China and the EU. Although China and the EU represent different development phases and policy contexts, the framework is valid for capturing the characteristics of information flows and actor networks along the flows. It is concluded that a common information platform based on the stakeholder network would benefit all stakeholders, help reach common framing of issues, and maintain a dynamic exchange of information. Depending on the country context, different types of stakeholders may play different roles in creating, supervising, and maintaining such platforms. Digital infrastructures/products as hardware and farmers digital capacity as ‘software’ are the two wings for digital sustainable transformation. Innovative incentives from different countries may inspire each other. In any case, farmers’ actual farming behavior changes should be an important criterion for evaluating the effects and effectiveness of digital transition governance. Full article

(This article belongs to the Topic New Trends in Agri-Food Sector: Environmental, Economic and Social Perspectives)

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12 pages, 1355 KiB

Open AccessEditor’s ChoiceArticle

Benchmarking Machine Learning Approaches to Evaluate the Cultivar Differentiation of Plum (Prunus domestica L.) Kernels

by Ewa Ropelewska, Xiang Cai, Zhan Zhang, Kadir Sabanci and Muhammet Fatih Aslan

Agriculture 2022, 12(2), 285; https://doi.org/10.3390/agriculture12020285 - 17 Feb 2022

Cited by 13 | Viewed by 1942

Abstract

Plum fruit and kernels offer bioactive material for industrial production. The promising procedure for distinguishing plum kernel cultivars used in this study comprised two stages: image analysis to compute the texture parameters of plum kernels belonging to three cultivars ‘Emper’, ‘Kalipso’, and ‘Polinka’, [...] Read more.

Plum fruit and kernels offer bioactive material for industrial production. The promising procedure for distinguishing plum kernel cultivars used in this study comprised two stages: image analysis to compute the texture parameters of plum kernels belonging to three cultivars ‘Emper’, ‘Kalipso’, and ‘Polinka’, and discriminant analysis using machine learning algorithms to classify plum kernel cultivars based on selected textures with the highest discriminative power. The discriminative models built separately for sets of textures selected from all color channels L, a, b, R, G, B, U, V, S, X, Y, Z, color space Lab and color channel b using the KStar (Lazy), PART (Rules), and LMT (Trees) classifiers provided the highest average accuracies reaching 98% in the case of the color space Lab and the KStar classifier. In this case, individual cultivars were discriminated with the accuracies of 97% for ‘Emper’ and ‘Kalipso’ to 99% for ‘Polinka’. The values of other performance metrics were also satisfactory, higher than 0.95. The ROC curves were quite smooth and steady with the most satisfactory curve for the ‘Kalipso’ kernels. The present study sheds light on an objective, non-destructive, and inexpensive procedure for cultivar discrimination of plum kernels. Full article

(This article belongs to the Section Digital Agriculture)

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14 pages, 2452 KiB

Open AccessEditor’s ChoiceArticle

Barriers to the Development of Agricultural Mechanization in the North and Northeast China Plains: A Farmer Survey

by Yuewen Huo, Songlin Ye, Zhou Wu, Fusuo Zhang and Guohua Mi

Agriculture 2022, 12(2), 287; https://doi.org/10.3390/agriculture12020287 - 17 Feb 2022

Cited by 13 | Viewed by 12833

Abstract

Agricultural mechanization is essential to increase farmers’ income in modern agriculture. However, the use of machinery for crop production in China is quite inefficient. To understand the obstacles limiting farmers’ use of machinery, we conducted face-to-face interview surveys with 1023 farmers (including cooperative [...] Read more.

Agricultural mechanization is essential to increase farmers’ income in modern agriculture. However, the use of machinery for crop production in China is quite inefficient. To understand the obstacles limiting farmers’ use of machinery, we conducted face-to-face interview surveys with 1023 farmers (including cooperative directors, machine operators, and farmers without machines) in two major cereal-producing regions with large differences in farming scale: the North China Plain (2.7 ha per capita) and the Northeast China Plain (12.8 ha per capita). The results revealed that farmers in both regions had strong will to use machines. The obstacle preventing farmers from buying machines was the lack of machinery training in the Northeast China Plain and land fragmentation in the North China Plain. Among different farmer groups, land fragmentation was the main barrier for cooperative directors. Farmers without machines thought that there was lack of machinery training and that the cost of machinery purchase was high. Machine operators believed that machine maintenance was too expensive. The income and age also had an effect on the different groups of farmer. It is concluded that, to improve mechanization efficiency and stimulate farmers’ intention to use machinery, the government should make policies to encourage the merge of fragmented farmlands, provide targeted subsidies for agricultural machinery, and organize machinery training in an efficient way. Full article

(This article belongs to the Topic Grand Challenges of Advanced Technologies in Sustainable Agriculture 4.0: Future Farming, Harvesting and Preservation)

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24 pages, 4366 KiB

Open AccessEditor’s ChoiceArticle

Measurement and Calibration of the Discrete Element Parameters of Coated Delinted Cotton Seeds

by Mengjie Hu, Junfang Xia, Yong Zhou, Chengming Luo, Mingkuan Zhou and Zhengyuan Liu

Agriculture 2022, 12(2), 286; https://doi.org/10.3390/agriculture12020286 - 17 Feb 2022

Cited by 13 | Viewed by 2546

Abstract

To simulate the interactions between a pneumatic cotton precision seed-metering device and coated delinted cotton seeds accurately, physical and simulation experiments based on a rotating drum apparatus were combined to calibrate the discrete element simulation parameters of E`kangmian-10 cotton seeds. Firstly, the contact [...] Read more.

To simulate the interactions between a pneumatic cotton precision seed-metering device and coated delinted cotton seeds accurately, physical and simulation experiments based on a rotating drum apparatus were combined to calibrate the discrete element simulation parameters of E`kangmian-10 cotton seeds. Firstly, the contact parameters and the dynamic repose angle of the cotton seeds were measured through physical tests. Based on the particle size requirement of the Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) coupling simulation and the reverse engineering technology, the cotton seed discrete element bonded-particle model (BPM) was established. Secondly, taking the contact parameters as calibration objects and the simulated dynamic repose angle as the evaluation index, a Plackett–Burman (PB) test was designed for significance screening. The results of the screening test showed that the static friction coefficient of cotton seed–tough photosensitive resin, the impact recovery coefficient of cotton seed–cotton seed, and the static friction coefficient of cotton seed–cotton seed had a highly significant effect on the simulated dynamic repose angle. Next, a Box–Behnken Design (BBD) test was adopted to establish the quadratic regression model between significant parameters and the simulated dynamic repose angle, and then the multi-factor optimization solution was carried out to obtain the optimal combination of parameters: the static friction coefficient of cotton seed–tough photosensitive resin and the impact recovery coefficient and static friction coefficient of cotton seed–cotton seed were 0.33, 0.06 and 0.10, respectively. Lastly, verification tests on the rotating drum apparatus and the seed-metering device were performed, and their relative errors were less than 2%, which indicated that the discrete element models and the contact parameters of the coated delinted cotton seeds were reliable. This study provides a reference for the selection of the discrete element parameters of coated delinted cotton seeds for DEM-CFD coupling simulation and the optimal design of precision seed-metering device for cotton. Full article

(This article belongs to the Section Agricultural Technology)

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27 pages, 1399 KiB

Open AccessEditor’s ChoiceReview

Antimicrobial Use and Resistance in Plant Agriculture: A One Health Perspective

by Sally A. Miller, Jorge Pinto Ferreira and Jeffrey T. LeJeune

Agriculture 2022, 12(2), 289; https://doi.org/10.3390/agriculture12020289 - 17 Feb 2022

Cited by 58 | Viewed by 16567

Abstract

Bactericides, fungicides, and other pesticides play an important role in the management of plant diseases. However, their use can result in residues on plants and in the environment, with potentially detrimental consequences. The use of streptomycin, oxytetracycline, copper-based products, and some fungicides is [...] Read more.

Bactericides, fungicides, and other pesticides play an important role in the management of plant diseases. However, their use can result in residues on plants and in the environment, with potentially detrimental consequences. The use of streptomycin, oxytetracycline, copper-based products, and some fungicides is correlated with increased resistance among plant pathogens to these agents. Likewise, the recent rise in the incidence of environmental triazole fungicide-resistant Aspergillus fumigatus, the cause of aspergillosis in humans, has caused concern, particularly in Europe. Through horizontal gene transfer, genes can be exchanged among a variety of bacteria in the plant production environment, including phytopathogens, soil bacteria, and zoonotic bacteria that are occasionally present in that environment and in the food chain. Through mechanisms of horizontal gene transfer, co-resistance, cross-resistance, and gene up-regulation, resistance to one compound may confer resistance and multi-drug resistance to other similar, or even very dissimilar, compounds. Given the global rise in antimicrobial-resistant (AMR) organisms, and their effects on plant, animal, and human health, the prudent use of pesticides is required to maintain their effectiveness for food security and sustainable production, and to minimize the emergence and transmission of AMR organisms from horticultural sources. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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15 pages, 4118 KiB

Open AccessEditor’s ChoiceArticle

Efficacy of Bacillus subtilis XZ18-3 as a Biocontrol Agent against Rhizoctonia cerealis on Wheat

by Yanjie Yi, Pengyu Luan, Shifei Liu, Youtian Shan, Zhipeng Hou, Shuyun Zhao, Shao Jia and Ruifang Li

Agriculture 2022, 12(2), 258; https://doi.org/10.3390/agriculture12020258 - 11 Feb 2022

Cited by 20 | Viewed by 4212

Abstract

Rhizoctonia cerealis is a major fungal pathogen of wheat that causes great yield losses in all wheat-growing regions of the world. The biocontrol agent Bacillus subtilis XZ18-3 was investigated for inhibiting R. cerealis growth in wheat. The results of the mycelial growth test [...] Read more.

Rhizoctonia cerealis is a major fungal pathogen of wheat that causes great yield losses in all wheat-growing regions of the world. The biocontrol agent Bacillus subtilis XZ18-3 was investigated for inhibiting R. cerealis growth in wheat. The results of the mycelial growth test showed that the sterile filtrate of B. subtilis XZ18-3 could significantly inhibit the mycelial growth of R. cerealis and cause swelling and rupture of the mycelium. Observation by transmission electron microscopy indicated that the sterile filtrate could penetrate the cellular membrane of Rhizoctoniacerealis, resulting in organelle destruction. The effect of the sterile filtrates on the pathogen cells, shown through fluorescent microscopy using different stains, revealed the mechanism by which the sterile filtrate caused DNA fragmentation, accumulation of ROS and changes in cell membrane permeability. To reach a better treatment of the soil-borne fungi, the components of a wettable powder were screened and an optimised formula determined (30.0% kaolin, 4.0% polyvinyl alcohol, 8.0% Tween-80, 2.0% polyethylene glycol and 100% fermentation broth). A quality index analysis revealed that the wetting powder reached acceptable biological pesticide standards. Pot control experiments showed that the wettable powder of B. subtilis XZ18-3 effectively controlled the pathogens with an efficacy of 88.28%. This study has provided the potential biocontrol agents (BCAs) for wheat sharp eyespot disease. Full article

(This article belongs to the Special Issue Biological Control Strategies for Fungal Plant Pathogens)

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18 pages, 2569 KiB

Open AccessEditor’s ChoiceArticle

Forecasting Agricultural Commodity Prices Using Dual Input Attention LSTM

by Yeong Hyeon Gu, Dong Jin, Helin Yin, Ri Zheng, Xianghua Piao and Seong Joon Yoo

Agriculture 2022, 12(2), 256; https://doi.org/10.3390/agriculture12020256 - 10 Feb 2022

Cited by 24 | Viewed by 5740

Abstract

Fluctuations in agricultural commodity prices affect the supply and demand of agricultural commodities and have a significant impact on consumers. Accurate prediction of agricultural commodity prices would facilitate the reduction of risk caused by price fluctuations. This paper proposes a model called the [...] Read more.

Fluctuations in agricultural commodity prices affect the supply and demand of agricultural commodities and have a significant impact on consumers. Accurate prediction of agricultural commodity prices would facilitate the reduction of risk caused by price fluctuations. This paper proposes a model called the dual input attention long short-term memory (DIA-LSTM) for the efficient prediction of agricultural commodity prices. DIA-LSTM is trained using various variables that affect the price of agricultural commodities, such as meteorological data, and trading volume data, and can identify the feature correlation and temporal relationships of multivariate time series input data. Further, whereas conventional models predominantly focus on the static main production area (which is selected for each agricultural commodity beforehand based on statistical data), DIA-LSTM utilizes the dynamic main production area (which is selected based on the production of agricultural commodities in each region). To evaluate DIA-LSTM, it was applied to the monthly price prediction of cabbage and radish in the South Korean market. Using meteorological information for the dynamic main production area, it achieved 2.8% to 5.5% lower mean absolute percentage error (MAPE) than that of the conventional model that uses meteorological information for the static main production area. Furthermore, it achieved 1.41% to 4.26% lower MAPE than that of benchmark models. Thus, it provides a new idea for agricultural commodity price forecasting and has the potential to stabilize the supply and demand of agricultural products. Full article

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

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21 pages, 3554 KiB

Open AccessEditor’s ChoiceArticle

A Novel Object Detection Model Based on Faster R-CNN for Spodoptera frugiperda According to Feeding Trace of Corn Leaves

by Lei Du, Yaqin Sun, Shuo Chen, Jiedong Feng, Yindi Zhao, Zhigang Yan, Xuewei Zhang and Yuchen Bian

Agriculture 2022, 12(2), 248; https://doi.org/10.3390/agriculture12020248 - 9 Feb 2022

Cited by 22 | Viewed by 3164

Abstract

The conventional method for crop insect detection based on visual judgment of the field is time-consuming, laborious, subjective, and error prone. The early detection and accurate localization of agricultural insect pests can significantly improve the effectiveness of pest control as well as reduce [...] Read more.

The conventional method for crop insect detection based on visual judgment of the field is time-consuming, laborious, subjective, and error prone. The early detection and accurate localization of agricultural insect pests can significantly improve the effectiveness of pest control as well as reduce the costs, which has become an urgent demand for crop production. Maize Spodoptera frugiperda is a migratory agricultural pest that has severely decreased the yield of maize, rice, and other kinds of crops worldwide. To monitor the occurrences of maize Spodoptera frugiperda in a timely manner, an end-to-end Spodoptera frugiperda detection model termed the Pest Region-CNN (Pest R-CNN) was proposed based on the Faster Region-CNN (Faster R-CNN) model. Pest R-CNN was carried out according to the feeding traces of maize leaves by Spodoptera frugiperda. The proposed model was trained and validated using high-spatial-resolution red–green–blue (RGB) ortho-images acquired by an unmanned aerial vehicle (UAV). On the basis of the severity of feeding, the degree of Spodoptera frugiperda invasion severity was classified into the four classes of juvenile, minor, moderate, and severe. The degree of severity and specific feed location of S. frugiperda infestation can be determined and depicted in the frame forms using the proposed model. A mean average precision (mAP) of 43.6% was achieved by the proposed model on the test dataset, showing the great potential of deep learning object detection in pest monitoring. Compared with the Faster R-CNN and YOLOv5 model, the detection accuracy of the proposed model increased by 12% and 19%, respectively. Further ablation studies showed the effectives of channel and spatial attention, group convolution, deformable convolution, and the multi-scale aggregation strategy in the aspect of improving the accuracy of detection. The design methods of the object detection architecture could provide reference for other research. This is the first step in applying deep-learning object detection to S. frugiperda feeding trace, enabling the application of high-spatial-resolution RGB images obtained by UAVs to S. frugiperda-infested object detection. The proposed model will be beneficial with respect to S. frugiperda pest stress monitoring to realize precision pest control. Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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15 pages, 3264 KiB

Open AccessEditor’s ChoiceArticle

Experimental Investigation on the Impact of Drying–Wetting Cycles on the Shrink–Swell Behavior of Clay Loam in Farmland

by Wei Qi, Ce Wang, Zhanyu Zhang, Mingyi Huang and Jiahui Xu

Agriculture 2022, 12(2), 245; https://doi.org/10.3390/agriculture12020245 - 8 Feb 2022

Cited by 13 | Viewed by 2122

Abstract

Soil shrink–swell behavior is a common phenomenon in farmland, which usually alters the process of water and solute migration in soil. In this paper, we report on a phenomenological investigation aimed at exploring the impact of drying–wetting cycles on the shrink–swell behavior of [...] Read more.

Soil shrink–swell behavior is a common phenomenon in farmland, which usually alters the process of water and solute migration in soil. In this paper, we report on a phenomenological investigation aimed at exploring the impact of drying–wetting cycles on the shrink–swell behavior of soil in farmland. Samples were prepared using clay loam collected from farmland and subjected to four drying–wetting cycles. The vertical deformation of soil was measured by a vernier caliper, and the horizontal deformation was captured by a digital camera and then calculated via an image processing technique. The results showed that the height, equivalent diameter, volume and shrinkage-swelling potential of the soil decreased with the repeated cycles. Irreversible deformation (shrinkage accumulation) was observed during cycles, suggesting that soil cracks might form owing to previous drying rather than current drying. The vertical shrinkage process consisted of two stages: a declining stage and a residual stage, while the horizontal shrinkage process had one more stage, a constant stage at the initial time of drying. The VG-Peng model fit the soil shrinkage curves very well, and all shrinkage curves had four complete shrinkage zones. Drying–wetting cycles had a substantial impact on the soil shrinkage curves, causing significant changes in the distribution of void ratio and moisture ratio in the four zones. However, the impact weakened as the number of cycles increased because the soil structure became more stable. Vertical shrinkage dominated soil deformation at the early stage of drying owing to the effect of gravity, while nearly isotropic shrinkage occurred after entering residual shrinkage. Our study revealed the irreversible deformation and deformation anisotropy of clay loam collected from farmland during drying–wetting cycles and analyzed the shrink–swell behavior during cycles from both macroscopic and microscopic points of view. The results are expected to improve the understanding of the shrink–swell behavior of clay loam and the development of soil desiccation cracks, which will be benefit research on water and solute migration in farmland. Full article

(This article belongs to the Section Agricultural Soils)

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14 pages, 270 KiB

Open AccessEditor’s ChoiceArticle

Characteristics of Population Quality and Rice Quality of Semi-Waxy japonica Rice Varieties with Different Grain Yields

by Qiuyuan Liu, Shuang Chen, Lei Zhou, Yu Tao, Jinyu Tian, Zhipeng Xing, Haiyan Wei and Hongcheng Zhang

Agriculture 2022, 12(2), 241; https://doi.org/10.3390/agriculture12020241 - 8 Feb 2022

Cited by 10 | Viewed by 1806

Abstract

A primary focus of rice breeding and production is the optimization of yield and quality. Currently, semi-waxy japonica rice is widely planted in the middle and lower reaches of the Yangtze River due to its good eating quality and strong reputation among consumers. [...] Read more.

A primary focus of rice breeding and production is the optimization of yield and quality. Currently, semi-waxy japonica rice is widely planted in the middle and lower reaches of the Yangtze River due to its good eating quality and strong reputation among consumers. However, little information is yet available on grain yield formation and rice quality characteristics of these semi-waxy japonica rice varieties with different grain yields. In this study, three high-yielding (HGY) semi-waxy japonica rice varieties and three low-yielding (LGY) semi waxy japonica rice varieties were compared for population quality and rice quality in 2018 and 2019. The average values of spikelet per panicle, 1000-grain weight, and total spikelet number of the HGY varieties were significantly higher than those of the LGY varieties, while the panicle number and filled grain rate showed the opposite. Compared with the LGY varieties, the HGY varieties had a larger leaf area index at each growth stage, with a larger high efficient leaf area composed of a larger leaf length and width and smaller leaf angles of the top three leaves, as well as a greater single stem-sheath weight, more total dry matter accumulation, and longer growth duration from elongating to maturity. There were significant differences in rice quality between the HGY and LGY varieties. Compared with the LGY varieties, the head milled rice rate of the HGY varieties decreased significantly, and the chalky kernel rate and chalkiness degree increased significantly. Due to the low protein content, high peak viscosity, trough viscosity, and final viscosity and breakdown, as well as low setback, consistence, and pasting temperature of the HGY varieties, their taste values were significantly better than those of the LGY varieties. These results suggest that the HGY varieties could achieve a synergistic improvement of grain yield and eating quality, but the milling quality and appearance quality require further improvement. Full article

(This article belongs to the Section Crop Production)

16 pages, 2949 KiB

Open AccessEditor’s ChoiceArticle

Research on Maize Seed Classification and Recognition Based on Machine Vision and Deep Learning

by Peng Xu, Qian Tan, Yunpeng Zhang, Xiantao Zha, Songmei Yang and Ranbing Yang

Agriculture 2022, 12(2), 232; https://doi.org/10.3390/agriculture12020232 - 6 Feb 2022

Cited by 33 | Viewed by 6030

Abstract

Maize is one of the essential crops for food supply. Accurate sorting of seeds is critical for cultivation and marketing purposes, while the traditional methods of variety identification are time-consuming, inefficient, and easily damaged. This study proposes a rapid classification method for maize [...] Read more.

Maize is one of the essential crops for food supply. Accurate sorting of seeds is critical for cultivation and marketing purposes, while the traditional methods of variety identification are time-consuming, inefficient, and easily damaged. This study proposes a rapid classification method for maize seeds using a combination of machine vision and deep learning. 8080 maize seeds of five varieties were collected, and then the sample images were classified into training and validation sets in the proportion of 8:2, and the data were enhanced. The proposed improved network architecture, namely P-ResNet, was fine-tuned for transfer learning to recognize and categorize maize seeds, and then it compares the performance of the models. The results show that the overall classification accuracy was determined as 97.91, 96.44, 99.70, 97.84, 98.58, 97.13, 96.59, and 98.28% for AlexNet, VGGNet, P-ResNet, GoogLeNet, MobileNet, DenseNet, ShuffleNet, and EfficientNet, respectively. The highest classification accuracy result was obtained with P-ResNet, and the model loss remained at around 0.01. This model obtained the accuracy of classifications for BaoQiu, ShanCu, XinNuo, LiaoGe, and KouXian varieties, which reached 99.74, 99.68, 99.68, 99.61, and 99.80%, respectively. The experimental results demonstrated that the convolutional neural network model proposed enables the effective classification of maize seeds. It can provide a reference for identifying seeds of other crops and be applied to consumer use and the food industry. Full article

(This article belongs to the Special Issue Internet and Computers for Agriculture)

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18 pages, 6193 KiB

Open AccessEditor’s ChoiceArticle

A Lightweight Attention-Based Convolutional Neural Networks for Tomato Leaf Disease Classification

by Anil Bhujel, Na-Eun Kim, Elanchezhian Arulmozhi, Jayanta Kumar Basak and Hyeon-Tae Kim

Agriculture 2022, 12(2), 228; https://doi.org/10.3390/agriculture12020228 - 4 Feb 2022

Cited by 70 | Viewed by 6467

Abstract

Plant diseases pose a significant challenge for food production and safety. Therefore, it is indispensable to correctly identify plant diseases for timely intervention to protect crops from massive losses. The application of computer vision technology in phytopathology has increased exponentially due to automatic [...] Read more.

Plant diseases pose a significant challenge for food production and safety. Therefore, it is indispensable to correctly identify plant diseases for timely intervention to protect crops from massive losses. The application of computer vision technology in phytopathology has increased exponentially due to automatic and accurate disease detection capability. However, a deep convolutional neural network (CNN) requires high computational resources, limiting its portability. In this study, a lightweight convolutional neural network was designed by incorporating different attention modules to improve the performance of the models. The models were trained, validated, and tested using tomato leaf disease datasets split into an 8:1:1 ratio. The efficacy of the various attention modules in plant disease classification was compared in terms of the performance and computational complexity of the models. The performance of the models was evaluated using the standard classification accuracy metrics (precision, recall, and F1 score). The results showed that CNN with attention mechanism improved the interclass precision and recall, thus increasing the overall accuracy (>1.1%). Moreover, the lightweight model significantly reduced network parameters (~16 times) and complexity (~23 times) compared to the standard ResNet50 model. However, amongst the proposed lightweight models, the model with attention mechanism nominally increased the network complexity and parameters compared to the model without attention modules, thereby producing better detection accuracy. Although all the attention modules enhanced the performance of CNN, the convolutional block attention module (CBAM) was the best (average accuracy 99.69%), followed by the self-attention (SA) mechanism (average accuracy 99.34%). Full article

(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)

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18 pages, 1590 KiB

Open AccessEditor’s ChoiceArticle

Biostimulants Improve Plant Growth and Bioactive Compounds of Young Olive Trees under Abiotic Stress Conditions

by Giulia Graziani, Aurora Cirillo, Paola Giannini, Stefano Conti, Christophe El-Nakhel, Youssef Rouphael, Alberto Ritieni and Claudio Di Vaio

Agriculture 2022, 12(2), 227; https://doi.org/10.3390/agriculture12020227 - 4 Feb 2022

Cited by 14 | Viewed by 3083

Abstract

The negative impacts of extreme heat and drought on olive plants have driven the quest for mitigation approaches based on the use of biostimulants, which have proved to be effective in contrasting environmental stresses. The aim of our study was to evaluate the [...] Read more.

The negative impacts of extreme heat and drought on olive plants have driven the quest for mitigation approaches based on the use of biostimulants, which have proved to be effective in contrasting environmental stresses. The aim of our study was to evaluate the effectiveness of six biostimulants in mitigating high temperature and water stress in young olive trees in terms of vegetative and eco-physiological parameters as well as bioactive compound content. Biostimulants based on glycine betaine and macro- and micro-algae effectively protected the plants from abiotic stress by improving their eco-physiological and vegetative parameters. At the end of the growing season, olive plants were experiencing water deficit which had built up through the summer months. At this time, the glycine betaine-treated plants had a three-fold higher stomatal conductance compared with the control, while plants sprayed with the seaweed mix had a relative water content 33% higher than the control. The kaolin treatment resulted in higher total phenolics and antioxidant activities (DPPH, FRAP and ABTS) in water stress conditions and caused an increase of 238.53 and 443.49% in leaves total polyphenols content in 100% and 50% water regime, respectively. This study showed the effectiveness of biostimulants in mitigating the damage from abiotic stress on young olive trees, by improving some vegetative, eco-physiological and leaf nutraceutical parameters. Further studies are needed to test the efficiency of these biostimulants in open field conditions on olive trees in full production. Full article

(This article belongs to the Special Issue Plant Secondary Metabolism as a Response to Single or Multiple Stresses)

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14 pages, 3241 KiB

Open AccessEditor’s ChoiceArticle

Effect of Straw Length, Stubble Height and Rotary Speed on Residue Incorporation by Rotary Tillage in Intensive Rice–Wheat Rotation System

by Gaoming Xu, Yixuan Xie, Md. A. Matin, Ruiyin He and Qishuo Ding

Agriculture 2022, 12(2), 222; https://doi.org/10.3390/agriculture12020222 - 3 Feb 2022

Cited by 12 | Viewed by 2620

Abstract

High-yielding agriculture in an intensive rice–wheat rotation system leads to plenty of residues left in the field after harvest, which is detrimental to seeding operation, seed germination, and early plant growth. Some residue thus needs to be incorporated into the soil. Providing the [...] Read more.

High-yielding agriculture in an intensive rice–wheat rotation system leads to plenty of residues left in the field after harvest, which is detrimental to seeding operation, seed germination, and early plant growth. Some residue thus needs to be incorporated into the soil. Providing the relationship between tillage operations and residue incorporation and establishing a mathematical model play important roles in residue management and the design of tillage machinery. In order to obtain detailed data on the interaction between residue incorporation and tillage operations, a multifunctional field-testing bench with precise parameter control was developed to assess residue incorporation characteristics of rotary tillage, and we investigated the effects of straw length, stubble height and rotary speed on residue incorporation. Three experimental factors affecting residue incorporation performance were studied, i.e., six lengths of straw (30–150 mm), four heights of stubble (50–200 mm), and three rotary speeds (240–320 rpm). Chopped straw and stubble with certain sizes were prepared for the test, and we measured the burying rate and distribution uniformity of residue after rotary tillage. The results indicated that straw length, stubble height, and rotary speed all impact residue incorporation quality. The burying rate and distribution uniformity of residue decreased with the increase in straw length and stubble height; a lower rotary speed parameter buried less residue and distributed it with worse uniformity than a higher one. It is suggested that farmers determine the straw length and stubble height at the stage of harvest according to the required burying rate and distribution uniformity of residue. Full article

(This article belongs to the Topic Soil Fertility and Plant Nutrition for Sustainable Agriculture)

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14 pages, 1465 KiB

Open AccessEditor’s ChoiceReview

Exploring the Adaptive Responses of Plants to Abiotic Stresses Using Transcriptome Data

by Muhammad Haseeb Javaid, Ali Raza Khan, Abdul Salam, Asifa Neelam, Wardah Azhar, Zaid Ulhassan and Yinbo Gan

Agriculture 2022, 12(2), 211; https://doi.org/10.3390/agriculture12020211 - 1 Feb 2022

Cited by 21 | Viewed by 3432

Abstract

In recent decades, global climate change and heavy metal stress have severely affected plant growth and biomass, which has led to a serious threat to food safety and human health. Anthropogenic activities, the rapid pace of urbanization, and the use of modern agricultural [...] Read more.

In recent decades, global climate change and heavy metal stress have severely affected plant growth and biomass, which has led to a serious threat to food safety and human health. Anthropogenic activities, the rapid pace of urbanization, and the use of modern agricultural technologies have further aggravated environmental conditions, resulting in limited crop growth and productivity. This review highlights the various adaptive transcriptomic responses of plants to tolerate detrimental environmental conditions, such as drought, salinity, and heavy metal contamination. These stresses hinder plant growth and development by disrupting their physiological and biochemical processes by inducing oxidative stress, nutritional imbalance, and osmotic disturbance, and by deteriorating their photosynthetic machinery. Plants have developed different strategies to safeguard themselves against the toxic effects of these environmental stresses. They stimulate their secondary messenger to activate cell signaling, and they trigger other numerous transcriptomic responses associated with plant defense mechanisms. Therefore, the recent advances in biological sciences, such as transcriptomics, metabolomics, and proteomics, have assisted our understanding of the stress-tolerant strategies adopted by plants, which could be further utilized to breed tolerant species. This review summarizes the stress-tolerant strategies of crops by covering the role of transcriptional factors in plants. Full article

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20 pages, 2643 KiB

Open AccessEditor’s ChoiceReview

A Review of the Category, Mechanism, and Controlling Methods of Chemical Clogging in Drip Irrigation System

by Kaili Shi, Tiangang Lu, Wengang Zheng, Xin Zhang and Lili Zhangzhong

Agriculture 2022, 12(2), 202; https://doi.org/10.3390/agriculture12020202 - 31 Jan 2022

Cited by 20 | Viewed by 4799

Abstract

Drip irrigation is an important way to alleviate the global water shortage. However, the emitter-clogging issue of drip irrigation directly affects irrigation uniformity and operation efficiency, even disabling the whole system and reducing crop production. Currently, with the widespread use of saline water [...] Read more.

Drip irrigation is an important way to alleviate the global water shortage. However, the emitter-clogging issue of drip irrigation directly affects irrigation uniformity and operation efficiency, even disabling the whole system and reducing crop production. Currently, with the widespread use of saline water and large-scale utilization of fertigation, the issue with the chemical clogging of emitters has become more prominent. The poor uniformity of irrigation and fertilization distribution caused by emitter clogging results in salt damage and fertilizer loss due to the complex clogging mechanism. However, no extensive information on chemical clogging is available. Herein, we surveyed the latest research on chemical clogging caused by saline water irrigation and fertigation in drip irrigation systems and described the clogging mechanisms of the emitter by analyzing the key factors, clogging rules, and substances. We also present a framework of the control technologies for clogging based on physical, chemical, and biological methods. Finally, we present the current challenges of fertigation with saline water and technical trends of emitter clogging in the drip irrigation system. To conclude, the efficient integration of these three methods is critical to prevent and eliminate chemical clogging. Full article

(This article belongs to the Special Issue Management and Strategies for Improving the Use of Saline Water in Agriculture)

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