Agriculture

15 pages, 1434 KiB

Open AccessArticle

Cell Recycling Application in Single-Stage and Sequential-Stage Co-Production of Xylitol and Ethanol Using Corn Cob Hydrolysates

by Kritsadaporn Porninta, Chatchadaporn Mahakuntha, Julaluk Khemacheewakul, Charin Techapun, Yuthana Phimolsiripol, Pornchai Rachtanapun, Kittisak Jantanasakulwong, Juan Feng, Su Lwin Htike, Rojarej Nunta, **nshu Zhuang, Wen Wang, Wei Qi, Zhongming Wang, Sumeth Sommanee and Noppol Leksawasdi

Agriculture 2024, 14(7), 1062; https://doi.org/10.3390/agriculture14071062 (registering DOI) - 30 Jun 2024

Abstract

A sustainable bioeconomy in agricultural and agro-industrial production must inevitably involve the sustainable use of agricultural residues through zero-waste processes. Corn cob is considered crucial agricultural waste as 278 and 293 million tons were produced worldwide in 2022 and 2023, respectively. Corn cob [...] Read more.

A sustainable bioeconomy in agricultural and agro-industrial production must inevitably involve the sustainable use of agricultural residues through zero-waste processes. Corn cob is considered crucial agricultural waste as 278 and 293 million tons were produced worldwide in 2022 and 2023, respectively. Corn cob hydrolysates, which are abundant in xylose and glucose, could be efficiently utilized for xylitol and ethanol production through the cultivation of recycling the yeast strain Candida magnoliae TISTR 5664 in the single-stage and sequential-stage co-production of these products. The statistically significant maxima (p ≤ 0.05) ethanol concentrations were improved by 7.8% (49.9–51.7 g/L or 91.3–95.6% of the theoretical) from the single stage of ethanol production employing recycled cells and 9.9% (50.9–54.1 g/L or 77.3–83.9% of the theoretical) from the second step of sequential-stage co-production using recycled cells without xylitol accumulation. Conversely, the single-stage xylitol production utilizing recycled cells under microaerobic conditions resulted in a statistically significant lower (p ≤ 0.05) xylitol concentration by two folds relative to the control, while ethanol concentration was elevated by almost double. The statistically significant maximum (p ≤ 0.05) xylitol was achieved at 25.9 g/L (58.6% of the theoretical) when sequential-stage co-production was initiated in the first step with fresh inoculum only and not recycled cells. The sequential-stage co-production of xylitol and ethanol presented the potential for statistically significant improvement (p ≤ 0.05) of both xylitol and ethanol production processes. Full article

(This article belongs to the Special Issue Agricultural Waste—Status and Future Prospects)

12 pages, 3465 KiB

Open AccessArticle

A Two-Year Study of Bioorganic Fertilizer on the Content of Pb and as in Brown Rice and Rice Yield in a Contaminated Paddy Field

by Huaidong He, Jun Zhou, Anwen **ao, Yehan Yan, Aimin Chen and Bangxing Han

Agriculture 2024, 14(7), 1061; https://doi.org/10.3390/agriculture14071061 (registering DOI) - 30 Jun 2024

Abstract

Bioorganic fertilizer (BOF) represents favorable potential for agricultural production, but the safe and residual effects of BOF application in heavy-metal-contaminated soils still remain unclear. A two-year field experiment of four rice-growing cycles were conducted to study the effects of the one-time addition of [...] Read more.

Bioorganic fertilizer (BOF) represents favorable potential for agricultural production, but the safe and residual effects of BOF application in heavy-metal-contaminated soils still remain unclear. A two-year field experiment of four rice-growing cycles were conducted to study the effects of the one-time addition of BOF (low and high dosages, 0.45 and 0.9 kg/m², namely, BOF1 and BOF2, respectively) on the lead (Pb) and arsenic (As) accumulations in brown rice, rice yield, and soil properties in an acidic and Pb-As-contaminated paddy field. The results show that BOF application enhanced the rice yields by 7.9–25.5% and increased the soil pH, organic carbon contents, and fluorescein diacetate hydrolase activity in the former two rice-growing cycles, while these attributes declined gradually and were not significant in the last two cycles. The soil bulk density decreased marginally due to the BOF. Furthermore, the BOF1 treatment barely affected the rice Pb and As concentrations during all cycles, whereas the BOF2 treatment clearly increased the Pb concentrations in brown rice, exceeding the food quality standard limit of 0.2 mg/kg in the last three cycles, and slightly increased the rice As in the former three cycles. The BOF effects on Pb and As in brown rice were due to the changes in the available soil Pb and As, respectively. Our results indicate that a one-time application of BOF could ameliorate the soil conditions of rice growth in two rice-growing cycles, while the high-dose BOF seemed undesirable in toxic-metal-contaminated soils. BOF application at the rate of 0.45 kg/m² per annum may be a potential strategy for safe rice production in Pb-As-contaminated fields. Full article

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

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26 pages, 2026 KiB

Open AccessReview

Meat of Sheep: Insights into Mutton Evaluation, Nutritive Value, Influential Factors, and Interventions

by Wenli Ding, Yanan Lu, Bowen Xu, Pan Chen, Aoyun Li, Fuchun Jian, Guangqing Yu and Shucheng Huang

Agriculture 2024, 14(7), 1060; https://doi.org/10.3390/agriculture14071060 (registering DOI) - 30 Jun 2024

Abstract

Meat from sheep offers an abundance of essential amino acids and trace elements essential for optimal human health and a delectable culinary delight. Because it has fewer calories and a lower cholesterol content than other meats, this succulent meat is not only delicious [...] Read more.

Meat from sheep offers an abundance of essential amino acids and trace elements essential for optimal human health and a delectable culinary delight. Because it has fewer calories and a lower cholesterol content than other meats, this succulent meat is not only delicious but also a nutritious choice. Globally, discriminating consumers have expressed profound appreciation for its irresistible flavor and nutritious composition. High-quality sheep breeds and lamb quality are in the spotlight as the market for sheep meat grows. Nevertheless, the demand for rapid growth and the use of antibiotics and other drugs have led to a shortage of high-quality mutton on the market. In the face of this emergency phenomenon, people add organic matter to the growth of mutton to improve the quality of mutton. This paper discusses the comprehensive evaluation methods of meat quality; summarizes the relationship between the nutritional components of meat and diet; discusses the genetic factors affecting meat quality attributes; feed nutrition, feeding methods, mutton storage methods, and related measures to improve the quality of mutton; and provides information on the current status of mutton and the challenges of ensuring high-quality meat supply in the future. Full article

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

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23 pages, 9841 KiB

Open AccessArticle

Enhanced Real-Time Target Detection for Picking Robots Using Lightweight CenterNet in Complex Orchard Environments

by Pan Fan, Chusan Zheng, ** Sun, Dong Chen, Guodong Lang and Yafeng Li

Agriculture 2024, 14(7), 1059; https://doi.org/10.3390/agriculture14071059 (registering DOI) - 30 Jun 2024

Abstract

The rapid development of artificial intelligence and remote sensing technologies is indispensable for modern agriculture. In orchard environments, challenges such as varying light conditions and shading complicate the tasks of intelligent picking robots. To enhance the recognition accuracy and efficiency of apple-picking robots, [...] Read more.

The rapid development of artificial intelligence and remote sensing technologies is indispensable for modern agriculture. In orchard environments, challenges such as varying light conditions and shading complicate the tasks of intelligent picking robots. To enhance the recognition accuracy and efficiency of apple-picking robots, this study aimed to achieve high detection accuracy in complex orchard environments while reducing model computation and time consumption. This study utilized the CenterNet neural network as the detection framework, introducing gray-centered RGB color space vertical decomposition maps and employing grouped convolutions and depth-separable convolutions to design a lightweight feature extraction network, Light-Weight Net, comprising eight bottleneck structures. Based on the recognition results, the 3D coordinates of the picking point were determined within the camera coordinate system by using the transformation relationship between the image’s physical coordinate system and the camera coordinate system, along with depth map distance information of the depth map. Experimental results obtained using a testbed with an orchard-picking robot indicated that the proposed model achieved an average precision (AP) of 96.80% on the test set, with real-time performance of 18.91 frames per second (FPS) and a model size of only 17.56 MB. In addition, the root-mean-square error of positioning accuracy in the orchard test was 4.405 mm, satisfying the high-precision positioning requirements of the picking robot vision system in complex orchard environments. Full article

(This article belongs to the Section Agricultural Technology)

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16 pages, 7783 KiB

Open AccessArticle

Design and Performance Test of Soybean Profiling Header Suitable for Harvesting Bottom Pods on Film

by Shiguo Wang, Bin Li, Shuren Chen, Zhong Tang, Weiwei Zhou and **aohu Guo

Agriculture 2024, 14(7), 1058; https://doi.org/10.3390/agriculture14071058 (registering DOI) - 30 Jun 2024

Abstract

In order to solve the problems of bottom pod leakage and soil removal by header, a soybean header profiling system was designed in this paper. The cutter height off-ground detection device was installed on both sides of the header, and the cutter distance [...] Read more.

In order to solve the problems of bottom pod leakage and soil removal by header, a soybean header profiling system was designed in this paper. The cutter height off-ground detection device was installed on both sides of the header, and the cutter distance from the ground was represented by the angle sensor turning when the profiling wheel met the rolling ground. The hydraulic electromagnetic reversing valve was installed so that the profiling system could automatically control the lifting of the header, the unilateral power of the solenoid valve was 0.15 s, and the height of the cutter from the ground was changed by 10 mm. The height of the cutter off the ground was set to 80 mm, and the adjustment range of the soybean header profiling system was 45–125 mm. The test results showed that the maximum absolute error of the cutter off the ground height detection device was 5.98 mm, the minimum absolute error was 1.00 mm, and the relative error was 0.038. The cutter height adjustment device was powered for 0.15 s, and the average adjustment distance was 11.158 mm. The soybean header profiling system did not shovel soil during field harvest, and the stubble height of 85% of soybean plants was less than 10 mm from the set height after harvest. The results showed that the soybean header profiling system could effectively adjust the cutter height from the ground so that the cutter height from the ground was kept at 80 mm. This study could provide a reference for the intelligent design of soybean harvesters. Full article

(This article belongs to the Section Agricultural Technology)

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15 pages, 2865 KiB

Open AccessArticle

Effect of Near-Freezing Temperature Storage on the Quality and Organic Acid Metabolism of Apple Fruit

by Chang Shu, Bangdi Liu, Handong Zhao, Kuanbo Cui and Weibo Jiang

Agriculture 2024, 14(7), 1057; https://doi.org/10.3390/agriculture14071057 (registering DOI) - 30 Jun 2024

Abstract

Organic acids play critical roles in fruit physiological metabolism and sensory quality. However, the conventional storage of apple fruit at 0 ± 0.1 °C cannot maintain fruit acidity efficiently. This study investigated near-freezing temperature (NFT) storage for ‘Golden Delicious’ apples, and the quality [...] Read more.

Organic acids play critical roles in fruit physiological metabolism and sensory quality. However, the conventional storage of apple fruit at 0 ± 0.1 °C cannot maintain fruit acidity efficiently. This study investigated near-freezing temperature (NFT) storage for ‘Golden Delicious’ apples, and the quality parameters, organic acid content, and malate metabolism were studied. The results indicate that NFT storage at −1.7 ± 0.1 °C effectively maintained the postharvest quality of apple fruit when compared to traditional storage at 0 ± 0.1 °C. Fruit that underwent NFT storage showed a better appearance and lower respiratory rate, ethylene production, weight loss, and malondialdehyde (MDA) content but higher firmness and soluble solids content. Further, fruit after NFT storage contained higher titratable acid (18.75%), malate (51.61%), citrate (36.59%), and succinate (2.12%) content when compared to the control after 250 days. This was achieved by maintaining higher cytosolic NAD-dependent malate dehydrogenase (cyNAD-MDH), phosphoenolpyruvate carboxylase (PEPC), vacuolar H⁺-ATPase (V-ATPase), and vacuolar inorganic pyrophosphatase (V-PPase) activities that promote malate biosynthesis and accumulation while inhibiting enzyme activity that is responsible for malate decomposition, including phosphoenolpyruvate carboxylase kinase (PEPCK) as well as the cytosolic NAD phosphate-dependent malic enzyme (cyNADP-ME). Further, storage at NFTs maintained a higher expression of malate biosynthesis-related genes (MdcyNAD-MDH and MdPEPC) and transport-related genes (MdVHA and MdVHP) while suppressing malate consumption-related genes (MdcyME and MdPEPCK). The results demonstrate that NFT storage could be an effective application for apple fruit, which maintains postharvest quality and alleviates organic acid degradation. Full article

(This article belongs to the Special Issue Analysis of Agricultural Food Physicochemical and Sensory Properties)

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13 pages, 1336 KiB

Open AccessArticle

Cyclic Electron Flow Alleviates the Stress of Light Fluctuation on Soybean Photosynthesis

by Yi Lei, **g Gao, Qi Wang, Weiying Zeng, Dhungana Diwakar, Yaodan Zhang, **anming Tan, Zudong Sun, Feng Yang and Wenyu Yang

Agriculture 2024, 14(7), 1056; https://doi.org/10.3390/agriculture14071056 (registering DOI) - 30 Jun 2024

Abstract

Crops often face light intensity fluctuations in natural settings. Intercrop** is widely used to improve crop yield and resource utilization worldwide, but crops suffer from high-frequency and high-intensity light fluctuations due to mutual crop influence. Soybean is an important legume crop and is [...] Read more.

Crops often face light intensity fluctuations in natural settings. Intercrop** is widely used to improve crop yield and resource utilization worldwide, but crops suffer from high-frequency and high-intensity light fluctuations due to mutual crop influence. Soybean is an important legume crop and is often intercropped with other crops, but little is known about soybean’s response to light fluctuation environments. Herein, three fluctuation frequencies (1, 10, and 20 min/cycle) were used to analyze soybean photosynthesis responses by measuring leaf growth, chlorophyll content, gas exchange, and electron transfer. Our data revealed that faster fluctuation frequencies led to the stronger suppression of soybean morphology and photosynthesis, with significant reductions of 31.31% and 21.58%, respectively. Damage to photosystems II (PSII) and I (PSI) also intensified, with significant decreases of 18.52% and 18.38% in their effective quantum yields Y(II) and Y(I). Additionally, increased fluctuation frequency exacerbated the consumption of the plastoquinone pool and linear electron flow but enhanced the cyclic electron flow across the thylakoid membrane and, thus, increased heat dissipation in PSII. Our findings indicate that an increased fluctuation frequency inflicted more severe damage on the soybean photosynthesis system. However, PSI-enhanced CEF improved NPQ and coordinated photoprotection to some extent. Full article

(This article belongs to the Section Crop Production)

12 pages, 1466 KiB

Open AccessArticle

Nutritional Value Evaluation of Corn Silage from Different Mesoregions of Southern Brazil

by Mikael Neumann, Ellen Baldissera, Livia Alessi Ienke, André Martins de Souza, Paulo Eduardo Piemontez de Oliveira and Valter Harry Bumbieris Junior

Agriculture 2024, 14(7), 1055; https://doi.org/10.3390/agriculture14071055 (registering DOI) - 30 Jun 2024

Abstract

Corn silage is widely used in livestock farming; however, its quality is easily altered, and one of the factors that has a high influence in this regard is the region of production. The objective was to evaluate the chemical–bromatological composition of 498 samples [...] Read more.

Corn silage is widely used in livestock farming; however, its quality is easily altered, and one of the factors that has a high influence in this regard is the region of production. The objective was to evaluate the chemical–bromatological composition of 498 samples of corn silage from mesoregions in Southern Brazil during the 2022/2023 summer harvest. The following were studied in relation to our objective: nutritional composition, dry matter, mineral matter, ether extract, starch, crude protein, neutral detergent fiber, acid detergent fiber, acid detergent lignin, total digestible nutrients, total carbohydrates, and fractions of carbohydrates. The silages from Central South-PR had higher levels of starch and ether extract (30.68% ± 6.24% and 3.41% ± 0.92%, respectively), whereas in West-SC, the silages had higher levels in the A + B1 fraction of carbohydrates (49.59% ± 6.34%). Silages in North-PR had higher concentrations of neutral detergent fiber and acid detergent fiber (49.86% ± 5.92% and 29.70% ± 4.38%, respectively), while in Northwest-RS and West-PR, silages had higher levels of the B2 carbohydrate fractions (46.25% ± 1.98% and 44.55% ± 3.84%, respectively). The nutritional composition differences presented were due to the variables of each mesoregion, interfering in the scenario of formulating diets and animal nutrition. Full article

(This article belongs to the Special Issue Silage Preparation, Processing and Efficient Utilization)

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14 pages, 7155 KiB

Open AccessArticle

Hyperspectral-Based High-throughput Phenoty** to Assess Water-Use Efficiency in Cotton

by Sahila Beegum, Muhammad Adeel Hassan, Purushothaman Ramamoorthy, Raju Bheemanahalli, Krishna N. Reddy, Vangimalla Reddy and Kambham Raja Reddy

Agriculture 2024, 14(7), 1054; https://doi.org/10.3390/agriculture14071054 (registering DOI) - 29 Jun 2024

Abstract

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenoty**, crucial to breeding programs, is often viewed as [...] Read more.

Cotton is a pivotal global commodity underscored by its economic value and widespread use. In the face of climate change, breeding resilient cultivars for variable environmental conditions becomes increasingly essential. However, the process of phenoty**, crucial to breeding programs, is often viewed as a bottleneck due to the inefficiency of traditional, low-throughput methods. To address this limitation, this study utilizes hyperspectral remote sensing, a promising tool for assessing crucial crop traits across forty cotton varieties. The results from this study demonstrated the effectiveness of four vegetation indices (VIs) in evaluating these varieties for water-use efficiency (WUE). The prediction accuracy for WUE through VIs such as the simple ratio water index (SRWI) and normalized difference water index (NDWI) was higher (up to R² = 0.66), enabling better detection of phenotypic variations (P < 0.05) among the varieties compared to physiological-related traits (from R² = 0.21 to R²= 0.42), with high repeatability and a low RMSE. These VIs also showed high Pearson correlations with WUE (up to r = 0.81) and yield-related traits (up to r = 0.63). We also selected high-performing varieties based on the VIs, WUE, and fiber quality traits. This study demonstrated that the hyperspectral-based proximal sensing approach helps rapidly assess the in-season performance of varieties for imperative traits and aids in precise breeding decisions. Full article

(This article belongs to the Special Issue Smart Agriculture Sensors and Monitoring Systems for Field Detection)

19 pages, 2589 KiB

Open AccessArticle

Design and Test of Discrete Element-Based Separation Roller Potato–Soil Separation Device

by **nwu Du, ** Liu, Yueyun Zhao, Chenglin Zhang, **aoxuan Zhang and Yanshuai Wang

Agriculture 2024, 14(7), 1053; https://doi.org/10.3390/agriculture14071053 (registering DOI) - 29 Jun 2024

Abstract

To address the problems of low bright rates and high rates of potato injuries, a left and right-hand rotation combination of potato–soil separation devices was developed. Its overall structure and working principle were introduced. A Texture Analyzer and pressure sensor were used to [...] Read more.

To address the problems of low bright rates and high rates of potato injuries, a left and right-hand rotation combination of potato–soil separation devices was developed. Its overall structure and working principle were introduced. A Texture Analyzer and pressure sensor were used to measure the force threshold of different varieties of potatoes. A discrete element model of separation rollers and potatoes was established. The collision characteristics of potatoes were analyzed using the device inclination angle, rotational speed, and the center distance of the separation rollers as test factors. A field trial was carried out to optimize the best combination of factors by taking the rate of injured potatoes, bright potatoes, and skin-breaking rate as the test indexes. The force threshold for skin-breaking injury in potatoes was found to be 190–195 N. When the inclination angle of the device was 6°, the rotation speed of the separation roller was 100 r/min, and the distance between the centers of the separation rollers was 79 mm. The rate of injury was 1.25%, the rate of bright potatoes was 99.01%, and the rate of skin-breaking was 1.58%. When the inclination angle of the device was 8°, the rotational speed of the separating roller was 80 r/min, and the center distance of the separating roller was 79 mm, the rate of injured potato was 1.43%, the rate of bright potato was 98.64%, and the rate of broken skin was 1.77%. This paper offers an optimized reference for the effectual removal of sticky soil. Full article

(This article belongs to the Section Agricultural Technology)

17 pages, 2026 KiB

Open AccessArticle

A Lightweight Rice Pest Detection Algorithm Using Improved Attention Mechanism and YOLOv8

by Jianjun Yin, Pengfei Huang, Deqin **ao and Bin Zhang

Agriculture 2024, 14(7), 1052; https://doi.org/10.3390/agriculture14071052 (registering DOI) - 29 Jun 2024

Abstract

Intelligent pest detection algorithms are capable of effectively detecting and recognizing agricultural pests, providing important recommendations for field pest control. However, existing recognition models have shortcomings such as poor accuracy or a large number of parameters. Therefore, this study proposes a lightweight and [...] Read more.

Intelligent pest detection algorithms are capable of effectively detecting and recognizing agricultural pests, providing important recommendations for field pest control. However, existing recognition models have shortcomings such as poor accuracy or a large number of parameters. Therefore, this study proposes a lightweight and accurate rice pest detection algorithm based on improved YOLOv8. Firstly, a Multi-branch Convolutional Block Attention Module (M-CBAM) is constructed in the YOLOv8 network to enhance the feature extraction capability for pest targets, yielding better detection results. Secondly, the Minimum Points Distance Intersection over Union (MPDIoU) is introduced as a bounding box loss metric, enabling faster model convergence and improved detection results. Lastly, lightweight Ghost convolutional modules are utilized to significantly reduce model parameters while maintaining optimal detection performance. The experimental results demonstrate that the proposed method outperforms other detection models, with improvements observed in all evaluation metrics compared to the baseline model. On the test set, this method achieves a detection average precision of 95.8% and an F1-score of 94.6%, with a model parameter of 2.15 M, meeting the requirements of both accuracy and lightweightness. The efficacy of this approach is validated by the experimental findings, which provide specific solutions and technical references for intelligent pest detection. Full article

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

24 pages, 1763 KiB

Open AccessArticle

Role of Policy-Supported Hog Insurance in Promoting Green Total Factor Productivity: The Case of China during 2005–2021

by Dongli Wu, Shan He, Lingui Qin, **gyue Feng and Yu Gao

Agriculture 2024, 14(7), 1051; https://doi.org/10.3390/agriculture14071051 (registering DOI) - 29 Jun 2024

Abstract

Hog insurance and rural environmental protection are complementary to each other. Studying the environmental effects of hog insurance is imperative for safeguarding food safety and promoting the long-term development of the agricultural insurance industry. Informed by the risk management theory and sustainable development [...] Read more.

Hog insurance and rural environmental protection are complementary to each other. Studying the environmental effects of hog insurance is imperative for safeguarding food safety and promoting the long-term development of the agricultural insurance industry. Informed by the risk management theory and sustainable development theory, this paper constructs a theoretical framework for the impact of policy-supported hog insurance on the green total factor productivity (GTFP) of hog farming. Utilizing panel data from China’s hog-dominant production areas spanning from 2005 to 2021, the slacks-based measures of directional distance functions (SBM-DDF) model and multiple-time-point difference-in-differences (DID) approach were used to measure GTFP and explore the effects of hog insurance on GTFP and the underlying mechanisms. The findings indicate a substantial enhancement in GTFP due to hog insurance. The conclusion drawn was robust to various tests. The mechanism is that hog insurance fosters GTFP by expanding the breeding scale, adjusting the planting–breeding structure, and promoting technological progress. Furthermore, the environmental effects of hog insurance policy are more pronounced in economically developed regions, with significant effects observed on the GTFP of free-range, small-scale, and medium-scale hog-farming households. This study contributes new evidence to the field of assessing the environmental impact of agricultural insurance policies and provides valuable insights for furthering green transformation and development in the hog insurance-supported breeding industry. Full article

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

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22 pages, 5932 KiB

Open AccessArticle

The Integration of Mechanical Energy Absorbers into Rollover Protective Structures to Improve the Safety of Agricultural Tractors in the Event of Rollover

by José R. Alfaro-Lopez, Amaya Perez-Ezcurdia, Juan-Ignacio Latorre-Biel, Ignacio Arana-Navarro, Marta Benito-Amurrio and Pedro Villanueva-Roldán

Agriculture 2024, 14(7), 1050; https://doi.org/10.3390/agriculture14071050 (registering DOI) - 29 Jun 2024

Abstract

The combination of safety belts and rollover protective structures (ROPSs) is key in improving the safety of agricultural tractors in the event of rollover. However, we also have the opportunity to enhance the security provided by each ROPS; one such example is the [...] Read more.

The combination of safety belts and rollover protective structures (ROPSs) is key in improving the safety of agricultural tractors in the event of rollover. However, we also have the opportunity to enhance the security provided by each ROPS; one such example is the combination of this safety device with adequate mechanical energy absorbers (MEAs). Inexpensive disc-shaped MEAs can be included in the anchoring points of a ROPS onto the chassis of a tractor. Three configurations of ROPS combined with MEAs were tested during the application of loads that simulated the effects of side rollover in the vehicle. The tested configurations included a blank MEA as a reference case alongside a single MEA and a stack assembly containing both elements. The results of the tests show that both the deformation of the ROPS itself and the strain energy are larger in the case of blank MEAs; thus, there is also a risk that the clearance zone will be infringed upon and that the protective structure will collapse. We can conclude that the implementation of an appropriate MEA in ROPS reduces the deformation of the ROPS itself and its strain energy in cases of vehicle rollover; hence, the safety provided by such protection systems may be improved at a low cost. Full article

(This article belongs to the Special Issue Agricultural Machinery Design and Agricultural Engineering)

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12 pages, 1398 KiB

Open AccessArticle

Impact of Climate Change on the Phenology of Winter Oilseed Rape (Brassica napus L.)

by Jürgen Junk, Arturo Torres, Moussa El Jaroudi and Michael Eickermann

Agriculture 2024, 14(7), 1049; https://doi.org/10.3390/agriculture14071049 (registering DOI) - 29 Jun 2024

Abstract

In our investigation, we have developed innovative statistical models tailored to predict specific phenological stages of winter oilseed rape (WOSR) cultivation in Luxembourg. Leveraging extensive field observations and meteorological data, our modeling approach accurately forecasts critical growth stages of WOSR, including inflorescence emergence [...] Read more.

In our investigation, we have developed innovative statistical models tailored to predict specific phenological stages of winter oilseed rape (WOSR) cultivation in Luxembourg. Leveraging extensive field observations and meteorological data, our modeling approach accurately forecasts critical growth stages of WOSR, including inflorescence emergence (BBCH 51), initial flowering (BBCH 60), and cessation of flowering (BBCH 69), capitalizing on accumulated heat units. Our findings challenge conventional assumptions surrounding base temperatures, advocating for a specific base temperature of 3 °C for winter oilseed rape emergence, consistent with prior research. Validation via leave-one-out cross-validation yields promising outcomes, with average Root Mean Square Error (RMSE) values below 1, surpassing analogous studies. Particularly noteworthy is our model’s performance in predicting crucial growth stages, notably BBCH 60, pivotal for pest control. Despite advancements, hurdles persist in forecasting late-stage phenological events influenced by leaf senescence and anticipated climate change impacts, likely accelerating WOSR development and introducing new risks. In response, cultivar selection strategies informed by individual development rates and temperature sensitivities emerge as vital mitigation measures. As climate variability intensifies, precision agriculture assumes paramount importance in optimizing resource allocation and ensuring sustainable WOSR cultivation practices. Our study advocates for proactive integration of predictive modeling into adaptive management frameworks, empowering stakeholders to make informed decisions taking climatic dynamics into account. Full article

(This article belongs to the Section Ecosystem, Environment and Climate Change in Agriculture)

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18 pages, 1906 KiB

Open AccessArticle

Spatial and Temporal Variations of Soil pH in Farmland in **njiang, China over the Past Decade

by Yue Zhang, Huichun Ye, Ronghao Liu, Mingyao Tang, Chaojia Nie, Xuemei Han, **aoshu Zhao, Peng Wei and Fu Wen

Agriculture 2024, 14(7), 1048; https://doi.org/10.3390/agriculture14071048 (registering DOI) - 29 Jun 2024

Abstract

Soil pH is crucial for the quality of the farmland and crop growth. The objective of this study is to analyze the spatial and temporal variations of farmland soil pH in **njiang (XJ), and to provide a scientific basis for soil improvement and [...] Read more.

Soil pH is crucial for the quality of the farmland and crop growth. The objective of this study is to analyze the spatial and temporal variations of farmland soil pH in ** by 0.59 units. Furthermore, this study found that factors such as topography, nutrients, and irrigation methods all have certain influences on the spatial distribution of soil pH in XJ farmland, while variations in climate factors and fertilization levels may affect its long-term temporal changes. These research findings will provide new insights for adjusting and updating agricultural management measures related to soil pH regulation in XJ. Full article

(This article belongs to the Topic Remote Sensing and Geoinformatics in Agriculture and Environment Volume II)

15 pages, 3694 KiB

Open AccessArticle

Unravelling the Biochemical and Molecular Priming Effect of a New Yeast-Derived Product: New Perspectives towards Disease Management

by Giulia Scimone, Isabel Vicente, Guido Bartalena, Claudia Pisuttu, Lorenzo Mariotti, Samuele Risoli, Elisa Pellegrini, Sabrina Sarrocco and Cristina Nali

Agriculture 2024, 14(7), 1047; https://doi.org/10.3390/agriculture14071047 (registering DOI) - 29 Jun 2024

Abstract

Plants constantly face the environment that surrounds them and fight for survival against biotic and abiotic stress factors. To deal with harmful conditions, plants have developed a multilayer defence system, making them capable of recognising threats and promptly recovering from them. This phenomenon, [...] Read more.

Plants constantly face the environment that surrounds them and fight for survival against biotic and abiotic stress factors. To deal with harmful conditions, plants have developed a multilayer defence system, making them capable of recognising threats and promptly recovering from them. This phenomenon, which takes advantage of the “memory effect”, is referred to as bio-priming and represents a new frontier in terms of crop protection. Here, we investigated the “indirect” protective mechanisms of a new yeast extract formulate in Vitis vinifera cv. Sangiovese plants at both the biochemical and genic levels. The formulate was applied once a week for three consecutive weeks, and grapevine leaves were sampled from the first to the fifth day after treatment (dat) at every week of the experiment. Increased levels of jasmonic acid (every week at 2 dat; +70% as average) and abscisic acid (at 1 dat of the first week, more than 1.7-fold higher than the control) and the underproduction of salicylic acid (from 2 dat; −18%) confirmed that these signalling molecules/”specialised compounds” are actively involved in the early activation of defence pathways in treated vines. In addition, pr2 and chit1b, two genes involved in regulating hormonal crosstalk, were significantly up-regulated (both in the first and second week of the trial) and were also found to underlie upstream molecular activation. The results obtained by this investigation confirm the use of this new product to prime and protect grapevines from a wide range of fungal and fungal-like plant pathogens through the induction of defence responses. Full article

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

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23 pages, 1601 KiB

Open AccessArticle

A Novel Two-Stage Approach for Automatic Extraction and Multi-View Generation of Litchis

by Yuanhong Li, **g Wang, Ming Liang, Haoyu Song, Jianhong Liao and Yubin Lan

Agriculture 2024, 14(7), 1046; https://doi.org/10.3390/agriculture14071046 (registering DOI) - 29 Jun 2024

Abstract

Obtaining consistent multi-view images of litchis is crucial for various litchi-related studies, such as data augmentation and 3D reconstruction. This paper proposes a two-stage model that integrates the Mask2Former semantic segmentation network with the Wonder3D multi-view generation network. This integration aims to accurately [...] Read more.

Obtaining consistent multi-view images of litchis is crucial for various litchi-related studies, such as data augmentation and 3D reconstruction. This paper proposes a two-stage model that integrates the Mask2Former semantic segmentation network with the Wonder3D multi-view generation network. This integration aims to accurately segment and extract litchis from complex backgrounds and generate consistent multi-view images of previously unseen litchis. In the first stage, the Mask2Former model is utilized to predict litchi masks, enabling the extraction of litchis from complex backgrounds. To further enhance the accuracy of litchi branch extraction, we propose a novel method that combines the predicted masks with morphological operations and the HSV color space. This approach ensures accurate extraction of litchi branches even when the semantic segmentation model’s prediction accuracy is not high. In the second stage, the segmented and extracted litchi images are passed as input into the Wonder3D network to generate multi-view of the litchis. After comparing different semantic segmentation and multi-view synthesis networks, the Mask2Former and Wonder3D networks demonstrated the best performance. The Mask2Former network achieved a mean Intersection over Union (mIoU) of 79.79% and a mean pixel accuracy (mPA) of 85.82%. The Wonder3D network achieved a peak signal-to-noise ratio (PSNR) of 18.89 dB, a structural similarity index (SSIM) of 0.8199, and a learned perceptual image patch similarity (LPIPS) of 0.114. Combining the Mask2Former model with the Wonder3D network resulted in an increase in PSNR and SSIM scores by 0.21 dB and 0.0121, respectively, and a decrease in LPIPS by 0.064 compared to using the Wonder3D model alone. Therefore, the proposed two-stage model effectively achieves automatic extraction and multi-view generation of litchis with high accuracy. Full article

(This article belongs to the Section Digital Agriculture)

34 pages, 4233 KiB

Open AccessArticle

Performance Evaluation of Three Peanut Cultivars Grown under Elevated CO₂ Concentrations

by Nicola Novello, Joel B. Johnson, Haydee Laza, Kerry B. Walsh and Mani Naiker

Agriculture 2024, 14(7), 1045; https://doi.org/10.3390/agriculture14071045 (registering DOI) - 29 Jun 2024

Abstract

This study explored the performance and physiological responses of three commercially used peanut cultivars in Australian farming systems under ambient and elevated CO₂ conditions, aiming to identify the most suitable genotype for dual-purpose (grain and graze) crop** experiments. The experiment utilized an [...] Read more.

This study explored the performance and physiological responses of three commercially used peanut cultivars in Australian farming systems under ambient and elevated CO₂ conditions, aiming to identify the most suitable genotype for dual-purpose (grain and graze) crop** experiments. The experiment utilized an open-top chamber (OTC) facility to regulate CO₂ concentrations. The elevated CO₂ (EC) treatment targeted approximately 650 ± 50 µmol mol⁻¹, while both ambient CO₂ (AC) and control plots operated at a concentration of approximately 400 µmol mol⁻¹. Notably, control plots without chambers served as a reference for current CO₂ and environmental conditions. In contrast, despite having the same ambient CO₂ concentration, AC plots were enclosed in chambers, allowing for plant growth comparisons with EC plots with the same environmental conditions aside from CO₂ levels. The analyses revealed significant effects of CO₂ enrichment on peanut plants. In particular, the EC treatment led to enhanced photosynthetic rates (20% in Kairi, 31% in Holt, and 19% in Alloway), alongside reduced stomatal conductance (−55% in Kairi, −32% in Holt, and −40% in Alloway), transpiration, and increased water use efficiency compared to AC conditions. Elevated CO₂ levels positively influenced pod yields in Kairi (+41%) and Alloway (+36%). However, CO₂ enrichment did not significantly alter the protein content, total phenolic content, cupric-reducing antioxidant capacity, and ferric-reducing antioxidant power of peanut plant material. Furthermore, no significant differences were observed in the phytochemical composition among the three cultivars under ambient or elevated CO₂ conditions. On the other hand, analysis of the fibre structure conducted on peanut stover harvested at plant maturity suggested potential declines in feedstock quality. Based on the findings of this research, further investigations and testing, including simulated grazing trials, will be carried out to identify a single breed line suitable for dual-purpose management under future elevated CO₂ conditions. Full article

(This article belongs to the Section Crop Production)

15 pages, 2766 KiB

Open AccessArticle

Identification and Characterization of Resistance Loci to Stripe Rust in Winter Wheat Breeding Line YN1813

by Jianwei Tang, Yan Gao, Yujia Li, Bin Bai, Ling Wu, Yi Ren, Hongwei Geng and Guihong Yin

Agriculture 2024, 14(7), 1044; https://doi.org/10.3390/agriculture14071044 (registering DOI) - 29 Jun 2024

Abstract

The development and deployment of diverse resistance sources in novel wheat cultivars underpin the durable control of stripe rust. The objectives of this study were to identify quantitative trait loci (QTL) associated with stripe rust resistance in the Chinese wheat breeding line YN1813 [...] Read more.

The development and deployment of diverse resistance sources in novel wheat cultivars underpin the durable control of stripe rust. The objectives of this study were to identify quantitative trait loci (QTL) associated with stripe rust resistance in the Chinese wheat breeding line YN1813 and to provide wheat breeders with original genes with potentially durable resistance. A total of 306 F_7:8 recombinant inbred lines (RIL), derived from a cross between YN1813 (infection type 0–3 and disease severity 1–36%) and the moderately susceptible landrace Chinese Spring (IT 7–9 and DS 41–65%), were assessed for stripe rust disease severity in the field at Qingshui in Gansu and Pixian in Sichuan in 2020 and 2021 following inoculation with a mixture of the currently predominant Pst races. The parents and RIL were genotyped using the Wheat 55K single-nucleotide polymorphism (SNP) array. The total length of the constructed genetic linkage map was 3896.30 cm, with an average interval of 1.30 cm between adjacent markers. Two major QTL were identified on chromosome 7B and 7D across all tested environments. QYr.hau-7B was mapped to a 2.26 cm interval between the SNP markers AX-110908486–AX-89658728–AX-109489314 on chromosome 7B, explaining 0.9% to 16.9% of the phenotypic variation. QYr.hau-7D was positioned in a 0.67 cm interval flanked by the SNP markers AX-111654594 and AX-89378255, explaining 0.4% to 21.4% of the phenotypic variation. The QTL on 7D likely correspond to the previously known gene Yr18, whereas QYr.hau-7B was presumed to be a novel gene adjacent to YrZH84 or the core part of YrZH84. SNP markers closely linked with QYr.hau-7B were converted to allele-specific quantitative PCR-based genoty** assay (AQP) markers and validated in a panel of 712 wheat accessions. The group possessing a positive allele (TT) of AQP_AX-89658728 significantly (p < 0.05) decreased the IT by 45.8% and the DS by 63.2%. QYr.hau-7B and its markers could be useful in breeding programs to improve the level and durability of stripe rust resistance. Full article

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

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