Agriculture

10 pages, 2156 KiB

Open AccessArticle

Influencing Factors of Cutting Force for Apple Tree Branch Pruning

by Chengjun Li, Hanshi Zhang, Qingchun Wang and Zhongjia Chen

Agriculture 2022, 12(2), 312; https://doi.org/10.3390/agriculture12020312 - 21 Feb 2022

Cited by 14 | Viewed by 3211

Apple, which occupies the first position in the world with regard to its yield, is an important economic crop in China. Pruning of apple trees is still dominated by manual pruning, resulting in high labor costs and low efficiency. Additionally, there are some [...] Read more.

Apple, which occupies the first position in the world with regard to its yield, is an important economic crop in China. Pruning of apple trees is still dominated by manual pruning, resulting in high labor costs and low efficiency. Additionally, there are some limitations with pruning machines. Thus, research regarding the mechanical properties of apple branches is the basis for the designing proper pruning machine. This paper aims to study the effect of the feed rate, cutting line speed, branch diameter, and moisture content on the cutting force. Results revealed that cutting force depended on the feed rate, cutting line speed, and branch diameter. Furthermore, both the cutting line speed and the branch diameter had a significant effect on the cutting force (p < 0.01), while the feed rate had a small effect on the cutting force (p > 0.05). However, the moisture content had no effect on the cutting force, with a difference of cutting force between samples with moisture content of 15% and 50% less than 5%. Based on the experiments performed, an equation relating the feed rate, the cutting line speed, the branch diameter was derived to calculate the cutting force. By verification test, it established that regression equation was valid with error less than 4%. This study explored the mechanical properties of apple branch, and obtained the optimal cutting parameters, which can provide a reference for the design of the pruning machine. Full article

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19 pages, 2955 KiB

Open AccessArticle

Effects of Shallow Groundwater Depth and Nitrogen Application Level on Soil Water and Nitrate Content, Growth and Yield of Winter Wheat

by Yingjun She, Ping Li, Xuebin Qi, Wei Guo, Shafeeq Ur Rahman, Hongfei Lu, Cancan Ma, Zhenjie Du, Jiaxin Cui and Zhijie Liang

Agriculture 2022, 12(2), 311; https://doi.org/10.3390/agriculture12020311 - 21 Feb 2022

Cited by 9 | Viewed by 2869

Abstract

The large amount of nitrogen application on the North China Plain has caused a serious negative impact on the sustainable development of regional agriculture and ecological environmental protection. Our aim was to explore the effects of nitrogen fertilization rate and groundwater depth on [...] Read more.

The large amount of nitrogen application on the North China Plain has caused a serious negative impact on the sustainable development of regional agriculture and ecological environmental protection. Our aim was to explore the effects of nitrogen fertilization rate and groundwater depth on growth attributes, soil-water and soil-fertilizer contents, and the winter wheat yield. Experiments were carried out in micro-lysimeters at groundwater depths of 60, 90, 120, and 150 cm on the basis of 0, 150, 240, and 300 kg/ha nitrogen fertilization rates in the growth season for winter wheat. Results showed that plant height, leaf area index, soil plant analysis development, and yield without nitrogen application increased significantly with increases in groundwater depth. The optimal groundwater depths for growth attributes and yield were 60–120 cm and tended to be shallower with added nitrogen application. Soil moisture was lowered significantly with groundwater depth, adding a nitrogen application reduced soil moisture, and excessive nitrogen input intensified soil drought. Nitrate-N accumulation at the 120–150 cm depths was significantly higher than that at the 60–90 cm depths, and a 300 kg/ha (traditional nitrogen application rate) treatment was 6.7 times greater than that of 150 kg/ha treatment and increased by 74% more than that of the 240 kg/ha treatment at 60–150 cm depth. Compared with the yield of the 300 kg/ha rate, the yield of the 240 kg/ha rate had no significant difference, but the yield increased by 3.90% and 11.09% at the 120 cm and 150 cm depths. The growth attributes and yield of winter wheat were better, and the soil nitrate-N content was lower, when the nitrogen application rate was 240 kg/ha. Therefore, it can be concluded that nitrogen application can be reduced by 20% on the North China Plain. Full article

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

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19 pages, 17733 KiB

Open AccessArticle

Developing an IoT-Enabled Cloud Management Platform for Agricultural Machinery Equipped with Automatic Navigation Systems

by Fan Zhang, Wenyu Zhang, Xiwen Luo, Zhigang Zhang, Yueteng Lu and Ben Wang

Agriculture 2022, 12(2), 310; https://doi.org/10.3390/agriculture12020310 - 21 Feb 2022

Cited by 16 | Viewed by 5376

Abstract

Smart farming uses advanced tools and technologies such as intelligent agricultural machines, high-precision sensors, navigation systems, and sophisticated computer systems to increase the economic benefits of agriculture and reduce the associated human effort. With the increasing demands of individualized farming operations, the internet [...] Read more.

Smart farming uses advanced tools and technologies such as intelligent agricultural machines, high-precision sensors, navigation systems, and sophisticated computer systems to increase the economic benefits of agriculture and reduce the associated human effort. With the increasing demands of individualized farming operations, the internet of things is a crucial technique for acquiring, monitoring, processing, and managing the agricultural resource data of precision agriculture and ecological monitoring domains. Here, an internet of things-based system scheme integrating the most recent technologies for designing a management platform for agricultural machines equipped with automatic navigation systems is proposed. Various agricultural machinery cyber-models and their corresponding sensor nodes were constructed in a pre-production phase. Three key enabling technologies—multi-optimization of agricultural machinery scheduling, development of physical architecture and software, and integration of the controller-area-network with a mobile network—were addressed to support the system scheme. A demonstrative prototype system was developed and a case study was used to validate the feasibility and effectiveness of the proposed approach. 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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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 23 | Viewed by 5101

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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13 pages, 2910 KiB

Open AccessArticle

Dynamic Resistant Starch Accumulation in Contrasting Wheat Genotypes Highlights the Lipid Metabolic Pathway Related to Resistant Starch Synthesis

by Hong-Pan Wang, Hai-Ya Cai, Jing-Huan Zhu, Xia Wei, Shuo Zhang, Gang Liu, Yong-Gang He, Bo Li, Le Xu, Chun-Hai Jiao, Wei Hua and Yan-Hao Xu

Agriculture 2022, 12(2), 308; https://doi.org/10.3390/agriculture12020308 - 21 Feb 2022

Cited by 5 | Viewed by 2723

Abstract

Resistant starch (RS) shows several health benefits. Enhancing the RS content of wheat is of major commercial importance. However, knowledge regarding the RS synthesis mechanism in wheat remains limited. In this study, the dynamic accumulation of RS during the filling process in two [...] Read more.

Resistant starch (RS) shows several health benefits. Enhancing the RS content of wheat is of major commercial importance. However, knowledge regarding the RS synthesis mechanism in wheat remains limited. In this study, the dynamic accumulation of RS during the filling process in two wheat (Triticum aestivum L.) genotypes with contrasting RS contents (H242, high RS content; H189, low RS content) were investigated. The results demonstrate that beyond 25 days after pollination (DAP), the RS content of H189 was relatively stable, but that of H242 continued to increase. Secondary accumulation was observed in the high-RS-content wheat genotype. A comparative transcriptome analysis between H242 and H189 at 20 DAP and 35 DAP showed that the differentially expressed genes were mainly involved in glycerolipid metabolism, glycerophospholipid metabolism and glucuronate interconversions. Furthermore, weighted gene coexpression network analysis suggested that lipid metabolic pathways such as the glycerophospholipid metabolism pathway might be involved in RS synthesis, and lipid-related genes upregulated beyond 25 DAP resulted in RS secondary accumulation. This work provides insight into the characteristics and mechanisms of RS synthesis. Full article

(This article belongs to the Special Issue Molecular Genetics and Functional Genomics for the Breeding of Cereal Crops)

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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 19 | Viewed by 3766

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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14 pages, 2648 KiB

Open AccessArticle

The Carotenoid Cleavage Dioxygenase Gene CCD7-B, at Large, Is Associated with Tillering in Common Wheat

by Wenlong Yang, Ameer Ahmed Mirbahar, Muhammad Shoaib, Xueyuan Lou, Linhe Sun, Jiazhu Sun, Kehui Zhan and Aimin Zhang

Agriculture 2022, 12(2), 306; https://doi.org/10.3390/agriculture12020306 - 21 Feb 2022

Cited by 5 | Viewed by 2695

Abstract

Wheat, an important cereal crop, is responsible for the livelihoods of many people, and a component of national food security. Tillering, which determines plant architecture and spike number, is a critical agronomic trait of wheat. The carotenoid cleavage dioxygenase 7 (CCD7) has an [...] Read more.

Wheat, an important cereal crop, is responsible for the livelihoods of many people, and a component of national food security. Tillering, which determines plant architecture and spike number, is a critical agronomic trait of wheat. The carotenoid cleavage dioxygenase 7 (CCD7) has an important effect on the growth of tillers or lateral branches and lateral roots of plants. In order to study the relationship between CCD7 and tillering in wheat, CCD7-B was isolated from 10 Chinese wheat varieties with different tiller numbers. Subsequently, bioinformatics, allelic variation analysis, and field experiments were performed. Wheat CCD7-B belongs to the retinal pigment epithelial membrane receptor (RPE65) superfamily; it displays the greatest homology with monocot CCD7 proteins. Phylogenetic analysis of wheat CCD7-B proteins indicated division into dicotyledonous and monocotyledonous clades. Allelic variation analysis of CCD7-B via SrgAI enzyme digestion (a marker of cleaved amplified polymorphic sequences) suggested that 262 Chinese wheat micro-core collections and 121 Chinese wheat major cultivars from the Yellow and Huai River Valley winter wheat region can be divided into two groups: CCD7-B1 (C/T/T) and CCD7-B2 (G/C/A). CCD7-B1 showed better allelic variation than did CCD7-B2 for increasing the number of effective tillers of wheat varieties in China. This study provides reference data for the application of CCD7-B alleles to wheat breeding and supports further research regarding the mechanism of tillering in common wheat. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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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 25 | Viewed by 11305

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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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 39 | Viewed by 13168

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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15 pages, 3334 KiB

Open AccessArticle

Climate Resilience and Environmental Sustainability: How to Integrate Dynamic Dimensions of Water Security Modeling

by Syed Abu Shoaib, Muhammad Muhitur Rahman, Faisal I. Shalabi, Ammar Fayez Alshayeb and Ziad Nayef Shatnawi

Agriculture 2022, 12(2), 303; https://doi.org/10.3390/agriculture12020303 - 21 Feb 2022

Cited by 2 | Viewed by 2765

Abstract

Considering hydro-climatic diversity, integrating dynamic dimensions of water security modeling is vital for ensuring environmental sustainability and its associated full range of climate resilience. Improving climate resiliency depends on the attributing uncertainty mechanism. In this study, a conceptual resilience model is presented with [...] Read more.

Considering hydro-climatic diversity, integrating dynamic dimensions of water security modeling is vital for ensuring environmental sustainability and its associated full range of climate resilience. Improving climate resiliency depends on the attributing uncertainty mechanism. In this study, a conceptual resilience model is presented with the consideration of input uncertainty. The impact of input uncertainty is analyzed through a multi-model hydrological framework. A multi-model hydrological framework is attributed to a possible scenario to help apply it in a decision-making process. This study attributes water security modeling with the considerations of sustainability and climate resilience using a high-speed computer and Internet system. Then, a subsequent key point of this investigation is accounting for water security modeling to ensure food security and model development scenarios. In this context, a four-dimensional dynamic space that maps sources, resource availability, infrastructure, and vibrant economic options is essential in ensuring a climate-resilient sustainable domain. This information can be disseminated to farmers using a central decision support system to ensure sustainable food production with the application of a digital system. Full article

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

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22 pages, 3423 KiB

Open AccessFeature PaperArticle

A Digital Advisor Twin for Crop Nitrogen Management

by Fabian Weckesser, Michael Beck, Kurt-Jürgen Hülsbergen and Sebastian Peisl

Agriculture 2022, 12(2), 302; https://doi.org/10.3390/agriculture12020302 - 21 Feb 2022

Cited by 2 | Viewed by 3532

Abstract

Farmers and consultants face an unmanageable amount of diverse knowledge and information for crop management decisions. To determine optimal actions, decision makers require knowledge-based support. In this way, decisions can be improved and heuristics can be replaced over time. The study presents a [...] Read more.

Farmers and consultants face an unmanageable amount of diverse knowledge and information for crop management decisions. To determine optimal actions, decision makers require knowledge-based support. In this way, decisions can be improved and heuristics can be replaced over time. The study presents a digital knowledge base with an integrated decision support system (DSS), using the example of nutrient supply, specifically nitrogen (N), fertilization. Therefore, the requirements of farmers and crop consultants for DSS to inform fertilization decisions for winter wheat (Triticum aestivum L.) were elaborated using surveys, expert interviews, and a prototype test. Semantic knowledge was enriched by expert knowledge and combined in a web application, the Crop Portal. To map regional and personal decision making patterns and experiences, the tacit knowledge on the complex advisory problem of N fertilization is made digitally usable. For this purpose, 16 fuzzy variables were specified and formalized. Individual decision trees and their interactions with an integrative knowledge base were used to multiply the consulting reach of experts. Using three consultants and nine model farms from different soil–climate areas in Germany, the Crop Portal was tested under practical conditions and the perceived pragmatic and hedonic quality of the system was evaluated using a standardized questionnaire. The field test showed that the variation in fertilizer recommendations from the ‘digital advisor twin’ ranged from 5 kg N ha⁻¹ to 16 kg N ha⁻¹ when compared with the decisions of the experts in the field. The study presents the participatory development and evaluation of a rule-based DSS prototype in agricultural practice. Full article

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

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14 pages, 319 KiB

Open AccessArticle

Effect of Sainfoin (Onobrychis viciifolia) Pellets on Rumen Microbiome and Histopathology in Lambs Exposed to Gastrointestinal Nematodes

by Daniel Petrič, Michaela Komáromyová, Dominika Batťányi, Martyna Kozłowska, Weronika Filipiak, Anna Łukomska, Sylwester Ślusarczyk, Malgorzata Szumacher-Strabel, Adam Cieślak, Marián Várady, Svetlana Kišidayová and Zora Váradyová

Agriculture 2022, 12(2), 301; https://doi.org/10.3390/agriculture12020301 - 21 Feb 2022

Cited by 1 | Viewed by 2675

Abstract

Our study analyzed the ruminal fermentation and microbiome, hematological profile, and abomasal histopathology of lambs experimentally infected with a gastrointestinal nematode (GIN) and fed sainfoin pellets (SFPs; 600 g DM/d/animal) for 14 d. Twenty-four lambs infected with Haemonchus contortus were divided into two [...] Read more.

Our study analyzed the ruminal fermentation and microbiome, hematological profile, and abomasal histopathology of lambs experimentally infected with a gastrointestinal nematode (GIN) and fed sainfoin pellets (SFPs; 600 g DM/d/animal) for 14 d. Twenty-four lambs infected with Haemonchus contortus were divided into two separated groups: animals fed meadow hay (control) and animals fed SFPs. The ruminal contents, fermentation parameters, and microbiome in vitro and in vivo were determined using molecular and microscopic techniques. Ruminal contents in the SFP group indicated smaller populations of Archaea (p < 0.001), Methanomicrobiales (p = 0.009), and lower methane concentrations in vitro (p = 0.046) and in vivo (p = 0.030) than the control group. The relative abundance of Butyrivibrio fibrisolvens quantified by real-time PCR was higher in the lambs with the SFP diet (p = 0.05). Haemonchosis affected the number of red blood cells of the lambs (p < 0.001). The lambs in the SFP group had a higher percentage of damaged abomasa glands than did the control group (p = 0.004). The consumption of SFPs by GIN-infected lambs may affect ruminal methanogens and subsequently decrease methane emission without undesirable changes in the ruminal microbiome or the health of the animals. Full article

(This article belongs to the Special Issue Safety and Efficacy of Feed Additives in Animal Production)

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 20 | Viewed by 3797

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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18 pages, 5865 KiB

Open AccessFeature PaperArticle

Effects of Solar Radiation on Dry Matter Distribution and Root Morphology of High Yielding Maize Cultivars

by Xiaoxia Guo, Yunshan Yang, Huifang Liu, Guangzhou Liu, Wanmao Liu, Yonghong Wang, Rulang Zhao, Bo Ming, Ruizhi Xie, Keru Wang, Shaokun Li and Peng Hou

Agriculture 2022, 12(2), 299; https://doi.org/10.3390/agriculture12020299 - 20 Feb 2022

Cited by 7 | Viewed by 5034

Abstract

The root system connects the plant with the soil, which is a key factor in determining the utilization of soil resources and plant growth potential. Solar radiation can change maize shoot and root growth and affect grain formation. In this study, the effects [...] Read more.

The root system connects the plant with the soil, which is a key factor in determining the utilization of soil resources and plant growth potential. Solar radiation can change maize shoot and root growth and affect grain formation. In this study, the effects of different solar radiation conditions on root morphology of three maize cultivars XY335, ZD958 and DH618 and their quantitative relationships were studied by conducting shading experiments. This study was conducted in maize high yield region of Qitai and Yinchuan, China, in 2018 and 2019. The planting densities were 7.5 × 10⁴ (D1) and 12 × 10⁴ (D2) plants ha⁻¹. The shading levels were natural light (CK), shading 15% (S1), 30% (S2) and 50% (S3). The results showed that maize responded to the decreased solar radiation through the increase in ratio of shoot dry weight (SWR) to whole plant dry weight and the decrease in ratio of root dry weight (RWR) to whole plant dry weight. As the solar radiation decreased, the root length density (RLD), root surface area (RSA), average root diameter (ARD) and root length ratio (RLR) decreased, while the specific root length (SRL) increased. With 100 MJ m⁻² decrease in solar radiation, the RWR, RLD, RSA and RLR each decreased by 1.47%, 0.5 mm cm⁻³,0.4 m m⁻² and 0. 19 m g⁻¹, respectively. Among the cultivars, the changes of DH618 were the fastest followed by XY335 and ZD958 but DH618 maintained the largest root system under any solar radiation condition. After the decrease of solar radiation, RWR, RLD and RLR were significantly positively correlated with the yield. This indicated that large root systems were conducive to the rapid response to decreased solar radiation and important for achieving stable and high yield. Maize cultivars with these type of root systems should be recommended to better adapt low solar radiation induced by regional variation or climate change. Full article

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

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14 pages, 1943 KiB

Open AccessArticle

Comparative Transcriptome Analysis of Bt Resistant and Susceptible Strains in Ostrinia furnacalis (Guenée) (Lepidoptera: Crambidae)

by Yaling Lin, Qing Gao, Yueqin Wang, Zhenying Wang, Kanglai He, Suqin Shang and Tiantao Zhang

Agriculture 2022, 12(2), 298; https://doi.org/10.3390/agriculture12020298 - 19 Feb 2022

Cited by 1 | Viewed by 2447

Abstract

The evolution of target pest population resistance to Bt toxins is the most relevant threat to the sustainability of Bt technology, thus it is necessary to clarify insect resistance mechanisms. Firstly, the resistance level of Asian corn borer was determined by bioassay. After [...] Read more.

The evolution of target pest population resistance to Bt toxins is the most relevant threat to the sustainability of Bt technology, thus it is necessary to clarify insect resistance mechanisms. Firstly, the resistance level of Asian corn borer was determined by bioassay. After 28 generations selection in the lab, the Cry1Ie-resistant strain (ACB-IeR) developed more than 862-fold resistance to Cry1Ie, and the Cry1F-resistant strain (ACB-FR) developed 961-fold resistance to Cry1F. The results show that long-term exposure to Bt toxins can lead to resistance. Then, we compared the differential expression genes (DEGs) of ACB-FR and ACB-IeR with susceptible strain (ACB-BtS), and analyzed GO function and KEGG pathway through transcriptome sequencing. The comparison showed that in Bt-resistant strains, many genes have a significant down-regulated trend. Several Bt-resistance candidate genes were differentially expressed in both resistant strains. Furthermore, the DEGs were verified by RT-qPCR and showed similar trend. These results provide candidate genes for further research on the Bt resistance mechanism. Full article

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

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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 56 | Viewed by 8442

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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15 pages, 3065 KiB

Open AccessArticle

Effects of Irrigation Strategy and Plastic Film Mulching on Soil N₂O Emissions and Fruit Yields of Greenhouse Tomato

by Yuan Li, Mingzhi Zhang, Zhenguang Lu, Yushun Zhang and Jingwei Wang

Agriculture 2022, 12(2), 296; https://doi.org/10.3390/agriculture12020296 - 18 Feb 2022

Cited by 4 | Viewed by 2463

Abstract

Agriculture is a major source of global greenhouse gas emissions. Approximately 1/3 of vegetables in China are produced in greenhouses. However, the effects of different irrigation strategies and plastic film (PF) mulching combinations on N₂O emissions and tomato fruit yields in [...] Read more.

Agriculture is a major source of global greenhouse gas emissions. Approximately 1/3 of vegetables in China are produced in greenhouses. However, the effects of different irrigation strategies and plastic film (PF) mulching combinations on N₂O emissions and tomato fruit yields in greenhouses are unclear. The aims of this study were to explore the effects of micro-sprinkler irrigation under plastic film (MSPF), drip irrigation under plastic film (DIPF) and micro-sprinkler irrigation (MSI) on the soil nutrients, enzyme activity, nirS-type denitrifying bacterial community, N₂O emissions and fruit yields of tomato. The results showed that MSPF could improve the uniformity of soil water distribution and surface (0–40 cm) soil water content. Film mulching could increase soil temperature at depths of 5–25 cm. Both MSPF and DIPF increased microbial nitrogen, promoted the activity of rhizosphere soil urease and leucine aminopeptidase, changed the community of denitrifying bacteria, accelerated the turnover of soil nutrients and improved yield and water use efficiency. PF mulching had a greater impact on the nirS-type denitrifying bacterial community when compared to irrigation strategy. We conclude that MSPF can be used to configure commercially available installation and operation. The comprehensive benefit of MSPF treatment is that it is more profitable than that of DIPF. Full article

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13 pages, 1407 KiB

Open AccessArticle

Carbon Storage Potential of Agroforestry System near Brick Kilns in Irrigated Agro-Ecosystem

by Nayab Komal, Qamar uz Zaman, Ghulam Yasin, Saba Nazir, Kamran Ashraf, Muhammad Waqas, Mubeen Ahmad, Ammara Batool, Imran Talib and Yinglong Chen

Agriculture 2022, 12(2), 295; https://doi.org/10.3390/agriculture12020295 - 18 Feb 2022

Cited by 12 | Viewed by 3407

Abstract

The current study was conducted to estimate the carbon (C) storage status of agroforestry systems, via a non-destructive strategy. A total of 75 plots (0.405 ha each) were selected by adopting a lottery method of random sampling for C stock estimations for soil, [...] Read more.

The current study was conducted to estimate the carbon (C) storage status of agroforestry systems, via a non-destructive strategy. A total of 75 plots (0.405 ha each) were selected by adopting a lottery method of random sampling for C stock estimations for soil, trees and crops in the Mandi-Bahauddin district, Punjab, Pakistan. Results revealed that the existing number of trees in selected farm plots varied from 25 to 30 trees/ha. Total mean tree carbon stock ranged from 9.97 to 133 Mg C ha⁻¹, between 5–10 km away from the brick kilns in the study area. The decreasing order in terms of carbon storage potential of trees was Eucalyptus camaldulensis > Syzygium cumin > Popolus ciliata > Acacia nilotica > Ziziphus manritiana > Citrus sinensis > Azadirachtta Indica > Delbergia sisso > Bambusa vulgaris > Melia azadarach > Morus alba. Average soil carbon pools ranged from 10.3–12.5 Mg C ha⁻¹ in the study area. Meanwhile, maximum C stock for wheat (2.08 × 10⁶ Mg C) and rice (1.97 × 10⁶ Mg C) was recorded in the cultivated area of Tehsil Mandi-Bahauddin. The entire ecosystem of the study area had an estimated woody vegetation carbon stock of 68.5 Mg C ha⁻¹ and a soil carbon stock of 10.7 Mg C ha⁻¹. These results highlight that climate-smart agriculture has great potential to lock up more carbon and help in the reduction of CO₂ emissions to the atmosphere, and can be further used in planning policies for executing tree planting agendas on cultivated lands and for planning future carbon sequestration ventures in Pakistan. Full article

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

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15 pages, 2301 KiB

Open AccessFeature PaperArticle

Survey of Oomycetes Associated with Root and Crown Rot of Almond in Spain and Pathogenicity of Phytophthora niederhauserii and Phytopythium vexans to ‘Garnem’ Rootstock

by Francisco Beluzán, Xavier Miarnau, Laura Torguet, Josep Armengol and Paloma Abad-Campos

Agriculture 2022, 12(2), 294; https://doi.org/10.3390/agriculture12020294 - 18 Feb 2022

Cited by 13 | Viewed by 3958

Abstract

From 2018 to 2020, surveys of oomycetes associated with root and crown rot of almond (Prunus dulcis) were conducted on diseased young almond trees in commercial orchards and nurseries in six provinces of Spain. A total of 104 oomycete isolates [...] Read more.

From 2018 to 2020, surveys of oomycetes associated with root and crown rot of almond (Prunus dulcis) were conducted on diseased young almond trees in commercial orchards and nurseries in six provinces of Spain. A total of 104 oomycete isolates were obtained from plant and soil samples, which h were identified by sequencing the internal transcribed spacer (ITS) region of the ribosomal DNA. Diverse species belonging to the genera Globisporangium, Phytophthora, Phytopythium and Pythium were found, Phytopythium vexans and Phytophthora niederhauserii being the most frequent. The pathogenicity of these two species to one-year-old almond seedlings of ‘Garnem’ (P. dulcis × P. persica) rootstock was studied. All seedlings inoculated with Pp. vexans and Ph. niederhauserii isolates showed severe symptoms at the late stage of the pathogenicity test (defoliation, wilting and dieback) and several plants died. Some isolates of Ph. niederhauserii significantly reduced the dry weight of the roots compared with the control, but this effect was not observed in seedlings inoculated with Pp. vexans. These results provide new information about the oomycete species present in almond crops in Spain and highlight the importance of carrying out frequent phytosanitary surveys for a better knowledge of potential risks posed by these soil-borne pathogens. Full article

(This article belongs to the Special Issue Soil Borne Plant Pathogens: New Insights on Sustainable Control and Agronomic Implications)

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16 pages, 1935 KiB

Open AccessArticle

Valorization of Quality of Vermicomposts and Composts Using Various Parameters

by Monika Jakubus and Weronika Michalak-Oparowska

Agriculture 2022, 12(2), 293; https://doi.org/10.3390/agriculture12020293 - 18 Feb 2022

Cited by 4 | Viewed by 2833

Abstract

Due to the increasing biomass of biowaste it is necessary to manage it rationally. This work presents comparisons and valorization of vermicomposts (VCs) and composts (Cs) prepared from various biowastes generated in households and private gardens, in terms of their practical use. The [...] Read more.

Due to the increasing biomass of biowaste it is necessary to manage it rationally. This work presents comparisons and valorization of vermicomposts (VCs) and composts (Cs) prepared from various biowastes generated in households and private gardens, in terms of their practical use. The tested VCs and Cs were subjected to chemical analyses to assess the amounts of macro- (N, P, K, S, Mg, Ca, Na) and micronutrients (Fe, Zn, Mn, Cu, Ni), as well as contents of organic matter (OM), total organic carbon (TOC), humic compounds (HS) and labile and water extractable organic carbon (LC, WEOC). Moreover, humification indexes (HR, HI, DP) were determined. The amounts of macro- and micronutrients, OM, TOC, LC, WEOC were greater for vermicomposts. Regardless of these differences, both vermicomposts and composts were characterized by considerable amounts of organic matter ranging from 325 to 631 g·kg⁻¹ and TOC amounting from 82 to 270 g·kg⁻¹. Moreover, the tested organic fertilizers were characterized by high contents of N (7–21.5 g·kg⁻¹), K (3.7–24.4 g·kg⁻¹), Ca (12.2–44.0 g·kg⁻¹), Fe (133.1–333.8 mg·kg⁻¹) and Mn (71.5–113.8 mg·kg⁻¹). The analyzed VCs and Cs did not exceed the permissible amounts of heavy metals (Cr, Pb) and contained a comparable amount and quality of humus compounds. The level of C_HS ranged from 29.6 to 41 g·kg⁻¹ for vermicomposts, and from 19.8 to 51.8 g·kg⁻¹ for composts. The humification indexes indicate that VCs and Cs were well–matured despite different composting conditions. The HI values for VCs ranged from 8.3% to 10% and for Cs amounted from 12.2% to 16.8%. Similarly, the HR values were higher for composts (24.3–33%) in comparison to VCs (15.2–20.1%). Vermicomposting and composting of biowaste is economically and environmentally justified. Fertilizers obtained in the composting process are a valuable source of organic material and nutrients essential for plants and can be safely used in private gardens. Full article

(This article belongs to the Special Issue Vermicompost in Sustainable Crop Production)

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16 pages, 3819 KiB

Open AccessArticle

Measuring Method of Slip Ratio for Tractor Driving Wheels Based on Machine Vision

by Shaohua Zhu, Lin Wang, Zhongxiang Zhu, Enrong Mao, Yiming Chen, Yuxi Liu and Xianxu Du

Agriculture 2022, 12(2), 292; https://doi.org/10.3390/agriculture12020292 - 17 Feb 2022

Cited by 8 | Viewed by 4340

Abstract

Tractors are prone to large slips when they are in field operation. The degree of slip plays a vital role in traction efficiency and fuel efficiency. This paper presents a method for measuring the slip ratio of tractors in field operation based on [...] Read more.

Tractors are prone to large slips when they are in field operation. The degree of slip plays a vital role in traction efficiency and fuel efficiency. This paper presents a method for measuring the slip ratio of tractors in field operation based on machine vision. The accurate measurement of slip ratio needs to obtain actual velocity and theoretical velocity separately. For obtaining the actual velocity, a monocular camera mounted on the tractor vertically faces down at the ground to collect images. Then, the feature points of inter-frame ground images are matched by the ORB (Oriented FAST and Rotated BRIEF) algorithm for calculating the translational displacement. Next, a homography matrix based on camera calibration is proposed to complete the transformation of a point from the pixel coordinate system to the world coordinate system. Aiming to acquire the theoretical velocity, a method that takes the variations in tire radius into account is proposed, and the tire radii of the driving wheels are indirectly determined by the tire inflation pressure in real-time. The proposed measurement method was verified with an experimental tractor. The results show that the mean absolute errors of the tractor driving wheels’ slip ratio measured by the machine vision method are less than 0.75%, and the maximum of the absolute errors is not more than 2.22%, which shows good performance. Full article

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

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4 pages, 188 KiB

Open AccessEditorial

Intercropping Systems for Sustainable Agriculture

by Martin Weih, M. Inés Mínguez and Stefano Tavoletti

Agriculture 2022, 12(2), 291; https://doi.org/10.3390/agriculture12020291 - 17 Feb 2022

Cited by 9 | Viewed by 4420

Abstract

Increasing sustainability in agriculture is an imperative target for whole food and feed production and transformation chains [...] Full article

(This article belongs to the Special Issue Intercropping Systems for Sustainable Agriculture)

15 pages, 2121 KiB

Open AccessArticle

Phylogenetic Analysis of Ryegrass (Lolium rigidum) Populations and the Proliferation of ALS Resistance in Saudi Arabia

by Abdelhalim I. Ghazy, Talal K. Al-Ateeq, Eid I. Ibrahim, Hussein M. Migdadi, Kotb A. Attia, Muhammad Javed, Muhammad Altaf Khan, Ibrahim Al-Ashkar and Abdullah Al-Doss

Agriculture 2022, 12(2), 290; https://doi.org/10.3390/agriculture12020290 - 17 Feb 2022

Cited by 1 | Viewed by 2268

Abstract

Morphological and simple sequence repeat (SSR) approaches were used to determine the genetic diversity of 29 ryegrass (Lolium rigidum) genotypes belonging to eight populations collected from several regions in Saudi Arabia. In this study, 50 in Silico-developed SSR markers derived from [...] Read more.

Morphological and simple sequence repeat (SSR) approaches were used to determine the genetic diversity of 29 ryegrass (Lolium rigidum) genotypes belonging to eight populations collected from several regions in Saudi Arabia. In this study, 50 in Silico-developed SSR markers derived from genomic and expressed sequence tag (EST) microsatellites were examined. Analysis of variance showed highly significant differences in all studied traits. Cluster analysis based on the morphological data of the 29 Lolium genotypes and using PAST (paleontological statistics) software was performed. According to the results, clustering was based mostly on genotype location. The sensitive genotypes for herbicide were clustered in one group. In addition, using EST-SSR markers, we observed the existence of a considerable number of genetic variations among Lolium genotypes. From these markers, only 31 produced reasonable amplification products. The results showed that 23 SSR markers revealed that 74.19% were polymorphic. The number of alleles detected per primer ranged from one to five in the primer LTC SSR1. The tested primers amplified 1434 bands across eight populations, with an average of 46.26 bands per primer. The polymorphism information content (PIC) values ranged from 0.11 to 0.76 for the primers LT EST-SSR5 and LTC SSR1. The unweighted pair group method with arithmetic average (UPGMA) clustering of the 29 genotypes representing eight populations was based essentially on their locations and herbicide-tolerance levels. Most of the populations formed into four clusters, together representing genotypes. Moreover, the tolerant populations were distinguished from the sensitive ones. The relationship between the genetic diversity and geographical source of Lolium rigidum populations of Saudi Arabia was revealed through this study. The results showed that the efficiency of developed SSR markers are transferable across species. They have been helpful to assess the genetic diversity of the ryegrass population as this could be applied to differentiate between tolerant and sensitive populations of ryegrass. Full article

(This article belongs to the Section Crop Genetics, Genomics and Breeding)

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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 90 | Viewed by 22665

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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16 pages, 724 KiB

Open AccessFeature PaperArticle

Pesticide Use Culture among Food Crop Farmers: Implications for Subtle Exposure and Management in Barbados

by David Oscar Yawson

Agriculture 2022, 12(2), 288; https://doi.org/10.3390/agriculture12020288 - 17 Feb 2022

Cited by 7 | Viewed by 4122

Abstract

Globally, there is a strong interest in on-farm pesticide use culture due to genuine concerns about the individual, public, and ecological health risks posed by pesticides. At farm scale, pesticide use culture can be captured via the assessments of knowledge, attitudes, and practices [...] Read more.

Globally, there is a strong interest in on-farm pesticide use culture due to genuine concerns about the individual, public, and ecological health risks posed by pesticides. At farm scale, pesticide use culture can be captured via the assessments of knowledge, attitudes, and practices (KAP) to inform intervention strategy and integrated science-based management. Despite the intensive use of pesticides in agriculture in the Caribbean, there is limited information on pesticide use culture or KAP assessment. This study assessed the pesticide use culture among selected food crop farmers in Barbados. A cross-sectional study of 93 food crop farmers, using a semi-structured instrument, was carried out. The results show that the respondents self-rated their level of knowledge on pesticide handling and application as medium to high but low on waste management. Over 50% of the respondents indicated they determine application rates and could understand and follow information on pesticide labels. The majority of the respondents relied on the Internet for information on pesticides, and less than half had received formal training on pesticide use in the three years preceding this study. On attitude, there was overwhelming support for the encouragement of pesticide usage to reduce losses in yield and quality of harvest. Knowledge did not always imply positive attitudes toward safe practices. While 86% agreed that pesticides posed considerable risks to the personal health of users, 60% agreed that one did not need to have all the recommended personal protective equipment (PPE) before using a given pesticide. Due to gaps in the knowledge–attitude–practice continuum, some respondents applied pesticides when necessary, and there was low adherence to the use of recommended PPE when handling/applying pesticides or cleaning/repairing pesticide application equipment, and some respondents indicated a tendency to eat, drink, or smoke during or immediately after pesticide application. These suggest subtle exposure. It was concluded that the low use of recommended PPE, high reliance on the Internet for pesticide guidance, and, particularly, pesticide waste disposal practices require urgent attention from policy, regulatory, and practical levels to improve the pesticide use culture. Full article

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

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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 19 | Viewed by 16720

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 16 | Viewed by 3109

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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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 15 | Viewed by 2396

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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16 pages, 6165 KiB

Open AccessArticle

LA-DeepLab V3+: A Novel Counting Network for Pigs

by Chengqi Liu, Jie Su, Longhe Wang, Shuhan Lu and Lin Li

Agriculture 2022, 12(2), 284; https://doi.org/10.3390/agriculture12020284 - 17 Feb 2022

Cited by 16 | Viewed by 3011

Abstract

Accurate identification and intelligent counting of pig herds can effectively improve the level of fine management of pig farms. A semantic segmentation and counting network was proposed in this study to improve the segmentation accuracy and counting efficiency of pigs in complex image [...] Read more.

Accurate identification and intelligent counting of pig herds can effectively improve the level of fine management of pig farms. A semantic segmentation and counting network was proposed in this study to improve the segmentation accuracy and counting efficiency of pigs in complex image segmentation. In this study, we built our own datasets of pigs under different scenarios, and set three levels of number detection difficulty—namely, lightweight, middleweight, and heavyweight. First, an image segmentation model of a small sample of pigs was established based on the DeepLab V3+ deep learning method to reduce the training cost and obtain initial features. Second, a lightweight attention mechanism was introduced, and attention modules based on rows and columns can accelerate the efficiency of feature calculation and reduce the problem of excessive parameters and feature redundancy caused by network depth. Third, a recursive cascade method was used to optimize the fusion of high- and low-frequency features for mining potential semantic information. Finally, the improved model was integrated to build a graphical platform for the accurate counting of pigs. Compared with FCNNs, U-Net, SegNet, and DenseNet methods, the DeepLab V3+ experimental results show that the values of the comprehensive evaluation indices P, R, AP, F₁-score, and MIoU of LA-DeepLab V3+ (single tag) are higher than those of other semantic segmentation models, at 86.04%, 75.06%, 78.67%, 0.8, and 76.31%, respectively. The P, AP, and MIoU values of LA-DeepLab V3+ (multiple tags) are also higher than those of other models, at 88.36%, 76.75%, and 74.62%, respectively. The segmentation accuracy of pig images with simple backgrounds reaches 99%. The pressure test of the counting network can calculate the number of pigs with a maximum of 50, which meets the requirements of free-range breeding in standard piggeries. The model has strong generalization ability in pig herd detection under different scenarios, which can serve as a reference for intelligent pig farm management and animal life research. Full article

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

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23 pages, 12396 KiB

Open AccessArticle

The Initiation of a Phytosociological Study on Certain Types of Medicinal Plants

by Emanuela Alice Luță, Manuela Ghica and Cerasela Elena Gîrd

Agriculture 2022, 12(2), 283; https://doi.org/10.3390/agriculture12020283 - 16 Feb 2022

Cited by 3 | Viewed by 3787

Abstract

The cultivation of medicinal plants represents great necessity and topicality these days, given that the pharmaceutical industry requires high quality raw materials in large quantities. Those are used for the production of food supplements/phytomedicines/medical devices or gemmo-derivatives’ products. Starting from these premises, this [...] Read more.

The cultivation of medicinal plants represents great necessity and topicality these days, given that the pharmaceutical industry requires high quality raw materials in large quantities. Those are used for the production of food supplements/phytomedicines/medical devices or gemmo-derivatives’ products. Starting from these premises, this present study aimed to culture common batches of different associations of medicinal plants in order to quantify the fabrication of plant products, but also to observe possible changes in their internal structure, in direct correlation with the biosynthesis of active principles. The crops were monitored in 2018–2021. It was found that in all the common crops compared to the control ones, the amount of vegetable product provided was much higher (for example, the thyme-rosemary crop produced 730 g of fresh vegetable plants, compared with 540 g in the control crop; St. John’s Wort in culture with lemon balm delivered 1934 g of vegetable product, compared with 1423 g obtained from the control crop; mint was grown with lemon balm and produced a double amount of vegetable mass compared with the control crop). The presence of numerous glandular hairs in the samples from the phytosociological groups for the species from the Lamiaceae family, could explain the difference in the volatile oil content (4 mL/100 g produced by rosemary from the thyme-rosemary crop compared with 3.6 mL/100 g from the control one; 6.6 mL/100 g generated by thyme from the thyme-rosemary crop compared with 3.6 mL/100 from the control group; 2 mL/100 g of lemon balm volatile oil from the mint-lemon balm compared with 0.6 mL/100 g). The content of other types of active principles is dependent on the culture association. From results analysis it was found that in the phytosociological groups, flavones, PCAs and total polyphenols were significantly higher compared to control ones (2.4413 ± 0.1858 g flavones expressed in rutin/100 g in the thyme dried leaves from thyme-rosemary to 1.9317 ± 0.0947 g flavones produced by the control thyme; 9.9461 ± 0.8385 g PCAs expressed in chlorogenic acid/100 g for the same sample compared with 6.9709 ± 1.4921 g produced by the control batch; 11.1911 ± 0.7959 g TPC expressed in tannic acid/100 g in the thyme dried leaves from the thyme-rosemary phytosociological crop to 6.0393 ± 0.3204 g from the control one). The obtained results can be a starting point regarding the potential associations of medicinal plants in crops, in order to obtain a qualitative and quantitative vegetal mass. 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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Agriculture, Volume 12, Issue 2 (February 2022) – 190 articles

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