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Agriculture, Volume 14, Issue 11 (November 2024) – 242 articles

Cover Story (view full-size image): Driven by consumer interest, producer and retailer strategies, as well as normative context, the rapid development of the world organic sector has stimulated an increase in socio-economic research. The implementation of a structural topic model on scientific abstracts from the last 20 years allowed us to identify three broad areas of interest for socio-economic researchers: consumers, production, and society. The relationship of these areas varies in different regions, which indicates good integration of organic socio-economic research within local contexts. Overall, consumer-focused studies are more prominent than production-focused studies. The latter seems to call for renewed attention and analysis of the organic sector, assisted by evidence of the organic supply chain. View this paper
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20 pages, 10852 KiB  
Article
Impact of Grazing Tibetan Pigs on Soil Quality
by Guoxin Wu, Haoqi Wang, Mengqi Duan, Licuo Ze, Shixiong Dong, Huimin Zhang, Kejun Wang, Zhankun Tan and Peng Shang
Agriculture 2024, 14(11), 2096; https://doi.org/10.3390/agriculture14112096 - 20 Nov 2024
Viewed by 312
Abstract
Pig manure, as an organic fertilizer, can significantly affect soil nutrient content, pH, and electrical conductivity. Moreover, the accumulation of heavy metals in pig manure and their potential ecological risks are also important concerns in soil management. Additionally, grazing systems may influence soil [...] Read more.
Pig manure, as an organic fertilizer, can significantly affect soil nutrient content, pH, and electrical conductivity. Moreover, the accumulation of heavy metals in pig manure and their potential ecological risks are also important concerns in soil management. Additionally, grazing systems may influence soil health and ecological balance by altering the soil microbial community structure. Therefore, this study investigates the impact of grazing Tibetan pigs on soil quality, focusing on the physicochemical properties, heavy metal accumulation, and microbial diversity. In the surface soil after grazing (GS0), pH, EC, AP, and AK were significantly higher than before grazing (NS0) (p < 0.05), while AN showed no significant difference. In the 10 cm soil layer, pH, EC, AK, and AN in GS10 were significantly higher than in NS10 (p < 0.05), whereas AP was significantly lower (p < 0.05). At the 20 cm depth, pH, EC, AP, and AK in GS20 were significantly higher than in NS20 (p < 0.05), but AN was significantly lower (p < 0.05). Overall, AN, AP, and AK decreased with increasing soil depth, while pH and EC showed no significant changes between the 10 cm and 20 cm layers (p > 0.05). In GS0 soil, the contents of Cd(II) and Zn(II) were significantly lower than those in NS0 (p < 0.05), while Pb(II) content was significantly higher (p < 0.05). There were no significant differences in Cu(II), Ni(II), Cr(VI), As(V), and Hg(II) (p > 0.05). In GS10 soil, Ni and Pb(II) contents were higher, whereas Cu(II), Zn(II), and Hg(II) contents were lower. In GS20 soil, Pb(II) and Cr(VI) contents were higher, while Cu(II) and Zn(II) contents were lower. Overall, GS had consistently lower Cd(II), Cu(II), Zn(II), and Hg(II) contents at all depths compared to NS, while Pb(II) and Cr(VI) contents were higher, showing depth-related variation trends, possibly due to plant absorption and heavy metal leaching. Probiotics such as Firmicutes, Bacteroidetes, and Acinetobacter increased significantly in soil, resulting in changes in the soil bacterial community. Full article
(This article belongs to the Section Agricultural Soils)
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20 pages, 6819 KiB  
Article
Analysis and Experimentation on the Motion Characteristics of a Dragon Fruit Picking Robot Manipulator
by Kairan Lou, Zongbin Wang, Bin Zhang, Qiu Xu, Wei Fu, Yang Gu and Jinyi Liu
Agriculture 2024, 14(11), 2095; https://doi.org/10.3390/agriculture14112095 - 20 Nov 2024
Viewed by 381
Abstract
Due to the complex growth positions of dragon fruit and the difficulty in robotic picking, this paper proposes a six degrees of freedom dragon fruit picking robot and investigates the manipulator’s motion characteristics to address the adaptive motion issues of the picking manipulator. [...] Read more.
Due to the complex growth positions of dragon fruit and the difficulty in robotic picking, this paper proposes a six degrees of freedom dragon fruit picking robot and investigates the manipulator’s motion characteristics to address the adaptive motion issues of the picking manipulator. Based on the agronomic characteristics of dragon fruit cultivation, the structural design of the robot and the dimensions of its manipulator were determined. A kinematic model of the dragon fruit picking robot based on screw theory was established, and the workspace of the manipulator was analyzed using the Monte Carlo method. Furthermore, a dynamic model of the manipulator based on the Kane equation was constructed. Performance experiments under trajectory and non-trajectory planning showed that trajectory planning significantly reduced power consumption and peak torque. Specifically, Joint 3’s power consumption decreased by 62.28%, and during the picking, placing, and resetting stages, the peak torque of Joint 4 under trajectory planning was 10.14 N·m, 12.57 N·m, and 16.85 N·m, respectively, compared to 12.31 N·m, 15.69 N·m, and 22.13 N·m under non-trajectory planning. This indicated that the manipulator operates with less impact and smoother motion under trajectory planning. Comparing the dynamic model simulation and actual testing, the maximum absolute error in the joint torques was −2.76 N·m, verifying the correctness of the dynamic equations. Through field picking experiments, it was verified that the machine’s picking success rate was 66.25%, with an average picking time of 42.4 s per dragon fruit. The manipulator operated smoothly during each picking process. In the study, the dragon fruit picking manipulator exhibited good stability, providing the theoretical foundation and technical support for intelligent dragon fruit picking. Full article
(This article belongs to the Section Agricultural Technology)
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17 pages, 1434 KiB  
Review
Diversity of Honeybee Behavior Is a Potential Inbuilt Trait for Varroa Tolerance: A Basic Tool for Breeding Varroa-Resistant Strains
by Peter Njukang Akongte, Daegeun Oh, Changhoon Lee, Yongsoo Choi and Dongwon Kim
Agriculture 2024, 14(11), 2094; https://doi.org/10.3390/agriculture14112094 - 20 Nov 2024
Viewed by 486
Abstract
The ectoparasitic mite Varroa destructor is well known for transmitting a number of viruses that can contribute to the collapse of honeybee colonies. To date, the many control measures put in place to limit the spread of V. destructor have yielded no satisfactory [...] Read more.
The ectoparasitic mite Varroa destructor is well known for transmitting a number of viruses that can contribute to the collapse of honeybee colonies. To date, the many control measures put in place to limit the spread of V. destructor have yielded no satisfactory results. This is challenging because the effect of the parasite on honeybee colonies is becoming notorious. This has weakened the beekeeping industry and reduced pollination services, which may contribute to global food insecurity in the future. Therefore, it is necessary to put in place possible control measures and outline sustainable approaches to mitigate research efforts against the Varroa destructor. Extensive research to elaborate on the best possible solution has revealed that the selective breeding of naturally occurring V. destructor immune-related traits of honeybee strains is sustainable. Since the Integrated Pest Management approach was introduced, while still being very unreliable, there are open questions as to what control strategy could be considered effective. After cross-examination of existing strategies, a more practical way could be the adoption of an integrated approach. This approach should involve the association of selective breeding of honeybee colonies with V. destructor immune-related traits and the application of soft chemical treatment. Full article
(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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21 pages, 5229 KiB  
Article
Sprayable Biodegradable Polyester-Urethane-Urea Mulching Treatment Increases Abundance of Soil Microbes
by Cuyler K. Borrowman, Raju Adhikari, Kei Saito, Karen Little, Stuart Gordon and Antonio F. Patti
Agriculture 2024, 14(11), 2093; https://doi.org/10.3390/agriculture14112093 - 20 Nov 2024
Viewed by 482
Abstract
The paper investigates for the first time the impact of a novel sprayable, biodegradable polyester-urethane-urea (PEUU) mulch on the microbial community composition of an agricultural soil. In this study changes to the composition of the soil microbial community and in soil enzyme activity [...] Read more.
The paper investigates for the first time the impact of a novel sprayable, biodegradable polyester-urethane-urea (PEUU) mulch on the microbial community composition of an agricultural soil. In this study changes to the composition of the soil microbial community and in soil enzyme activity involved in nutrient cycling were monitored on tomato plants grown under controlled greenhouse conditions. Particular attention was given to impacts on the relative changes in abundance of soil microbes. The PEUU mulch reduced the abundance of a small number of soil microbe taxa, but also provided an environment in which some taxa, which were comparatively rare in initial and unmulched soils, thrived. Importantly, the relative abundances of Azospirillum, Noviherbaspirillum, Exophiala, Phoma, Chaetomium and Clonostachys species all increased in soils treated with PEUU mulch. Principal coordinates analysis revealed the microbial community composition on PEUU films alone and in PEUU treated soil were most similar, while the PEUU films’ microbial community differed the most from the initial soil’s microbial community. These results indicate that from an agricultural productivity and an environmental safety standpoint the use of PEUU mulch may be preferable to PE and could provide additional plant growth benefits by increasing the abundance of soil microbes. Full article
(This article belongs to the Special Issue Impact of Plastics on Agriculture)
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19 pages, 800 KiB  
Article
The Influence of Season and Age on Specific Semen Traits and Reproductive Behavior in Carpatina Breed Bucks
by Constantin Pascal, Claudia Pânzaru, Răzvan-Mihail Radu-Rusu, Vasile Maciuc, Alexandru Marian Florea and Ionică Nechifor
Agriculture 2024, 14(11), 2092; https://doi.org/10.3390/agriculture14112092 - 20 Nov 2024
Viewed by 456
Abstract
This study explores how age and seasonal changes impact semen characteristics and reproductive behavior in Carpatina breed bucks. Males were divided into three age groups: young (14–23 months; L14), adult (3–4 years; L34), and older (5–6 years; L56). Scrotal biometry was determined using [...] Read more.
This study explores how age and seasonal changes impact semen characteristics and reproductive behavior in Carpatina breed bucks. Males were divided into three age groups: young (14–23 months; L14), adult (3–4 years; L34), and older (5–6 years; L56). Scrotal biometry was determined using a measuring tape, and testicular volume was evaluated by fully submerging the testes in a water-filled container and measuring the displaced water. Semen analysis was conducted on samples collected each season, with volume, color, and acidity being assessed. The evaluation of specific semen characteristics (motility, sperm concentration, normal spermatozoa) was conducted using a Computer-Assisted Semen Analysis (CASA) system, and testosterone levels were measured in blood samples collected at the start of each season. Behavior and sexual reflexes were evaluated based on mating desire and the bucks’ reaction to the presence of females. Key findings indicate that testicular volume varies significantly with both age and season, with the most pronounced differences between younger bucks and the older groups, especially during autumn. Semen quality parameters such as ejaculate volume, sperm concentration, and motility also showed seasonal fluctuations, with younger bucks having lower sperm concentrations. Testosterone levels were observed to increase with age, peaking in autumn. Behavioral observations revealed that younger bucks exhibited less intense sexual activity, although this improved during autumn. Additionally, a significant correlation was identified between body weight and testicular volume in adult bucks (R = 0.942, p-value = 0.016 for L34; R = 0.797, p-value = 0.022 for L56), suggesting that age plays a crucial role in reproductive potential. Our findings highlight that, while bucks are capable of year-round reproduction, autumn provides optimal conditions for semen quality and reproductive performance. This research has valuable implications for optimizing breeding programs, contributing to genetic advancement, and improving management strategies in goat farming, especially within temperate continental climates. Full article
(This article belongs to the Special Issue Farming Factors’ Influence on Animal Productions)
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13 pages, 1880 KiB  
Article
Investigating the Influence of Organic Loading Rate, Temperature and Stirring Speed on Biogas Production Using Agricultural Waste in South Africa
by Ephodia Sihlangu, Primrose Magama, Idan Chiyanzu, Thierry Regnier, Dibungi Luseba and Khathutshelo Agree Nephawe
Agriculture 2024, 14(11), 2091; https://doi.org/10.3390/agriculture14112091 - 20 Nov 2024
Viewed by 501
Abstract
Biogas production offers an alternate method for managing agricultural waste and contributes to sustainable renewable energy generation. Anaerobic digestion (AD) enables the transformation of organic waste, including agricultural substrates, into biogas, mostly consisting of methane, carbon dioxide, and trace gases such as ammonia [...] Read more.
Biogas production offers an alternate method for managing agricultural waste and contributes to sustainable renewable energy generation. Anaerobic digestion (AD) enables the transformation of organic waste, including agricultural substrates, into biogas, mostly consisting of methane, carbon dioxide, and trace gases such as ammonia and hydrogen sulphide. The objective of this study was to employ a 30 L semi-continuous stirred tank reactor to evaluate the effects of organic loading rate, temperature, and speed of stirring on biogas production. The reactor was inoculated with 8.6 L and filled with 11.4 L of a mixed substrate including cattle manure, potato waste, potato starch waste, fruit waste, and expired dry dog food. The reactor was evaluated with organic loading rates (OLRs) of 11.2, 12.2, and 13.2 g VS/L d, and stirring speeds of 25.5, 35.5, and 45.5 rpm. The results indicated that the maximum yield was 12.2 g VS/L d at 45.5 rpm, and in thermophilic conditions, the biogas yield surpassed that of mesophilic conditions, measuring 105,860 NmL/g VS compared to 69,800 NmL/g VS. This study emphasises the significance of optimising operational parameters to improve biogas output, thereby contributing to sustainable energy resources and advancing the Sustainable Development Goals (SDGs). Full article
(This article belongs to the Section Agricultural Technology)
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17 pages, 7484 KiB  
Article
Prediction of the Potentially Suitable Areas of Sesame in China Under Climate Change Scenarios Using MaxEnt Model
by Guoqiang Li, Xue Wang, Jie Zhang, Feng Hu, Hecang Zang, Tongmei Gao, Youjun Li and Ming Huang
Agriculture 2024, 14(11), 2090; https://doi.org/10.3390/agriculture14112090 - 20 Nov 2024
Viewed by 511
Abstract
Sesame (Sesamum indicum L, flora of China) is an essential oil crop in China, but its growth and development are affected by climate change. To cope with the impacts of climate change on sesame cultivation, we used the Maximum Entropy (MaxEnt) model [...] Read more.
Sesame (Sesamum indicum L, flora of China) is an essential oil crop in China, but its growth and development are affected by climate change. To cope with the impacts of climate change on sesame cultivation, we used the Maximum Entropy (MaxEnt) model to analyze the bioclimatic variables of climate suitability of sesame in China and predicted the suitable area and trend of sesame in China under current and future climate scenarios. The results showed that the MaxEnt model prediction was excellent. The most crucial bioclimatic variable influencing the distribution of sesame was max temperature in the warmest month, followed by annual mean temperature, annual precipitation, mean diurnal range, and precipitation of the driest month. Under the current climate scenario, the suitable areas of sesame were widely distributed in China, from south (Hainan) to north (Heilongjiang) and from east (Yellow Sea) to west (Tibet). The area of highly suitable areas was 64.51 × 104 km2, accounting for 6.69% of the total land area in China, and was primarily located in mainly located in southern central Henan, eastern central Hubei, northern central Anhui, northern central Jiangxi, and eastern central Hunan. The area of moderately suitable areas and lowly suitable areas accounted for 17.45% and 25.82%, respectively. Compared with the current climate scenario, the area of highly and lowly suitable areas under future climate scenarios increased by 0.10%–11.48% and 0.08%–8.67%, while the area of moderately suitable areas decreased by 0.31%–23.03%. In addition, the increased highly suitable areas were mainly distributed in northern Henan. The decreased moderately suitable areas were mainly distributed in Heilongjiang, Jilin, and Liaoning. This work is practically significant for optimizing the regional layout of sesame cultivation in response to future climate conditions. Full article
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11 pages, 576 KiB  
Review
Residual Herbicide in Cover Cropping Systems
by Lucas O. R. Maia, Leonard B. Piveta and William G. Johnson
Agriculture 2024, 14(11), 2089; https://doi.org/10.3390/agriculture14112089 - 20 Nov 2024
Viewed by 501
Abstract
Soil residual herbicides are often applied at cover crop termination to extend the period of weed control and reduce the selection pressure for herbicide resistance. Previous studies indicate that one of the benefits of cover crop use is the increase in the activity [...] Read more.
Soil residual herbicides are often applied at cover crop termination to extend the period of weed control and reduce the selection pressure for herbicide resistance. Previous studies indicate that one of the benefits of cover crop use is the increase in the activity of enzymes in the soil. Some enzymes are also responsible for breaking down herbicide molecules. The biodegradation of herbicides in the soil is a natural process that leads to a reduction in the concentration of the parent compound overtime. Although cover crop use can result in the increased activity of soil enzymes, to date, there is no evidence that such increased activity also leads to a reduced persistence of residual herbicides in the soil. However, cover crop use does alter the fate of residual herbicides by interception, with some studies reporting more than 90% interception. Without rainfall or irrigation during the days following its application, the herbicide remains on the plant surface and is ineffective as a weed control tool. Following the integrated weed management approach, the combination of cover crop and soil residual herbicides is a promising alternative to delay the development of new herbicide resistance cases. However, more research is needed to understand the impact of biomass accumulation on residual herbicide fate and to determine the best strategies to improve herbicide placement on cover cropping system. This paper reviews the impact of cover crop use on soil microbial activity and the further degradation of soil residual herbicides as well as the fate of residual herbicides when applied at cover crop termination. Full article
(This article belongs to the Section Agricultural Soils)
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13 pages, 3096 KiB  
Article
Defoliation Categorization in Soybean with Machine Learning Algorithms and UAV Multispectral Data
by Marcelo Araújo Junqueira Ferraz, Afrânio Gabriel da Silva Godinho Santiago, Adriano Teodoro Bruzi, Nelson Júnior Dias Vilela and Gabriel Araújo e Silva Ferraz
Agriculture 2024, 14(11), 2088; https://doi.org/10.3390/agriculture14112088 - 19 Nov 2024
Viewed by 408
Abstract
Traditional disease severity monitoring is subjective and inefficient. This study employs a Parrot multispectral sensor mounted on an unmanned aerial vehicle (UAV) to apply machine learning algorithms, such as random forest, for categorizing defoliation levels in R7-stage soybean plants. This research assesses the [...] Read more.
Traditional disease severity monitoring is subjective and inefficient. This study employs a Parrot multispectral sensor mounted on an unmanned aerial vehicle (UAV) to apply machine learning algorithms, such as random forest, for categorizing defoliation levels in R7-stage soybean plants. This research assesses the effectiveness of vegetation indices, spectral bands, and relative vegetation cover as input parameters, demonstrating that machine learning approaches combined with multispectral imagery can provide a more accurate and efficient assessment of Asian soybean rust in commercial soybean fields. The random forest algorithm exhibited satisfactory classification performance when compared to recent studies, achieving accuracy, precision, recall, F1-score, specificity, and AUC values of 0.94, 0.92, 0.92, 0.92, 0.97, and 0.97, respectively. The input variables identified as most important for the classification model were the WDRVI and MPRI indices, the red-edge and NIR bands, and relative vegetation cover, with the highest Gini importance index. Full article
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17 pages, 3531 KiB  
Systematic Review
Comparison of Organic and Conventional Agriculture in the Czech Republic: A Systematic Review
by Hana Vašková and Pavel Saska
Agriculture 2024, 14(11), 2087; https://doi.org/10.3390/agriculture14112087 - 19 Nov 2024
Viewed by 642
Abstract
This systematic review aims to comprehensively examine publications that compared conventional and organic agriculture in the Czech Republic. Agriculture in the Czech Republic is unique because of considerable variability in natural and climatic conditions and from a historical context. The ultimate objective of [...] Read more.
This systematic review aims to comprehensively examine publications that compared conventional and organic agriculture in the Czech Republic. Agriculture in the Czech Republic is unique because of considerable variability in natural and climatic conditions and from a historical context. The ultimate objective of this systematic review was to identify possible research gaps that could serve as a background for updating national research policy. The search for suitable publications was performed in Scopus and Web of Science, and screening for eligibility followed the PRISMA approach. In total, 65 publications satisfied the inclusion criteria, the extraction of which provided 380 data records. Crop production appeared to be the most frequent research theme (204 records), followed by economy (122 records), biodiversity (n = 30), animal production (n = 18) and food (n = 6). Unfortunately, numerous records suffer from methodological and statistical flaws. The research gaps identified in this systematic review include important crops, comparisons between varieties and individual practices, topics related to drought, biodiversity-oriented research including ecosystem services, and meat or egg production. We propose that, to obtain robust comparisons between the two farming systems across multiple areas of research, one large experiment covering several organic and conventional farms across the country is needed. Full article
(This article belongs to the Section Agricultural Systems and Management)
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19 pages, 8708 KiB  
Article
Genome-Wide Analysis of GLK Gene Family in Four Cotton Species Provides Insights into Their Involvement in Cotton Abiotic Stress Response
by Rui Tang, Xin Zhou, Shuangshuang Weng, Fei Wang, Rong Li, Quanliang Xie, Zihan Li, Shuangquan Xie, Aiping Cao, Lu Zhuo, Manhong Wang and Hongbin Li
Agriculture 2024, 14(11), 2086; https://doi.org/10.3390/agriculture14112086 - 19 Nov 2024
Viewed by 523
Abstract
Cotton is a crucial economic crop that supplies natural fibers for the textile industry, with fiber quality being greatly impacted by abiotic stress throughout its growth stages. The Golden2-Like (GLK) gene family plays a key role in plant development and adaptation [...] Read more.
Cotton is a crucial economic crop that supplies natural fibers for the textile industry, with fiber quality being greatly impacted by abiotic stress throughout its growth stages. The Golden2-Like (GLK) gene family plays a key role in plant development and adaptation to abiotic stress. However, the specific functions and regulatory mechanisms of GLK members in cotton remain largely unexplored. In this study, a thorough analysis of GLK in four cotton species (Gossypium arboreum, G. raimondii, G. hirsutum, and G. barbadense) was conducted. A total of 198 GLK genes were identified in cotton. Conserved sequence analysis revealed that most GLK proteins contain two highly conserved domains: a MYB DNA-binding domain and a C-terminal (GCT) box. Promoter element analysis results show that the GLK gene family contains many stress response-related elements. Expression analysis demonstrated that GhGLK2, GhGLK11, GhGLK16, and GhGLK30 responded significantly to drought, salt, and temperature stresses. And GhGLK2, GhGLK13, GhGLK38, GhGLK42, and GhGLK46 responded significantly to cotton development. Yeast one-hybrid, yeast two-hybrid, and dual-luciferase assay results indicate that GhGLK2 interacts with GhGUN5, GhPIL6, GhNAC6, GhTPX2, and GhERF10. These findings suggest that these GhGLKs may play crucial roles in regulating the response to abiotic stress. Overall, this study provides a solid theoretical foundation for understanding the role of the GLK gene family in cotton’s response to abiotic stress. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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16 pages, 2425 KiB  
Article
The Crop Succession Systems Under No-Tillage Alters the Surface Layer Soil Carbon Stock and Stability
by Paloma Pimentel de Souza, Deivid Lopes Machado, Micael Silva de Freitas, Aracy Camilla Tardin Pinheiro Bezerra, Tiara Moraes Guimarães, Eder Marcos da Silva, Natanael Moreira do Nascimento, Rafael da Silva Borges, Vladimir Eliodoro Costa, Claudio Hideo Martins da Costa and Simério Carlos Silva Cruz
Agriculture 2024, 14(11), 2085; https://doi.org/10.3390/agriculture14112085 - 19 Nov 2024
Viewed by 399
Abstract
The main challenge of the no-tillage system (NTS) is to reconcile productivity, the maintenance of surface residues, and the stabilization of soil organic matter (SOM). To address this challenge, particularly in tropical regions, various cover crops have been tested. The objective of this [...] Read more.
The main challenge of the no-tillage system (NTS) is to reconcile productivity, the maintenance of surface residues, and the stabilization of soil organic matter (SOM). To address this challenge, particularly in tropical regions, various cover crops have been tested. The objective of this study was to test the effects of agricultural crop succession systems on the stock and stability of soil organic carbon in different surface layers of the soils. The research was carried out in the state of Goiás, Brazil, in an experiment set up in 2016, designed in randomized blocks with a split-plot scheme (treatments and soil layers), comprising four repetitions (blocks). The treatments (plots) consisted of crops grown in succession to soybean, which were as follows: T1—soybean/corn (Zea mays); T2—soybean/pearl millet (Pennisetum glaucum); T3—soybean/Urochloa ruziziensis (brachiaria); and T4—corn + Urochloa ruziziensis. The subplots represented the following soil layers: 0–5, 5–10, 10–20, and 20–40 cm. We evaluated the biomass dry mass and the soil parameters such as soil density, total porosity, and light organic matter across all layers. The organic carbon, grain size fractionation (mineral-associated organic carbon—MOC; sand-sized carbon—POC), and isotopic composition (δ13C) were determined in the 0–5 and 5–10 cm layers. The highest biomass dry production was observed in the soybean/pearl millet succession, which reduced the soil density and increased the total porosity in the surface layer. The soybean/pearl millet treatment produced high amounts of light organic matter, particularly in the 0–5 cm layer, a result also found for the soybean/brachiaria and soybean/corn + brachiaria systems. The crop successions did not alter the soil carbon stock or stability; however, the surface layer stored the highest amount of carbon, with elevated total organic carbon values and carbon stocks and stability (MOC and POC). Overall, in this study, replacing corn with other crops in succession with soybean did not affect the stock or stability of soil organic carbon. The species grown in succession with soybean contributed to the higher surface carbon stock and stability, promoting the formation of more stable and recalcitrant carbon. Full article
(This article belongs to the Special Issue Ecological Restoration of Degraded Soils in Sustainable Agriculture)
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17 pages, 2733 KiB  
Article
Mastitis Classification in Dairy Cows Using Weakly Supervised Representation Learning
by Soo-Hyun Cho, Mingyung Lee, Wang-Hee Lee, Seongwon Seo and Dae-Hyun Lee
Agriculture 2024, 14(11), 2084; https://doi.org/10.3390/agriculture14112084 - 19 Nov 2024
Viewed by 447
Abstract
Detecting mastitis on time in dairy cows is crucial for maintaining milk production and preventing significant economic losses, and machine learning has recently gained significant attention as a promising solution to address this issue. Most studies have detected mastitis on time series data [...] Read more.
Detecting mastitis on time in dairy cows is crucial for maintaining milk production and preventing significant economic losses, and machine learning has recently gained significant attention as a promising solution to address this issue. Most studies have detected mastitis on time series data using a supervised learning model, which requires the scale of labeled data; however, annotating the onset of mastitis in milking data from dairy cows is very difficult and costly, while supervised learning relies on accurate labels for ensuring the performance. Therefore, this study proposed a mastitis classification based on weakly supervised representation learning using an autoencoder on time series milking data, which allows for concurrent milking representation learning and weakly supervision with low-cost labels. The proposed method employed a structure where the classifier branches from the latent space of a 1D-convolutional autoencoder, enabling representation learning of milking data to be conducted from the perspective of reconstructing the original information and detecting mastitis. The branched classifier backpropagate the mastitis symptoms, which are less costly than mastitis diagnosis, during the encoder’s representation learning. The results showed that the proposed method achieved an F1-score of 0.6 that demonstrates performance comparable to previous studies despite using low-cost labels. Our method has the advantage of being easily reproducible across various data domains through low-cost annotation for supervised learning and is practical as it can be implemented with just milking data and weak labels, which can be collected in the field. Full article
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22 pages, 7322 KiB  
Article
Design and Parameter Optimization of a Rigid–Flexible Coupled Rod Tooth Threshing Device for Ratoon Rice Based on MBD-DEM
by Weijian Liu, Xuegeng Chen and Shan Zeng
Agriculture 2024, 14(11), 2083; https://doi.org/10.3390/agriculture14112083 - 19 Nov 2024
Viewed by 369
Abstract
To solve the problem of the high loss rate of threshing devices during the mechanical harvesting of ratoon rice, we propose a method using the principle of rigid–flexible coupling in this paper to reduce losses. Through analysis of the forces and collisions on [...] Read more.
To solve the problem of the high loss rate of threshing devices during the mechanical harvesting of ratoon rice, we propose a method using the principle of rigid–flexible coupling in this paper to reduce losses. Through analysis of the forces and collisions on ratoon rice grains during the threshing process, it has been confirmed that changing the structure and materials of the threshing contact components can effectively reduce grain loss. A rigid–flexible coupling rod tooth was designed, and the overall structural parameters of the device were determined based on force analysis results and dimensional boundary conditions. The MBD-DEM coupling method was used to simulate the threshing process, and the force conditions of the threshing rod teeth and threshing drum were obtained. The influence of the feeding amount and of the flexible body thickness on the crushing of ratoon rice grains was analyzed. In order to obtain the device’s optimal parameter combination, a three-factor quadratic regression orthogonal rotation combination experiment was conducted with drum speed, flexible body thickness, and rod tooth length as experimental factors. The optimization results showed that when the drum speed, flexible body thickness, and rod tooth length were 684 r/min, 3.86 mm, and 72.7 mm, respectively, the crushing rate, entrainment loss rate, and uncleaned rate were 1.260%, 2.132%, and 1.241%, respectively. The bench test showed that it is feasible to use the MBD–DEM coupling method to measure the motion and force of ratoon rice. The rigid–flexible coupling threshing device can reduce the grain crushing rate while ensuring grain cleanliness. Compared with traditional threshing devices, the crushing rate and entrainment loss rate of the rigid–flexible coupling threshing device were reduced by 55.7% and 27.5%, respectively. The research results can provide a reference for the design of threshing devices for ratoon rice harvesters. Full article
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14 pages, 2453 KiB  
Article
Dead Broiler Detection and Segmentation Using Transformer-Based Dual Stream Network
by Gyu-Sung Ham and Kanghan Oh
Agriculture 2024, 14(11), 2082; https://doi.org/10.3390/agriculture14112082 - 19 Nov 2024
Viewed by 403
Abstract
Improving productivity in industrial farming is crucial for precision agriculture, particularly in the broiler breeding sector, where swift identification of dead broilers is vital for preventing disease outbreaks and minimizing financial losses. Traditionally, the detection process relies on manual identification by farmers, which [...] Read more.
Improving productivity in industrial farming is crucial for precision agriculture, particularly in the broiler breeding sector, where swift identification of dead broilers is vital for preventing disease outbreaks and minimizing financial losses. Traditionally, the detection process relies on manual identification by farmers, which is both labor-intensive and inefficient. Recent advances in computer vision and deep learning have resulted in promising automatic dead broiler detection systems. In this study, we present an automatic detection and segmentation system for dead broilers that uses transformer-based dual-stream networks. The proposed dual-stream method comprises two streams that reflect the segmentation and detection networks. In our approach, the detection network supplies location-based features of dead broilers to the segmentation network, aiding in the prevention of live broiler mis-segmentation. This integration allows for more accurate identification and segmentation of dead broilers within the farm environment. Additionally, we utilized the self-attention mechanism of the transformer to uncover high-level relationships among the features, thereby enhancing the overall accuracy and robustness. Experiments indicated that the proposed approach achieved an average IoU of 88% on the test set, indicating its strong detection capabilities and precise segmentation of dead broilers. Full article
(This article belongs to the Section Digital Agriculture)
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23 pages, 2863 KiB  
Article
The Role of Sodium Alginate Hydrogel in Maintaining Soil Homeostasis Exposed to Sulcotrione
by Małgorzata Baćmaga, Jadwiga Wyszkowska and Jan Kucharski
Agriculture 2024, 14(11), 2081; https://doi.org/10.3390/agriculture14112081 - 19 Nov 2024
Viewed by 382
Abstract
Herbicides are the most widely used agrochemicals in crop protection, which has led to serious environmental pollution around the world, including soil ecosystems. It is important to look for new solutions that lead to an improvement in soil quality, even if only through [...] Read more.
Herbicides are the most widely used agrochemicals in crop protection, which has led to serious environmental pollution around the world, including soil ecosystems. It is important to look for new solutions that lead to an improvement in soil quality, even if only through the use of hydrogels. The aim of this study was therefore to determine the effect of sodium alginate on the microbiological and biochemical properties of sulcotrione-treated soil. It was found that both the herbicide and the sodium alginate had a significant effect on the soil environment. An amount of 10 g kg−1 of sodium alginate was applied to the soil, while sulcotrione was applied to the soil in the following amounts: 0.00 (C), 0.200 (R), 0.999 (5R), and 9.999 mg kg−1 (50R). Sulcotrione stimulated the activity of dehydrogenases, catalase, arylsulfatase, and β-glucosidase and inhibited the activities of alkaline phosphatase, acid phosphatase, and urease as well as the proliferation of organotrophic bacteria, actinobacteria, and fungi. This caused an increase in the colony development index (CD) of organotrophic bacteria and fungi and decreased the colony development index value of actinobacteria. It also increased the value of the ecophysiological diversity index (EP) of fungi. The addition of sodium alginate to the soil increased the numbers of organotrophic bacteria, actinobacteria, and fungi as well as the activities of dehydrogenases, catalase, urease, alkaline phosphatase, and arylsulfatase. The hydrogel had different effects on β-glucosidase activity. Acid phosphatase showed a significant decrease in activity after the addition of sodium alginate to the soil. Under the influence of sodium alginate, there was an increase in the index of colony development of actinobacteria and fungi, while there were decreases in organotrophic bacteria and the index of ecophysiological diversity of actinobacteria and fungi. The proliferation of microorganisms and the enzymatic activity of the soil changed over time both in soil enriched with sodium alginate and without its addition. This study may be useful for evaluating the effects of sulcotrione on the microbiological and biochemical properties of soil and the effectiveness of sodium alginate in improving the quality of soil exposed to sulcotrione. Full article
(This article belongs to the Section Agricultural Soils)
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17 pages, 1342 KiB  
Article
Study on the Mechanism of Agricultural Greenhouse Gas Emission Reduction Under Macro Emission Reduction Measures
by Zeyu Gong and Xuexi Huo
Agriculture 2024, 14(11), 2080; https://doi.org/10.3390/agriculture14112080 - 19 Nov 2024
Viewed by 387
Abstract
Clarifying the impact of macro emission reduction measures on the mechanism of agricultural greenhouse gas emission reduction is of great significance in promoting climate change governance and the construction of a carbon emission reduction policy system. This paper explores the mechanism of important [...] Read more.
Clarifying the impact of macro emission reduction measures on the mechanism of agricultural greenhouse gas emission reduction is of great significance in promoting climate change governance and the construction of a carbon emission reduction policy system. This paper explores the mechanism of important macro emission reduction measures based on a multi-level progressive factor decomposition perspective and designs a coupled model of computable general equilibrium and structural path decomposition to identify the key emission reduction paths of major macro emission reduction measures and to decompose the drivers that promote emission reduction in each path. This study found that: (1) The emission reduction effect of the combination of carbon tax, carbon sink and carbon capture, utilization, and storage macro emission reduction measures is dominated by the indirect emission reduction triggered by the industrial chain, accounting for 95.67% of the total agricultural GHG emission reduction, and the emission reduction effect is gradually weakened with the increase in the production level. (2) The emission intensity effect and the industrial structure effect are the main drivers of the macro emission reduction portfolio measures to promote emission reduction, but there are differences in the roles of the different drivers on the various production levels and different emission reduction pathways. (3) Vegetables, fertilizers, the light industry, and other key industries are the main agricultural greenhouse gas emission reduction contributing industries, of which the emission reduction contribution from citizen consumption is the largest, and the emission reduction is mainly achieved by influencing the demand path of the vegetable industry and the light industry to the upstream high-energy-consuming or high-emission industries. Therefore, there is a need to fully utilize the mechanisms that drive emission reduction at different production levels and pathways by each key factor and to take targeted measures to promote synergistic emission reduction among industries. In the short term, focus on enhancing the role of the emission intensity effect, while in the medium and long term, pay much attention to the positive role of the industrial structure effect on agricultural greenhouse gas emissions. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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13 pages, 1317 KiB  
Article
Light Intensity Effects on Productivity and Post-Harvest Quality in Perilla frutescens Cultivated in CEA
by Akvilė Viršilė, Ieva Gudžinskaitė, Kristina Laužikė, Gediminas Kudirka, Audrius Pukalskas and Giedrė Samuolienė
Agriculture 2024, 14(11), 2079; https://doi.org/10.3390/agriculture14112079 - 19 Nov 2024
Viewed by 460
Abstract
Leafy vegetables, mainly lettuces, are currently the main crop cultivated in controlled environment agriculture (CEA), including vertical farming and plant factories. There is a rising demand to expand this portfolio with a wider variety of underutilized edible plants containing various bioactive compounds and [...] Read more.
Leafy vegetables, mainly lettuces, are currently the main crop cultivated in controlled environment agriculture (CEA), including vertical farming and plant factories. There is a rising demand to expand this portfolio with a wider variety of underutilized edible plants containing various bioactive compounds and sensory properties seeking to enrich human diets. However, the optimal cultivation conditions for these underutilized plants significantly differ from those optimized for lettuce, basil, and other popular CEA crops. Therefore, this study aims to explore the impacts of light-emitting diode (LED) lighting intensity (photosynthetic photon flux density, PPFD) on green leaf Perilla frutescens cultivated in CEA. Plants were grown under four levels of LED lighting PPFDs from 150 to 300 µmol m−2s−1 for 4 weeks. Plant biomass productivity, soluble sugar contents, antioxidant properties (DPPH, ABTS free radical scavenging activities, FRAP antioxidant power), and total contents of phenolic compounds in leaves were evaluated at harvesting time. Further, harvested plant material was stored in the dark, at +6 °C, and the water content, water loss and transpiration rate, leaf sugar contents, and antioxidant properties were monitored 1, 3, and 5 days after harvesting. The summarized data suggest that higher cultivation lighting PPFD results in better harvest quality preservation during post-harvest storage. Full article
(This article belongs to the Special Issue Impact of Light on Horticultural Crops—2nd Edition)
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15 pages, 4980 KiB  
Article
Sensorless Design and Analysis of a Brushed DC Motor Speed Regulation System for Branches Sawing
by Shangshang Cheng, Huijun Zeng, Zhen Li, Qingting Jin, Shilei Lv, Jingyuan Zeng and Zhou Yang
Agriculture 2024, 14(11), 2078; https://doi.org/10.3390/agriculture14112078 - 19 Nov 2024
Viewed by 441
Abstract
Saw rotational speed critically influences cutting force and surface quality yet is often destabilized by variable cutting resistance. The sensorless detection method for calculating rotational speed based on current ripple can prevent the contact of wood chips and dust with Hall sensors. This [...] Read more.
Saw rotational speed critically influences cutting force and surface quality yet is often destabilized by variable cutting resistance. The sensorless detection method for calculating rotational speed based on current ripple can prevent the contact of wood chips and dust with Hall sensors. This paper introduces a speed control system for brushed DC motors that capitalizes on the linear relationship between current ripple frequency and rotational speed. The system achieves speed regulation through indirect speed measurement and PID control. It utilizes an H-bridge circuit controlled by the EG2014S driver chip to regulate the motor direction and braking. Current ripple detection is accomplished through a 0.02 Ω sampling resistor and AMC1200SDUBR signal amplifier, followed by a wavelet transform and Savitzky–Golay filtering for refined signal extraction. Experimental results indicate that the system maintains stable speeds across the 2000–6000 RPM range, with a maximum error of 2.32% at 6000 RPM. The improved ripple detection algorithm effectively preserves critical signals while reducing noise. This enables the motor to quickly regain speed when resistance is encountered, ensuring a smooth cutting surface. Compared to traditional Hall sensor systems, this sensorless design enhances adaptability in agricultural applications. Full article
(This article belongs to the Special Issue New Energy-Powered Agricultural Machinery and Equipment)
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18 pages, 2147 KiB  
Article
Evaluating the Environmental and Economic Benefits of New Technologies in Low-Salt Olive Fermentation
by Alexandra Mari, Tryfon Kekes, Christos Boukouvalas, Christina Drosou, Magdalini Krokida and Christos Tsartsaris
Agriculture 2024, 14(11), 2077; https://doi.org/10.3390/agriculture14112077 - 19 Nov 2024
Viewed by 434
Abstract
The evolving modern lifestyle influences consumer dietary habits, driving the demand for new food products rooted in traditional healthy foods with greater health benefits. The Mediterranean diet, characterized by low animal fat intake and high vegetable consumption, has been shown to protect against [...] Read more.
The evolving modern lifestyle influences consumer dietary habits, driving the demand for new food products rooted in traditional healthy foods with greater health benefits. The Mediterranean diet, characterized by low animal fat intake and high vegetable consumption, has been shown to protect against heart disease, cancer, and obesity. Fermented olives, integral to this diet, are known for their high phenolic content, antioxidant activity, and beneficial unsaturated fatty acids. This study evaluates the environmental and economic benefits of integrating alternative/effective technologies, such as osmotic dehydration and edible coating, into conventional olive production processes, aiming to develop traditional Greek table olives with reduced salt content, enhanced nutritional characteristics, and extended shelf life. A Life Cycle Assessment (LCA) analysis was conducted following the ISO 14040 and 14044 guidelines, adopting the ReCiPe 2016 (H) impact assessment methodology. Additionally, a preliminary economic evaluation including detailed planning, cost estimation, and process simulation was conducted. The results indicate significant environmental and economic advantages of the studied methods, despite more resources being required, making it a sustainable and promising approach for the production of high-quality fermented olives. Full article
(This article belongs to the Special Issue Feature Papers in Agricultural Product Quality and Safety)
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23 pages, 13244 KiB  
Article
Model for Inverting the Leaf Area Index of Green Plums by Integrating IoT Environmental Monitoring Data and Leaf Relative Content of Chlorophyll Values
by Caili Yu, Haiyang Tong, Daoyi Huang, Jianqiang Lu, Jiewei Huang, Dejing Zhou and Jiaqi Zheng
Agriculture 2024, 14(11), 2076; https://doi.org/10.3390/agriculture14112076 - 18 Nov 2024
Viewed by 442
Abstract
The quantitative inversion of the leaf area index (LAI) of green plum trees is crucial for orchard field management and yield prediction. The data on the relative content of chlorophyll (SPAD) in leaves and environmental data from orchards show a significant correlation with [...] Read more.
The quantitative inversion of the leaf area index (LAI) of green plum trees is crucial for orchard field management and yield prediction. The data on the relative content of chlorophyll (SPAD) in leaves and environmental data from orchards show a significant correlation with LAI. Effectively integrating these two data types for LAI inversion is important to explore. This study proposes a multi−source decision fusion LAI inversion model for green plums based on their adjusted determination coefficient (MDF−ADRS). First, three statistical methods—Pearson, Spearman rank, and Kendall rank correlation analyses—were used to measure the linear relationships between variables, and the six environmental factors most highly correlated with LAI were selected from the orchard’s environmental data. Then, using multivariate statistical analysis methods, LAI inversion models based on environmental feature factors (EFs−PM) and SPAD (SPAD−PM) were established. Finally, a weight optimization allocation strategy was employed to achieve a multi−source decision fusion LAI inversion model for green plums. This strategy adaptively allocates weights based on the predictive performance of each data source. Unlike traditional models that rely on fixed weights or a single data source, this approach allows the model to increase the influence of a key data source when its predictive strength is high and reduce noise interference when it is weaker. This dynamic adjustment not only enhances the model’s robustness under varying environmental conditions but also effectively mitigates potential biases when a particular data source becomes temporarily unreliable. Our experimental results show that the MDF−ADRS model achieves an R2 of 0.88 and an RMSE of 0.39 in the validation set, outperforming other fusion methods. Compared to the EFs−PM and SPAD−PM models, the R2 increased by 0.19 and 0.26, respectively, and the RMSE decreased by 0.16 and 0.22. This model effectively integrates multiple sources of data from green plum orchards, enabling rapid inversion and improving the accuracy of green plum LAI estimation, providing a technical reference for monitoring the growth and managing the production of green plums. Full article
(This article belongs to the Section Digital Agriculture)
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18 pages, 6120 KiB  
Article
Modeling and Parameter Selection of the Corn Straw–Soil Composite Model Based on the DEM
by Tianyue Xu, Yan Gou, Dongyan Huang, Jianqun Yu, Chunrong Li and Jingli Wang
Agriculture 2024, 14(11), 2075; https://doi.org/10.3390/agriculture14112075 - 18 Nov 2024
Viewed by 492
Abstract
During corn harvesting operations, machine–straw–soil contact often occurs, but there is a lack of research related to the role of straw–soil contact. Therefore, in this study, a composite contact model of corn straw‒soil particles was established based on the discrete element method (DEM). [...] Read more.
During corn harvesting operations, machine–straw–soil contact often occurs, but there is a lack of research related to the role of straw–soil contact. Therefore, in this study, a composite contact model of corn straw‒soil particles was established based on the discrete element method (DEM). First, the discrete element Hertz‒Mindlin method with bonding particle contact was used to establish a numerical model of the double-bonded bimodal distribution of corn straw, and bonding particle models of the outer skin‒outer skin, inner pulp‒inner pulp, and outer skin‒inner pulp were developed. The nonhomogeneous and deformable material properties were accurately expressed. The straw compression test combined with simulation calibration was used to determine some of the bonding contact parameters by means of the PB (Plackett–Burman) test, the steepest ascent test, and the BB (Box–Behnken) test. Additionally, Additionally, the Hertz-Mindlin with JKR (Johnson-Kendall-Roberts) + bonding key model was used to establish the numerical model of the soil particles, which was used to describe the irregularity and adhesion properties of the soil particles. The geometric model of the soil particles was established using the multisphere filling method. Finally, a composite contact model of corn straw‒soil particles was established, the contact parameters between straw and soil were calibrated via collision tests, inclined tests and inclined rolling tests, and the established composite contact model was further verified through direct shear tests between straw and soil. A theoretical foundation for the optimal design of equipment linked to maize harvesting is provided by this work. Full article
(This article belongs to the Section Agricultural Technology)
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17 pages, 2766 KiB  
Article
Scenario-Based Modeling of Agricultural Nitrous Oxide Emissions in China
by Miaoling Bu, Weiming Xi, Yu Wang and Guofeng Wang
Agriculture 2024, 14(11), 2074; https://doi.org/10.3390/agriculture14112074 - 18 Nov 2024
Viewed by 580
Abstract
Agricultural land in China represents a major source of nitrous oxide (N2O) emissions, and as population growth and technological advancements drive agricultural intensification, these emissions are projected to increase. A thorough understanding of historical trends and future dynamics of these emissions [...] Read more.
Agricultural land in China represents a major source of nitrous oxide (N2O) emissions, and as population growth and technological advancements drive agricultural intensification, these emissions are projected to increase. A thorough understanding of historical trends and future dynamics of these emissions is critical for formulating effective mitigation strategies and advancing progress toward the Sustainable Development Goals. This study quantifies N2O emissions across 31 provinces in China from 2000 to 2021, employing the IPCC coefficient method alongside China’s provincial greenhouse gas inventory guidelines. The spatiotemporal evolution of emission intensities was examined, with the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model employed to assess the influence of population, technological development, economic growth, and energy structure. The findings confirm that agricultural land remains the primary source of N2O emissions, with significantly higher levels observed in eastern coastal regions compared to western inland areas. Implementing targeted mitigation strategies, such as enhanced agricultural- and manure-management practices and region-specific interventions, is imperative to effectively curb the rising emission trends. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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14 pages, 2486 KiB  
Article
Environmental Efficiency of Agriculture in Visegrád Group Countries vs. the EU and the World
by Arkadiusz Sadowski, Natalia Genstwa-Namysł, Jagoda Zmyślona and Luboš Smutka
Agriculture 2024, 14(11), 2073; https://doi.org/10.3390/agriculture14112073 - 18 Nov 2024
Viewed by 466
Abstract
The production of foodstuffs for an ever-increasing population is the basic, irreducible and unalienable function of agriculture. It involves environmental impacts, including greenhouse gas emissions. This is what makes it so important to examine the levels of environmental efficiency of agriculture. As countries [...] Read more.
The production of foodstuffs for an ever-increasing population is the basic, irreducible and unalienable function of agriculture. It involves environmental impacts, including greenhouse gas emissions. This is what makes it so important to examine the levels of environmental efficiency of agriculture. As countries differ in their emission levels, it is reasonable to look for what determines them. Hence, the purpose of this study was to identify the changes in the environmental efficiency of agriculture in Visegrád Group countries and worldwide in 1961–2020. These countries share a similar economic history and demonstrate comparable environmental and geographic conditions, making it possible to pinpoint the factors responsible for how the parameters covered by the study change over time. The research used data from the FAOSTAT database. Environmental efficiency of agriculture was defined as the relationship between production volumes in kilocalories and emissions. Initially, this parameter deteriorated in the Visegrád countries, but since the late 1970s it has improved, first linked to the crisis of the socialist economy and its collapse (including a drastic decline in livestock production) and then to the implementation of CAP instruments. Full article
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
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19 pages, 12970 KiB  
Article
Integrated Transcriptome and Metabolomics Analysis Reveals That Probiotics and Tea Polyphenols Synergetically Regulate Lipid Metabolism in Laying Hens
by Ming Qin, Cai Ma, Zengguang Wang, Mingzhi Liang, Yufen Sha, Jiewei Liu, Shunjin Ge, Longzong Guo and Ruili Li
Agriculture 2024, 14(11), 2072; https://doi.org/10.3390/agriculture14112072 - 18 Nov 2024
Viewed by 566
Abstract
Tea polyphenols (TP) and probiotics (PB) have been recognized for their ability to improve lipid metabolism and regulate immune function. However, their specific impact on lipid metabolism in laying hens has not been thoroughly elucidated. Therefore, this study sought to examine the effect [...] Read more.
Tea polyphenols (TP) and probiotics (PB) have been recognized for their ability to improve lipid metabolism and regulate immune function. However, their specific impact on lipid metabolism in laying hens has not been thoroughly elucidated. Therefore, this study sought to examine the effect of TP and Bacillus subtilis on lipid metabolism in laying hens through transcriptome and metabolome analyses. Two hundred Hy-line Brown layers were randomly allocated into four groups with supplemental dietary TP and PB alone and their combination for 8 weeks. Each treatment had 10 replicates of five birds. Supplementation with a TP and PB combination (TP-PB) increased redness (a*) (p < 0.05) compared to the control basal diet (CT). Dietary TP-PB decreased egg yolk and serum total cholesterol (TC) concentrations (p < 0.05) without affecting the content of total bile acid (TBA). The combined use of TP and PB significantly improved hepatic fatty acid synthetase (FAS) activity (p < 0.05) and reduced liver fat particles. Dietary TP-PB primarily influenced the transcript levels of genes involved in fat metabolic pathways. In particular, TP-PB supplementation reduced lipid storage by activating the Notch signaling pathway. Furthermore, the addition of TP-PB in the diet modulated the abundance of metabolic biomarkers associated with bile secretion and valine, leucine, and isoleucine degradation. An interaction network of mRNAs and metabolites was constructed associated with lipid metabolism, such as deoxycholic acid, TAG (14:3–14:3–20:5), PDK4, and HES4. Overall, these findings emphasized the potential health advantages of the TP and PB combination as a possible functional feed supplement in livestock nutrition. Full article
(This article belongs to the Section Farm Animal Production)
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15 pages, 4674 KiB  
Article
Research on Automatic Alignment for Corn Harvesting Based on Euclidean Clustering and K-Means Clustering
by Bin Zhang, Hao Xu, Kunpeng Tian, Jicheng Huang, Fanting Kong, Senlin Mu, Teng Wu, Zhongqiu Mu, Xingsong Wang and Deqiang Zhou
Agriculture 2024, 14(11), 2071; https://doi.org/10.3390/agriculture14112071 - 18 Nov 2024
Viewed by 391
Abstract
Aiming to meet the growing need for automated harvesting, an automatic alignment method based on Euclidean clustering and K-means clustering is proposed to address issues of driver fatigue and inaccurate driving in manually operated corn harvesters. Initially, the corn field environment is scanned [...] Read more.
Aiming to meet the growing need for automated harvesting, an automatic alignment method based on Euclidean clustering and K-means clustering is proposed to address issues of driver fatigue and inaccurate driving in manually operated corn harvesters. Initially, the corn field environment is scanned using LiDAR to obtain point cloud data, which are then subjected to pass-through filtering and statistical filtering to remove noise and non-corn contour points. Subsequently, Euclidean clustering and K-means clustering methods are applied to the filtered point cloud data. To validate the impact of Euclidean clustering on subsequent clustering, two separate treatments of the obtained point cloud data were conducted during experimental validation: the first used the K-means clustering algorithm directly, while the second involved performing Euclidean clustering followed by K-means clustering. The results demonstrate that the combined method of Euclidean clustering and K-means clustering achieved a success rate of 81.5%, representing a 26.5% improvement over traditional K-means clustering. Additionally, the Rand index increased by 0.575, while accuracy improved by 57% and recall increased by 61%. Full article
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28 pages, 12256 KiB  
Article
Design and Testing of a Small-Scale Composting Facility for Sheep Manure Utilizing Aeration and Thermal Treatment
by Jian Wang, Kailin Ren and Longfei Zhang
Agriculture 2024, 14(11), 2070; https://doi.org/10.3390/agriculture14112070 - 18 Nov 2024
Viewed by 482
Abstract
Inner Mongolia has the largest sheep population among China’s provinces, resulting in the production of a substantial amount of sheep manure. If left untreated, this manure can contribute to environmental pollution. However, sheep manure serves a dual purpose: it can be both a [...] Read more.
Inner Mongolia has the largest sheep population among China’s provinces, resulting in the production of a substantial amount of sheep manure. If left untreated, this manure can contribute to environmental pollution. However, sheep manure serves a dual purpose: it can be both a pollutant and a valuable source of organic fertilizer. Consequently, there is an urgent need to address the environmental issues arising from manure accumulation and its unused status. In this paper, a viable solution is proposed: the conversion of manure into fertilizer through a composting unit incorporating high-temperature aerobic fermentation technology. This unit, tailored for small farms and individual farmers, integrates critical functions such as ventilation, heating, and turning. Additionally, it boasts excellent thermal insulation, enhancing composting efficiency and enabling precise control over fermentation conditions. This design mitigates heat loss and accelerates maturation, addressing common challenges in traditional composting. The design process encompassed both equipment construction and control systems, with a primary focus on compost fermentation and aeration heating. The components were carefully designed or selected based on theoretical analysis and subsequently validated using simulation software, including EDEM and Fluent. The control system seamlessly integrates a touch screen interface, PLC programming, and control circuits to manage air pumps and electric heaters in response to changes in temperature and oxygen concentration. Furthermore, it controls the motors during the recovery phase. A comprehensive performance evaluation was conducted, revealing notable improvements. Under artificially heated conditions, the maximum temperature of the compost increased by approximately 20 °C, the composting cycle was reduced by roughly 4 days, and the seed germination index (GI) rose by about 9% when compared to natural fermentation. Thus, this device significantly accelerates composting and improves fertilizer quality by increasing the decomposition rate. Full article
(This article belongs to the Section Agricultural Technology)
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15 pages, 4337 KiB  
Article
Identification of Two R2R3-MYB Genes Involved in Flavan-3-Ols Biosynthesis as Modulated by Salicylic Acid Through RNA-Seq in Grape Berries (Vitis spp.)
by Fengchan Yu, Pengfei Zhai, Wenjing Ge, Runtian Zhou, Shuwen Zan, Jinjun Liang, Pengfei Wen and Yu Gary Gao
Agriculture 2024, 14(11), 2069; https://doi.org/10.3390/agriculture14112069 - 17 Nov 2024
Viewed by 498
Abstract
Flavan-3-ols are plant secondary metabolites that play important roles in stress resistance. Our previous studies revealed that salicylic acid (SA) activates R2R3-MYB transcription factors, promoting flavan-3-ol biosynthesis. This study identified two R2R3-MYB genes that exhibited positive responses to both exogenous SA and were [...] Read more.
Flavan-3-ols are plant secondary metabolites that play important roles in stress resistance. Our previous studies revealed that salicylic acid (SA) activates R2R3-MYB transcription factors, promoting flavan-3-ol biosynthesis. This study identified two R2R3-MYB genes that exhibited positive responses to both exogenous SA and were probably involved in flavan-3-ol biosynthesis through RNA-sequencing, functional enrichment analysis, and qRT-PCR. The results indicated that the contents of total flavan-3-ols and their monomers, (+)-catechin and (−)-epicatechin, in grape berries after exogenous SA application were substantially increased compared to those in the control. A total of 683 differentially expressed genes in response to exogenous SA treatment were identified using RNA-seq. KEGG analysis revealed enrichment of the ‘flavonoid biosynthesis’ and ‘plant hormone signal transduction’ pathways. A specific module highly associated with flavan-3-ol biosynthesis was identified by constructing a co-expression network. Two candidate genes (VvMYB108B and VvMYB145) likely participating in flavan-3-ol biosynthesis were selected using qRT-PCR. Therefore, these two potential genes that respond to SA and putatively participate in flavan-3-ol biosynthesis were identified for the first time. These results lay a solid basis for a more profound understanding of the molecular regulation of flavan-3-ol biosynthesis in grapes. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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24 pages, 5384 KiB  
Article
Small Farmers’ Agricultural Practices and Adaptation Strategies to Perceived Soil Changes in the Lagoon of Venice, Italy
by Tiziana Floridia, Julia Prakofjewa, Luigi Conte, Giulia Mattalia, Raivo Kalle and Renata Sõukand
Agriculture 2024, 14(11), 2068; https://doi.org/10.3390/agriculture14112068 - 16 Nov 2024
Viewed by 785
Abstract
Farmers have a pivotal responsibility in soil conservation: they can either preserve or deplete it through their choices. The responsibility of agriculture increases when practised in delicate ecosystems, such as lagoonal ones. The Venetian Lagoon islands, which are increasingly subjected to natural and [...] Read more.
Farmers have a pivotal responsibility in soil conservation: they can either preserve or deplete it through their choices. The responsibility of agriculture increases when practised in delicate ecosystems, such as lagoonal ones. The Venetian Lagoon islands, which are increasingly subjected to natural and anthropic subsidence, occasional flooding events (acqua alta), and eustatic sea level rise, are constantly exposed to erosive processes that challenge farmers to play with their adaptive capability. This research was carried out on the islands of Sant’Erasmo and Vignole, the most representative of island agriculture in the Venetian Lagoon: they almost exclusively rely on agriculture, which is almost nil in the other islands. This empirical research aimed to explore farmers’ agricultural practices, perceptions of soil changes, and how they adapt to them. It was fundamental for this study that the field research involved direct human contact with farmers (through semi-structured interviews) for data collection and using qualitative methods for data analysis, integrating scientific and non-scientific forms of knowledge and actors. The final purpose was to demonstrate the sustainability (valued on the potential depletion or regeneration capability) of agricultural practices and adaptation strategies on a theoretical basis. Despite their polycultural landscape (maintained by low-input farming systems), escaped from the predominant landscape oversimplification, Sant’Erasmo and Vignole are also subjected to unsustainable agricultural practices, including heavy mechanisation and synthetic inputs. Coupled with natural soil salinity that is exacerbated by increasing drought periods, these practices can contribute to soil degradation and increased salinity. The reported adaptation strategies, such as zeroed, reduced, or more conscious use of machines, were guided by the need to reduce the negative impact of soil changes on productivity. Our research revealed some of them as sustainable and others as unsustainable (such as increasing irrigation to contrast soil salinity). Participatory action research is needed to support farmers in designing effective sustainable agricultural practices and adaptation strategies. Full article
(This article belongs to the Special Issue Regenerative Agriculture: Farming with Benefit)
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20 pages, 4501 KiB  
Article
Study on Path Planning in Cotton Fields Based on Prior Navigation Information
by Meng Wang, Changhe Niu, Zifan Wang, Yongxin Jiang, Jianming Jian and Xiuying Tang
Agriculture 2024, 14(11), 2067; https://doi.org/10.3390/agriculture14112067 - 16 Nov 2024
Viewed by 439
Abstract
Aiming at the operation scenario of existing crop coverage and the need for precise row alignment, the sowing prior navigation information of cotton fields in Xinjiang was used as the basis for the study of path planning for subsequent operations to improve the [...] Read more.
Aiming at the operation scenario of existing crop coverage and the need for precise row alignment, the sowing prior navigation information of cotton fields in Xinjiang was used as the basis for the study of path planning for subsequent operations to improve the planning quality and operation accuracy. Firstly, the characteristics of typical turnaround methods were analyzed, the turnaround strategy for dividing planning units was proposed, and the horizontal and vertical operation connection methods were put forward. Secondly, the obstacle avoidance strategies were determined according to the traits of obstacles. The circular arc–linear and cubic spline curve obstacle avoidance path generation methods were proposed. Considering the dual attributes of walking and the operation of agricultural machinery, four kinds of operation semantic points were embedded into the path. Finally, path generation software was designed. The simulation and field test results indicated that the operation coverage ratio CR ≥ 98.21% positively correlated with the plot area and the operation distance ratio DR ≥ 86.89% when non-essential reversing and obstacles were ignored. CR and DR were negatively correlated with the number of obstacles when considering obstacles. When considering non-essential reversing, the full coverage of operating rows could be achieved, but DR would be reduced correspondingly. Full article
(This article belongs to the Section Agricultural Technology)
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