Agriculture

27 pages, 4494 KiB

Open AccessArticle

Land Degradation in Southern Africa: Restoration Strategies, Grazing Management, and Livelihoods

by Mhlangabezi Slayi, Leocadia Zhou and Kgabo Humphrey Thamaga

Agriculture 2024, 14(10), 1849; https://doi.org/10.3390/agriculture14101849 (registering DOI) - 19 Oct 2024

Land degradation in communal rangelands poses significant challenges to environmental sustainability, agricultural productivity, and livelihoods in southern Africa. This study presents a bibliometric analysis of research trends, key contributors, thematic evolution, and collaborative networks in the field of land degradation in communal rangelands [...] Read more.

Land degradation in communal rangelands poses significant challenges to environmental sustainability, agricultural productivity, and livelihoods in southern Africa. This study presents a bibliometric analysis of research trends, key contributors, thematic evolution, and collaborative networks in the field of land degradation in communal rangelands from 1997 to 2024. Utilizing data obtained from the Scopus database, we examined 66 publications to identify patterns in publication output, leading journals, influential articles, and prominent authors and institutions. The analysis demonstrates an overall increase in research output, with a notable surge in publications during the past decade, indicating a growing academic and policy interest in this field. Major themes identified include sustainable land management, restoration strategies, and the impacts of grazing management on ecosystem health. Networks showcasing co-authorship and keyword co-occurrence reveal robust collaborative connections among researchers and a concentrated focus on specific dominant themes. Consequently, these findings propose opportunities for expanding interdisciplinary research and exploring underrepresented areas. This study provides a comprehensive overview of the research landscape, offering insights to steer future studies and inform policy interventions aimed at mitigating land degradation and bolstering the resilience of communal rangelands in southern Africa. Full article

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

16 pages, 1649 KiB

Open AccessArticle

Fruit Distribution Density Estimation in YOLO-Detected Strawberry Images: A Kernel Density and Nearest Neighbor Analysis Approach

by Lili Jiang, Yunfei Wang, Chong Wu and Haibin Wu

Agriculture 2024, 14(10), 1848; https://doi.org/10.3390/agriculture14101848 (registering DOI) - 19 Oct 2024

Abstract

Precise information on strawberry fruit distribution is of significant importance for optimizing planting density and formulating harvesting strategies. This study applied a combined analysis of kernel density estimation and nearest neighbor techniques to estimate fruit distribution density from YOLOdetected strawberry images. Initially, an [...] Read more.

Precise information on strawberry fruit distribution is of significant importance for optimizing planting density and formulating harvesting strategies. This study applied a combined analysis of kernel density estimation and nearest neighbor techniques to estimate fruit distribution density from YOLOdetected strawberry images. Initially, an improved yolov8n strawberry object detection model was employed to obtain the coordinates of the fruit centers in the images. The results indicated that the improved model achieved an accuracy of 94.7% with an [email protected]~0.95 of 87.3%. The relative error between the predicted and annotated coordinates ranged from 0.002 to 0.02, demonstrating high consistency between the model predictions and the annotated results. Subsequently, based on the strawberry center coordinates, the kernel density estimation algorithm was used to estimate the distribution density in the strawberry images. The results showed that with a bandwidth of 200, the kernel density estimation accurately reflected the actual strawberry density distribution, ensuring that all center points in high-density regions were consistently identified and delineated. Finally, to refine the strawberry distribution information, a comprehensive method based on nearest neighbor analysis was adopted, achieving target area segmentation and regional density estimation in the strawberry images. Experimental results demonstrated that when the distance threshold ϵ was set to 600 pixels, the correct grouping rate exceeded 94%, and the regional density estimation results indicated a significant positive correlation between the number of fruits and regional density. This study provides scientific evidence for optimizing strawberry planting density and formulating harvesting sequences, contributing to improved yield, harvesting efficiency, and reduced fruit damage. In future research, this study will further explore dynamic models that link fruit distribution density, planting density, and fruit growth status. Full article

(This article belongs to the Section Digital Agriculture)

35 pages, 662 KiB

Open AccessArticle

Potential Impacts of Diversification of Food Retail Working Hours on Consumer Behaviour and the Benefits for Local Producers in Latvia

by Liga Proskina, Lana Janmere, Sallija Cerina, Irina Pilvere, Aija Pilvere, Aleksejs Nipers and Daniela Proskina

Agriculture 2024, 14(10), 1847; https://doi.org/10.3390/agriculture14101847 (registering DOI) - 19 Oct 2024

Abstract

The capability of large food retail chains to respond quickly to changes in consumer behaviour and their dominant market position affects all food market players and often conflicts with the interests of national food producers, which can reduce the presence of locally sourced [...] Read more.

The capability of large food retail chains to respond quickly to changes in consumer behaviour and their dominant market position affects all food market players and often conflicts with the interests of national food producers, which can reduce the presence of locally sourced products in the food product mix in the country. Accordingly, the present research aims to identify the impacts of the diversification of opening hours of food supermarkets on consumer shopping habits and the implications for creating an advantage for small and medium agri-food producers in selling their products. The research applied a quantitative approach to identify the main trends in society (n = 2738), with a survey including 31 variables to quantify consumer behaviour, values, and opinions and seven socio-demographic variables. If a decision was made in Latvia to close grocery shops on Sundays or reduce their opening hours on weekends, 85% of consumers indicated that they would be unlikely to change their usual shopping location and would plan to shop at a supermarket on other days. The choice between farmers’ markets and local food shops on Sundays would be made by 45% of consumers, with more than half (53%) of them shopping at local food shops at least a few times a month. The research uniquely investigated the impact of reducing supermarket opening hours on the competitive advantage of small and medium-sized agri-food producers. The findings revealed that reducing supermarket opening hours does not confer a competitive advantage to the producers or significantly shift consumer preferences towards their products. Full article

(This article belongs to the Special Issue Agri-Food Marketing Strategies and Consumer Behavior)

14 pages, 12763 KiB

Open AccessArticle

Semantic Segmentation Model-Based Boundary Line Recognition Method for Wheat Harvesting

by Qian Wang, Wuchang Qin, Mengnan Liu, Junjie Zhao, Qingzhen Zhu and Yanxin Yin

Agriculture 2024, 14(10), 1846; https://doi.org/10.3390/agriculture14101846 (registering DOI) - 19 Oct 2024

Abstract

The wheat harvesting boundary line is vital reference information for the path tracking of an autonomously driving combine harvester. However, unfavorable factors, such as a complex light environment, tree shade, weeds, and wheat stubble color interference in the field, make it challenging to [...] Read more.

The wheat harvesting boundary line is vital reference information for the path tracking of an autonomously driving combine harvester. However, unfavorable factors, such as a complex light environment, tree shade, weeds, and wheat stubble color interference in the field, make it challenging to identify the wheat harvest boundary line accurately and quickly. Therefore, this paper proposes a harvest boundary line recognition model for wheat harvesting based on the MV3_DeepLabV3+ network framework, which can quickly and accurately complete the identification in complex environments. The model uses the lightweight MobileNetV3_Large as the backbone network and the LeakyReLU activation function to avoid the neural death problem. Depth-separable convolution is introduced into Atrous Spatial Pyramid Pooling (ASPP) to reduce the complexity of network parameters. The cubic B-spline curve-fitting method extracts the wheat harvesting boundary line. A prototype harvester for wheat harvesting boundary recognition was built, and field tests were conducted. The test results show that the wheat harvest boundary line recognition model proposed in this paper achieves a segmentation accuracy of 98.04% for unharvested wheat regions in complex environments, with an IoU of 95.02%. When the combine harvester travels at 0~1.5 m/s, the normal speed for operation, the average processing time and pixel error for a single image are 0.15 s and 7.3 pixels, respectively. This method could achieve high recognition accuracy and fast recognition speed. This paper provides a practical reference for the autonomous harvesting operation of a combine harvester. Full article

(This article belongs to the Special Issue Agricultural Collaborative Robots for Smart Farming)

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21 pages, 2847 KiB

Open AccessArticle

Dynamics of Energy Fluxes in a Mediterranean Vineyard: Influence of Soil Moisture

by Ricardo Egipto, Arturo Aquino and José Manuel Andújar

Agriculture 2024, 14(10), 1845; https://doi.org/10.3390/agriculture14101845 (registering DOI) - 19 Oct 2024

Abstract

Accurate evaluation of grapevine water use is essential for optimizing water management and maximizing grapevine yield and berry quality in Mediterranean climates. Understanding the water and heat flux dynamics in a vineyard during grapevine berry maturation is of utmost importance. This study focuses [...] Read more.

Accurate evaluation of grapevine water use is essential for optimizing water management and maximizing grapevine yield and berry quality in Mediterranean climates. Understanding the water and heat flux dynamics in a vineyard during grapevine berry maturation is of utmost importance. This study focuses on evaluating sensible and latent energy fluxes at the canopy, the soil beneath the canopy, and the interrow areas. The primary objective is to develop a model framework for accurately estimating these energy fluxes, contributing to a better understanding of their behavior during berry ripening. The model’s accuracy was assessed by comparing the estimated fluxes with those measured by an eddy-covariance system installed at a reference height of three meters in the experimental vineyard. This validation step was essential to confirm the model’s ability to capture the intricate energy flux dynamics of the vineyard, especially during grape maturation. The results revealed a high level of agreement between the observed and estimated fluxes, confirming the model’s reliability. This comprehensive evaluation of energy fluxes provides valuable insights for optimizing irrigation strategies. By doing so, this study contributes to improving grape quality, ensuring sustainable water resource use, and ultimately enhancing vineyard productivity in arid and water-scarce regions. Full article

(This article belongs to the Section Agricultural Water Management)

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28 pages, 6595 KiB

Open AccessArticle

An Evaluation Scheme Driven by Science and Technological Innovation—A Study on the Coupling and Coordination of the Agricultural Science and Technology Innovation-Economy-Ecology Complex System in the Yangtze River Basin of China

by Chunlin Xiong, Yilin Zhang and Weijie Wang

Agriculture 2024, 14(10), 1844; https://doi.org/10.3390/agriculture14101844 (registering DOI) - 19 Oct 2024

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Abstract

This study focuses on 19 provinces in the Yangtze River Basin of China. It gathers relevant data indicators from 2010 to 2021 and constructs an evaluation index system centered on agricultural science and technology innovation. The study evaluates the relationship between agricultural “science [...] Read more.

This study focuses on 19 provinces in the Yangtze River Basin of China. It gathers relevant data indicators from 2010 to 2021 and constructs an evaluation index system centered on agricultural science and technology innovation. The study evaluates the relationship between agricultural “science and technology innovation-economy-ecology” systems and identifies key obstacle factors using the obstacle degree model. The study draws the following conclusions: Firstly, the comprehensive development level index of the agricultural science and technology innovation system shows an overall linear upward trend (values range from 0.121 to 0.382). Secondly, the comprehensive development level index of the agricultural economic system exhibits an upward trend but with a relatively small overall magnitude (values range from 0.248 to 0.322). Thirdly, the comprehensive development level index of the agricultural ecological system demonstrates significant overall fluctuations, with notable regional disparities (values range from 0.384 to 0.414). Fourthly, the overall agricultural SEE (Science and technological innovation, Economy, Ecology) complex system exhibits a characteristic of “high coupling, low coordination”, identifying the main obstacle factors influencing agricultural SEECS based on a formulated approach. Subsequently, the following policy recommendations are proposed: Firstly, enhance the agricultural technological innovation system and promote green and efficient agricultural technology research and development. Secondly, to accelerate the transformation and upgrading of modern agriculture, achieving green and high-quality development of the agricultural economy. Thirdly, to strengthen agricultural ecological environment protection, laying a solid foundation for the healthy and sustainable development of agriculture. Full article

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

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14 pages, 1255 KiB

Open AccessArticle

Two-Stage Multimodal Method for Predicting Intramuscular Fat in Pigs

by Wenzheng Liu, Tonghai Liu, Jianxun Zhang and Fanzhen Wang

Agriculture 2024, 14(10), 1843; https://doi.org/10.3390/agriculture14101843 (registering DOI) - 18 Oct 2024

Viewed by 288

Abstract

Intramuscular fat (IMF) content significantly influences pork tenderness, flavor, and juiciness. Maintaining an optimal IMF range not only enhances nutritional value but also improves the taste of pork products. However, traditional IMF measurement methods are often invasive and time-consuming. Ultrasound imaging technology offers [...] Read more.

Intramuscular fat (IMF) content significantly influences pork tenderness, flavor, and juiciness. Maintaining an optimal IMF range not only enhances nutritional value but also improves the taste of pork products. However, traditional IMF measurement methods are often invasive and time-consuming. Ultrasound imaging technology offers a non-destructive solution capable of predicting IMF content and assessing backfat thickness as well as longissimus dorsi muscle area size. A two-stage multimodal network model was developed in this study. First, using B-mode ultrasound images, we employed the UNetPlus segmentation network to accurately delineate the longissimus dorsi muscle area. Subsequently, we integrated data on backfat thickness and longissimus dorsi muscle area to create a multimodal input for IMF content prediction using our model. The results indicate that UNetPlus achieves a 94.17% mean Intersection over Union (mIoU) for precise longissimus dorsi muscle area segmentation. The multimodal network achieves an R² of 0.9503 for IMF content prediction, with Spearman and Pearson correlation coefficients of 0.9683 and 0.9756, respectively, all within a compact model size of 4.96 MB. This study underscores the efficacy of combining segmented longissimus dorsi muscle images with data on backfat thickness and muscle area in a two-stage multimodal approach for predicting IMF content. Full article

(This article belongs to the Section Farm Animal Production)

18 pages, 1276 KiB

Open AccessArticle

Object Detection in High-Resolution UAV Aerial Remote Sensing Images of Blueberry Canopy Fruits

by Yun Zhao, Yang Li and Xing Xu

Agriculture 2024, 14(10), 1842; https://doi.org/10.3390/agriculture14101842 (registering DOI) - 18 Oct 2024

Viewed by 255

Abstract

Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth [...] Read more.

Blueberries, as one of the more economically rewarding fruits in the fruit industry, play a significant role in fruit detection during their growing season, which is crucial for orchard farmers’ later harvesting and yield prediction. Due to the small size and dense growth of blueberry fruits, manual detection is both time-consuming and labor-intensive. We found that there are few studies utilizing drones for blueberry fruit detection. By employing UAV remote sensing technology and deep learning techniques for detection, substantial human, material, and financial resources can be saved. Therefore, this study collected and constructed a UAV remote sensing target detection dataset for blueberry canopy fruits in a real blueberry orchard environment, which can be used for research on remote sensing target detection of blueberries. To improve the detection accuracy of blueberry fruits, we proposed the PAC3 module, which incorporates location information encoding during the feature extraction process, allowing it to focus on the location information of the targets and thereby reducing the chances of missing blueberry fruits. We adopted a fast convolutional structure instead of the traditional convolutional structure, reducing the model’s parameter count and computational complexity. We proposed the PF-YOLO model and conducted experimental comparisons with several excellent models, achieving improvements in mAP of 5.5%, 6.8%, 2.5%, 2.1%, 5.7%, 2.9%, 1.5%, and 3.4% compared to Yolov5s, Yolov5l, Yolov5s-p6, Yolov5l-p6, Tph-Yolov5, Yolov8n, Yolov8s, and Yolov9c, respectively. We also introduced a non-maximal suppression algorithm, Cluster-NMF, which accelerates inference speed through matrix parallel computation and merges multiple high-quality target detection frames to generate an optimal detection frame, enhancing the efficiency of blueberry canopy fruit detection without compromising inference speed. Full article

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

22 pages, 803 KiB

Open AccessArticle

A Non-Destructive Measurement Approach for the Internal Temperature of Shiitake Mushroom Sticks Based on a Data–Physics Hybrid-Driven Model

by Xin Zhang, Xinwen Zeng, Yibo Wei, Wengang Zheng and Mingfei Wang

Agriculture 2024, 14(10), 1841; https://doi.org/10.3390/agriculture14101841 (registering DOI) - 18 Oct 2024

Viewed by 245

Abstract

This study aimed to develop a non-destructive measurement method utilizing acoustic sensors for the efficient determination of the internal temperature of shiitake mushroom sticks during the cultivation period. In this research, the sound speed, air temperature, and moisture content of the mushroom sticks [...] Read more.

This study aimed to develop a non-destructive measurement method utilizing acoustic sensors for the efficient determination of the internal temperature of shiitake mushroom sticks during the cultivation period. In this research, the sound speed, air temperature, and moisture content of the mushroom sticks were employed as model inputs, while the temperature of the mushroom sticks served as the model output. A data–physics hybrid-driven model for temperature measurement based on XGBoost was constructed by integrating monotonicity constraints between the temperature of the mushroom sticks and sound speed, along with the condition that limited the difference between air temperature and stick temperature to less than 2 °C. The experimental results indicated that the optimal eigenfrequency for applying this model was 850 Hz, the optimal distance between the sound source and the shiitake mushroom sticks was 8.7 cm, and the temperature measurement accuracy was highest when the moisture content of the shiitake mushroom sticks was in the range of 56~66%. Compared to purely data-driven models, our proposed model demonstrated significant improvements in performance; specifically, RMSE, MAE, and MAPE decreased by 74.86%, 77.22%, and 69.30%, respectively, while R² increased by 1.86%. The introduction of physical knowledge constraints has notably enhanced key performance metrics in machine learning-based acoustic thermometry, facilitating efficient, accurate, rapid, and non-destructive measurements of internal temperatures in shiitake mushroom sticks. Full article

(This article belongs to the Section Digital Agriculture)

28 pages, 5530 KiB

Open AccessArticle

The Spatiotemporal Variations in and Propagation of Meteorological, Agricultural, and Groundwater Droughts in Henan Province, China

by Huazhu Xue, Ruirui Zhang, Wenfei Luan and Zhanliang Yuan

Agriculture 2024, 14(10), 1840; https://doi.org/10.3390/agriculture14101840 (registering DOI) - 18 Oct 2024

Viewed by 239

Abstract

As the global climate changes and droughts become more frequent, understanding the characteristics and propagation dynamics of drought is critical for monitoring and early warning. This study utilized the Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Groundwater Drought Index (GDI) [...] Read more.

As the global climate changes and droughts become more frequent, understanding the characteristics and propagation dynamics of drought is critical for monitoring and early warning. This study utilized the Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Groundwater Drought Index (GDI) to identify meteorological drought (MD), agricultural drought (AD), and groundwater drought (GD), respectively. Sen’s slope method and Mann–Kendall trend analysis were used to examine drought trends. The Pearson correlation coefficient (PCC) and theory of run were utilized to identify the propagation times between different types of droughts. Cross-wavelet transform (XWT) and wavelet coherence (WTC) were applied to investigate the linkages among the three types of droughts. The results showed that, from 2004 to 2022, the average durations of MD, AD, and GD in Henan Province were 4.55, 8.70, and 29.03 months, respectively. MD and AD were gradually alleviated, while GD was exacerbated. The average propagation times for the different types of droughts were as follows: 6.1 months (MD-AD), 4.4 months (MD-GD), and 16.3 months (AD-GD). Drought propagation exhibited significant seasonality, being shorter in summer and autumn than in winter and spring, and there were close relationships among MD, AD, and GD. This study revealed the characteristics and propagation dynamics of different types of droughts in Henan Province, providing scientific references for alleviating regional droughts and promoting the sustainable development of agriculture and food production. Full article

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

15 pages, 1029 KiB

Open AccessArticle

Performance of Small-Scale Hermetic Storage Systems Under Periodic Access

by Jaden Tatum and Ajay Shah

Agriculture 2024, 14(10), 1839; https://doi.org/10.3390/agriculture14101839 (registering DOI) - 18 Oct 2024

Viewed by 167

Abstract

This study characterizes the grain management performance of a novel integrated grain drying and storage system (iGDSS) adapted from 208 L drums to combat postharvest loss in developing countries through providing in situ mechanized drying and hermetic storage. The six-month storage trials of [...] Read more.

This study characterizes the grain management performance of a novel integrated grain drying and storage system (iGDSS) adapted from 208 L drums to combat postharvest loss in developing countries through providing in situ mechanized drying and hermetic storage. The six-month storage trials of 14% moisture content maize compared different access mechanisms and two levels of pest pressure: 0 and 10 maize weevils/kg grain. This experiment allowed comparisons of differential oxygen consumption rates in small-scale hermetic systems with and without storage pests, which has not been widely reported in the literature. The iGDSS system was found to maintain grain quality parameters in dry grains with and without storage pests. After six months of storage, the results demonstrated no statistically significant difference in the moisture content, test weight, germination, proportion of broken and damaged kernels, and presence of colony-forming units between inoculated and non-inoculated systems. The iGDSS was also found to maintain oxygen intrusion rates of 0.10–0.13% O₂/day, below recommended thresholds of 0.15% required to maintain benefits of modified atmosphere storage. These results indicate that the iGDSS can provide safe and reliable grain storage to smallholder farmers in developing countries, and that the drying functions of iGDSS can promote outcomes in hermetic storage. Full article

(This article belongs to the Special Issue Grain Harvesting, Processing Technology, and Storage Management)

17 pages, 936 KiB

Open AccessArticle

Increasing Productivity and Fruit Quality of ‘Mutsu’ Apple Orchard by Dwarfing Treatments

by Maria Małachowska, Tomasz Majak, Tomasz Krupa and Kazimierz Tomala

Agriculture 2024, 14(10), 1838; https://doi.org/10.3390/agriculture14101838 (registering DOI) - 18 Oct 2024

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Abstract

The aim of this 2022 study was to evaluate the effect of tree growth-limiting treatments on the tree yield and quality of ‘Mutsu’ apples. The experiment was established on 7-year-old trees on M.9 rootstock in a commercial orchard in Wilga near Warsaw. Growth-limiting [...] Read more.

The aim of this 2022 study was to evaluate the effect of tree growth-limiting treatments on the tree yield and quality of ‘Mutsu’ apples. The experiment was established on 7-year-old trees on M.9 rootstock in a commercial orchard in Wilga near Warsaw. Growth-limiting treatments included unilateral root pruning, spraying the trees with Regalis Plus 10 WG at various times, and spraying with Flordimex 480 SL. Eight combinations were used, with four replicates of 20 trees per repetition. The measurements included fruit set, length of this year’s shoots, yield per tree, average fruit weight, and the size structure of the yield. The distinctive physiological status of the apples was assessed directly after harvest, directly after 8 months of storage under CA conditions (1.5% CO₂, 1.5% O₂, 1 °C, >92% RH) and after an additional 7 days of shelf-life. Spraying trees with Regalis Plus 10 WG from the balloon stage onwards, irrespective of the treatment with root pruning, was most effective in both inhibiting long-stem growth and increasing tree yield (by almost two times) by increasing the number of apples per tree. The growth response of long-stemmed apple trees to both unilateral root pruning and Ethephon spray was significantly lower than it was to Regalis Plus 10 WG spray and had relatively little effect on their yield. Regalis Plus 10 WG resulted in a clear reduction in average fruit weight (by about 100 g), which, in the case of the large-fruited cultivar ‘Mutsu’, should be seen as an advantage. Its application from the balloon stage onwards promoted higher apple firmness at harvest and after simulated handling preceded by long-term storage. Full article

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

27 pages, 2993 KiB

Open AccessArticle

The Development of a Prediction Model Related to Food Loss and Waste in Consumer Segments of Agrifood Chain Using Machine Learning Methods

by Daniel Nijloveanu, Victor Tița, Nicolae Bold, Doru Anastasiu Popescu, Dragoș Smedescu, Cosmina Smedescu and Gina Fîntîneru

Agriculture 2024, 14(10), 1837; https://doi.org/10.3390/agriculture14101837 (registering DOI) - 18 Oct 2024

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Abstract

Food loss and waste (FLW) is a primary focus topic related to all human activity. This phenomenon has a great deal of importance due to its effect on the economic and social aspects of human systems. The most integrated approach to food waste [...] Read more.

Food loss and waste (FLW) is a primary focus topic related to all human activity. This phenomenon has a great deal of importance due to its effect on the economic and social aspects of human systems. The most integrated approach to food waste analysis is based on the study of FLW alongside the agrifood chain, which has also been performed in previous studies by the authors. This paper presents a modality of determination of food loss and waste effects with an emphasis on consumer segments in agrifood chains in the form of a predictive model based on statistical data collected based on specific methods in Romania. The determination is made comparatively, using two predictive machine learning-based methods and separate instruments (software), in order to establish the best model that fits the collected data structure. In this matter, a Decision Tree Approach (DTA) and a Neural Network Approach (NNA) will be developed, and common methodologies of the approaches will be applied. The results will determine predictive outcomes for a specific food waste (FW) agent (e.g., consumer) based on pattern recognition of the collected data. The results showed relatively high-accuracy predictions, especially for the NN approach, with lower performances using the DTA. The effects of the application of this predictive model will be expected to improve the food loss prevention measures within economic contexts when applied to real-life scenarios. Full article

(This article belongs to the Special Issue Applications of Data Analysis in Agriculture—2nd Edition)

11 pages, 3173 KiB

Open AccessArticle

Effects of Rainfall and Harvest Time on Postharvest Storage Performance of ‘Redson’ Fruit: A New Red Pomelo x Grapefruit Hybrid

by Leanne Salto, Itay Maoz, Livnat Goldenberg, Nir Carmi and Ron Porat

Agriculture 2024, 14(10), 1836; https://doi.org/10.3390/agriculture14101836 (registering DOI) - 18 Oct 2024

Viewed by 236

Abstract

‘Redson’ is a new triploid, red-fleshed pomelo × grapefruit hybrid. The goal of this study was to examine the effects of rainfall, harvest time, tree age, and yield on the postharvest storage performance of ‘Redson’ fruit. During 2022/23, two postharvest storage trials were [...] Read more.

‘Redson’ is a new triploid, red-fleshed pomelo × grapefruit hybrid. The goal of this study was to examine the effects of rainfall, harvest time, tree age, and yield on the postharvest storage performance of ‘Redson’ fruit. During 2022/23, two postharvest storage trials were conducted with early- and late-harvested fruit. The fruit from the early harvest retained good quality for up to 16 weeks of storage at 7.5 °C plus 1 week at 22 °C, whereas the late-harvested fruit suffered from a high decay incidence. During 2023/24, we expanded the postharvest trials to nine different fruit sets harvested from early season (late October) until the end of the season (January). Fruit quality was examined under the same storage conditions after 6 and 16 weeks, and the results indicated that early- and mid-season fruit retained good quality with minimal decay incidence even after prolonged storage for 16 weeks, whereas the late-season fruit suffered from significant decay incidences of 17–22% and a decline in flavor acceptability. Further analysis revealed strong and significant correlations between various rainfall parameters and harvest time and decay incidences. Overall, early-harvested fruit during the autumn had a superior postharvest storage performance, whereas late-harvested fruit during the rainy winter suffered from decay development. Full article

(This article belongs to the Special Issue Postharvest Physiology and Technology of Horticultural Crops—2nd Edition)

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16 pages, 1519 KiB

Open AccessArticle

Zinc Biofortification of Selective Colored Rice Cultivars: Improvement of Zinc Uptake, Agronomic Traits, and Nutritional Value

by Yuanqi Wang, Muhammad Raza Farooq, Yukun Guo, Haoyuan Sun, Pincheng Rao, Zhiwei Peng, Youtao Chen and Xuebin Yin

Agriculture 2024, 14(10), 1835; https://doi.org/10.3390/agriculture14101835 - 18 Oct 2024

Viewed by 226

Abstract

It is difficult for ordinary rice to break the zinc-rich standard. However, employing multiple unique rice cultivar resources through biofortification of agronomic measures to achieve the target is a promising attempt. In this study, a pot experiment was conducted on seven different colored [...] Read more.

It is difficult for ordinary rice to break the zinc-rich standard. However, employing multiple unique rice cultivar resources through biofortification of agronomic measures to achieve the target is a promising attempt. In this study, a pot experiment was conducted on seven different colored rice cultivars (GFHN 166, GFHN 168, GFHN 169, GH 1, GXHZ, GHSZ, and YXN), aiming to analyze the effect on zinc content, growth, quality, and health risk index when spraying zinc (400 g/ha) on the leaves at the heading age. The result indicated that after foliar biofortification treatment, the zinc content and the zinc accumulation of colored rice grains could reach up to 41.55 mg/kg and 2.28 mg/pot, respectively, increased by 43.92% and 65.22%. In addition, the SPAD value and grain protein content was 42.85 and 8.49%, also increased significantly by 2.15% and 2.91%, respectively. Among these, GXHZ and GHSZ could realize the zinc content of polished rice up to 69.7 mg/kg and 55.4 mg/kg, breaking through the standard of zinc-enrich rice (45 mg/kg). GXHZ plant height increased by 11.22%, and the zinc harvest index (6.44%) and zinc use efficiency (26.79%) were the highest. Meanwhile, the biofortification promoted the SPAD value of GHSZ and the protein content of GFHN 166 by 4.95% and 24.81%, respectively. Foliar-applied zinc at the heading stage is a vital practice to get better agronomic indicators, quality, and grain zinc biofortification of colored rice. Full article

(This article belongs to the Special Issue Mineral Biofortification in Agricultural Products)

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15 pages, 890 KiB

Open AccessArticle

The Role of Digital Finance in Shaping Agricultural Economic Resilience: Evidence from Machine Learning

by Chun Yang, Wangping Liu and Jiahao Zhou

Agriculture 2024, 14(10), 1834; https://doi.org/10.3390/agriculture14101834 (registering DOI) - 18 Oct 2024

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Abstract

This study offers detailed recommendations on strengthening government support without harming digital finance benefits, especially in negatively affected areas, which is critical for enhancing the inclusiveness of the digital financial landscape and reducing social disparities. This paper uses year 2011–2022 panel data from [...] Read more.

This study offers detailed recommendations on strengthening government support without harming digital finance benefits, especially in negatively affected areas, which is critical for enhancing the inclusiveness of the digital financial landscape and reducing social disparities. This paper uses year 2011–2022 panel data from China’s 31 provinces to empirically analyze digital finance’s effects, mechanisms, and heterogeneity on agricultural economy resilience with a two-way, fixed-effect model. It further explores each feature’s impacts using machine learning methodologies like the random forest, GBRT, SHAP value method, and ALE plot. The findings show that digital finance boosted agri-economy resilience, varying by food-producing status and marketization. Among all the features analyzed, government input, urbanization level, and planting structure emerged as the most critical factors influencing agri-economy resilience. Notably, government input negatively moderated this relationship. The ALE plot revealed non-linear effects of digital finance and planting structure on agri-economy resilience. Full article

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

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15 pages, 2577 KiB

Open AccessArticle

Optimization of Manure-Based Substrate Preparation to Reduce Nutrients Losses and Improve Quality for Growth of Agaricus bisporus

by Yucong Geng, Yuhan Wang, Han Li, Rui Li, Shengxiu Ge, Hongyuan Wang, Shuxia Wu and Hongbin Liu

Agriculture 2024, 14(10), 1833; https://doi.org/10.3390/agriculture14101833 - 18 Oct 2024

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Abstract

With the growing world population, food demand has also increased, resulting in increased agricultural waste and livestock manure production. Wheat straw and cow dung are rich nutrient sources and, if not utilized properly, may lead to environmental pollution. Keeping in view the cultivation [...] Read more.

With the growing world population, food demand has also increased, resulting in increased agricultural waste and livestock manure production. Wheat straw and cow dung are rich nutrient sources and, if not utilized properly, may lead to environmental pollution. Keeping in view the cultivation of Agaricus bisporus on straw/manure-based substrate, the current study aimed to optimize the conventional manure preparation technique to reduce nutrient losses and keep the quality of manure at its best. The treatments were considered as traditional and optimized schemes for mushroom substrate preparation. The results achieved herein indicated that the nutrient losses were low in the optimum scheme. For carbon (C), the loss was 43.55% at the substrate stage in the traditional scheme and reduced to 37.75% in the optimum scheme. In the case of nitrogen (N), the loss was 22.01% in the traditional scheme and was lower (18.49%) in the optimum scheme. The nutrient concentration in Agaricus bisporus was higher with the optimum scheme compared with the traditional scheme. It was 1.74% for C, 7.17% for N, 3.58% for phosphorus (P), and 4.92% for potassium (K). The optimum scheme also improved the Agaricus bisporus yield per unit area (84.55%) and the total yield (28.92%). The net income of the optimum scheme was 102.95% higher compared to the traditional scheme. The economic analysis also revealed that the benefit–cost ratio of the optimum scheme was high (48.86%) compared with the traditional scheme. This study concludes that the use of the optimum scheme can better utilize the wheat straw and cow manure waste for substrate preparation and reducing nutrient losses. In addition, the final mushroom residue can also be used as a leftover substrate for further utilization. Full article

(This article belongs to the Special Issue Management and Migration of Pollutants for Agroecosystem Green Development)

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21 pages, 8413 KiB

Open AccessArticle

Design and Testing of a Crawler Chassis for Brush-Roller Cotton Harvesters

by Zhenlong Wang, Fanting Kong, Qing Xie, Yuanyuan Zhang, Yongfei Sun, Teng Wu and Changlin Chen

Agriculture 2024, 14(10), 1832; https://doi.org/10.3390/agriculture14101832 - 17 Oct 2024

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Abstract

In China’s Yangtze River and Yellow River basin cotton-growing regions, the complex terrain, scattered planting areas, and poor adaptability of the existing machinery have led to a mechanized cotton harvesting rate of less than 10%. To address this issue, we designed a crawler [...] Read more.

In China’s Yangtze River and Yellow River basin cotton-growing regions, the complex terrain, scattered planting areas, and poor adaptability of the existing machinery have led to a mechanized cotton harvesting rate of less than 10%. To address this issue, we designed a crawler chassis for a brush-roller cotton harvester. It is specifically tailored to meet the 76 cm row spacing agronomic requirement. We also conducted a theoretical analysis of the power transmission system for the crawler chassis. Initially, we considered the terrain characteristics of China’s inland cotton-growing regions and the current cotton agronomy practices. Based on these, we selected and designed the power system and chassis; then, a finite element static analysis was carried out on the chassis frame to ensure safety during operation; finally, field tests on the harvester’s operability, stability, and speed were carried out. The results show that the inverted trapezoidal crawler walking device, combined with a hydraulic continuously variable transmission and rear-drive design, enhances the crawler’s passability. The crawler parameters included a ground contact length of 1650 mm, a maximum ground clearance of 270 mm, a maximum operating speed of 6.1 km/h, and an actual turning radius of 2300 mm. The maximum deformation of the frame was 2.198 mm, the deformation of the walking chassis was 1.0716 mm, the maximum equivalent stress was 216.96 MPa, and the average equivalent stress of the entire frame was 5.6356 MPa, which complies with the physical properties of the selected material, Q235. The designed cotton harvester crawler chassis features stable straight-line and steering performance. The vehicle’s speed can be adjusted based on the complexity of the terrain, with timely steering responses, minimal compaction on cotton, and reduced soil damage, meeting the requirements for mechanized harvesting in China’s inland small plots. Full article

(This article belongs to the Section Agricultural Technology)

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21 pages, 1213 KiB

Open AccessArticle

The Role of Geographical Indication Products in Promoting Agricultural Development—A Meta-Analysis Based on Global Data

by Chunyan Li, Qi Ban, Jianmei Gao, Lanqing Ge and Rui Xu

Agriculture 2024, 14(10), 1831; https://doi.org/10.3390/agriculture14101831 - 17 Oct 2024

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Abstract

As an intellectual property product that is highly farmer-friendly, geographical indication (GI) products have always garnered significant attention. In recent years, research on how GI products promote agricultural development has been increasing, yet the academic community remains divided on this issue. On one [...] Read more.

As an intellectual property product that is highly farmer-friendly, geographical indication (GI) products have always garnered significant attention. In recent years, research on how GI products promote agricultural development has been increasing, yet the academic community remains divided on this issue. On one hand, some studies point out that GI products can drive agricultural development; on the other hand, other studies suggest that the impact of GI products is not significant or varies. Meta-analysis is a method that leverages statistical techniques to integrate the findings of multiple studies with a common research objective, addressing controversial issues and arriving at generalizable conclusions. Therefore, to more precisely uncover the intrinsic relationship between GI products and agricultural development and to delve deeper into the root causes of the aforementioned discrepancies, this study employed a meta-analytic approach. We extracted 478 correlation coefficients (r) as effect sizes from 82 empirical articles worldwide. Using these coefficients, we calculated the overall effect size and moderating effects of GI products on promoting agricultural development. Research indicates that GI products exert a positive influence on agricultural development. There is a low positive correlation between the two (r = 0.197). Further analysis reveals that various factors at the sample, data, literature, and methodology levels all impact the outcomes of GI products’ promotion of agricultural development. Research has shown that, in pursuit of sustainable agricultural development goals, it is further recommended that governments should accord high priority to the cultivation and development of GI products. This is aimed at providing practical insights to facilitate the sustainable advancement of GI products and bolster agricultural competitiveness. Full article

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

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18 pages, 8200 KiB

Open AccessArticle

Prediction of Potential Suitability Areas for Ephedra sinica in the Five Northwestern Provinces of China Under Climate Change

by Yibo Xu, Xiaohuang Liu, Lianrong Zhao, Jiufen Liu, Xiaofeng Zhao, Hongyu Li, Chao Wang, Honghui Zhao, Ran Wang, Xinping Luo and Liyuan Xing

Agriculture 2024, 14(10), 1830; https://doi.org/10.3390/agriculture14101830 - 17 Oct 2024

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Abstract

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially [...] Read more.

Ephedra sinica (E. sinica) holds significant economic and medicinal importance and is predominantly found in arid areas. Due to the limitations of environmental variables, growth habits, and human activities, the production and suitability areas of E. sinica have significantly decreased, especially in the five northwestern provinces of China. In this study, 212 distribution points of E. sinica and 40 environmental variables were obtained to project the habitat suitability of E. sinica under different emission scenarios in the future. It identified precipitation in the wettest month, monthly mean of the diurnal temperature difference, and solar radiation intensity in April and July as the primary environmental factors affecting the suitability of E. sinica in the region. The areas of high, medium, and low suitability in the region cover 103,000 km², 376,500 km², and 486,800 km². Under future scenarios, the suitability areas from 2021 to 2100 will decrease by 20%, with high suitability areas decreasing by 65% to 85% particularly. With comprehensive environmental variables, the suitability areas of E. sinica from 2021 to 2100 are projected, filling the gap in the projection of E. sinica suitability areas in the five northwestern provinces of China over long time period. The suitability areas show a significant decreasing trend. This research provides valuable insights into the suitability areas and crucial environmental factors, offering theoretical support for future protection and management efforts for E. sinica. Full article

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

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18 pages, 3202 KiB

Open AccessArticle

Corn Yield Prediction Based on Dynamic Integrated Stacked Regression

by Xiangjuan Liu, Qiaonan Yang, Rurou Yang, Lin Liu and Xibing Li

Agriculture 2024, 14(10), 1829; https://doi.org/10.3390/agriculture14101829 - 17 Oct 2024

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Abstract

This study focuses on the problem of corn yield prediction, and a novel prediction model based on a dynamic ensemble stacking regression algorithm is proposed. The model aims to achieve more accurate corn yield prediction based on the in-depth exploration of the potential [...] Read more.

This study focuses on the problem of corn yield prediction, and a novel prediction model based on a dynamic ensemble stacking regression algorithm is proposed. The model aims to achieve more accurate corn yield prediction based on the in-depth exploration of the potential correlations in multisource and multidimensional data. Data on the weather conditions, mechanization degree, and maize yield in Qiqihar City, Heilongjiang Province, from 1995 to 2022, are used. Important features are determined and extracted effectively by using principal component analysis and indicator contribution assessment methods. Based on the combination of an early stopping mechanism and parameter grid search optimization, the performance of eight base models, including a deep learning model, is fine-tuned. Based on the theory of heterogeneous ensemble learning, a threshold is established to stack the high-performing models, realizing a dynamic ensemble mechanism and employing averaging and optimized weighting methods for prediction. The results demonstrate that the prediction accuracy of the proposed dynamic ensemble regression model is significantly better as compared to the individual base models, with the mean squared error (MSE) being as low as 0.006, the root mean squared error (RMSE) being 0.077, the mean absolute error (MAE) being 0.061, and a high coefficient of determination value of 0.88. These findings not only validate the effectiveness of the proposed approach in the field of corn yield prediction but also highlight the positive role of multisource data fusion in enhancing the performance of prediction models. Full article

(This article belongs to the Section Digital Agriculture)

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19 pages, 857 KiB

Open AccessArticle

Research on the Antecedent Configurations of Tea Agricultural Heritage Systems for Sustainable Development from a Symbiotic Perspective

by Liyu Mao, Jie Ma, Wenxin Wu, Wenqiang Jiang and Shuisheng Fan

Agriculture 2024, 14(10), 1828; https://doi.org/10.3390/agriculture14101828 - 17 Oct 2024

Viewed by 229

Abstract

Based on the theories of symbiosis and configurational analysis, this study constructs a theoretical framework for exploring the sustainable development of tea agricultural heritage systems, with an empirical investigation of 40 typical cases in China. Utilizing fuzzy-set qualitative comparative analysis (fsQCA) and integrating [...] Read more.

Based on the theories of symbiosis and configurational analysis, this study constructs a theoretical framework for exploring the sustainable development of tea agricultural heritage systems, with an empirical investigation of 40 typical cases in China. Utilizing fuzzy-set qualitative comparative analysis (fsQCA) and integrating multi-source data, this study delves into the intricate mechanisms underlying its sustainable development. The findings indicate that the sustainable development of tea agricultural heritage systems is not determined by a single factor but results from the interplay of multiple conditions. Specifically, ecological protection performance and regional driving capacity serve as necessary conditions, while research resource allocation, industrial comprehensive strength, and heritage site development level act as sufficient conditions. Furthermore, the sustainable development pathways can be categorized into two types, namely “dual-cycle drive” and “total-factor drive”, encompassing four configurations. The “dual-cycle drive” emphasizes the mutually beneficial symbiosis between ecological and socio-economic sustainability, involving ecological protection, research resources, regional driving capacity, and industrial strength. The “total-factor drive”, on the other hand, reflects the synergistic symbiosis of ecology, socio-economy, and culture, incorporating various combinations of factors such as ecological protection, regional driving capacity, tea culture inheritance, and heritage site development. Lastly, the driving combinations leading to non-sustainable development exhibit asymmetry, suggesting that the formation of non-sustainability is not merely the reverse outcome of sustainable conditions. The absence of key conditions, such as ecological protection or regional driving capacity, results in the emergence of non-sustainable configurations. In conclusion, this study unveils the complexity and multidimensionality of the sustainable development of tea agricultural heritage systems, providing a scientific basis and practical pathways for formulating effective protection and sustainable development strategies. Full article

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

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12 pages, 2742 KiB

Open AccessArticle

Effects of OsLPR2 Gene Knockout on Rice Growth, Development, and Salt Stress Tolerance

by Ying Gu, Chengfeng Fu, Miao Zhang, Changqiang Jin, Yuqi Li, Xingyu Chen, Ruining Li, Tingting Feng, Xianzhong Huang and Hao Ai

Agriculture 2024, 14(10), 1827; https://doi.org/10.3390/agriculture14101827 - 17 Oct 2024

Viewed by 321

Abstract

Rice (Oryza sativa L.), a globally staple food crop, frequently encounters growth, developmental, and yield limitations due to phosphate deficiency. LOW PHOSPHATE ROOT1/2 (LPR1/2) are essential genes in plants that regulate primary root growth and respond [...] Read more.

Rice (Oryza sativa L.), a globally staple food crop, frequently encounters growth, developmental, and yield limitations due to phosphate deficiency. LOW PHOSPHATE ROOT1/2 (LPR1/2) are essential genes in plants that regulate primary root growth and respond to local phosphate deficiency signals under low phosphate stress. In rice, five LPR genes, designated OsLPR1–OsLPR5 based on their sequence identity with AtLPR1, have been identified. OsLPR3 and OsLPR5 are specifically expressed in roots and induced by phosphate deficiency, contributing to rice growth, development, and the maintenance of phosphorus homeostasis under low phosphate stress. In contrast, OsLPR2 is uniquely expressed in shoots, suggesting it may have distinct functions compared with other family members. This study employed Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (CRISPR/Cas9) gene editing technology to generate oslpr2 mutant transgenic lines and subsequently investigated the effect of OsLPR2 gene knockout on rice growth, phosphate utilization, and salt stress tolerance in the seedling stage, as well as the effect of OsLPR2 gene knockout on rice development and agronomic traits in the maturation stage. The results indicated that the knockout of OsLPR2 did not significantly impact rice seedling growth or phosphate utilization, which contrasts significantly with its homologous genes, OsLPR3 and OsLPR5. However, the mutation influenced various agronomic traits at maturity, including plant height, tiller number, and seed setting rate. Moreover, the OsLPR2 mutation conferred enhanced salt stress tolerance in rice. These findings underscore the distinct roles of OsLPR2 compared with other homologous genes, establishing a foundation for further investigation into the function of the OsLPR family and the functional differentiation among its members. Full article

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

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23 pages, 10596 KiB

Open AccessArticle

Advanced Nuclear Magnetic Resonance, Fourier Transform–Infrared, Visible-NearInfrared and X-ray Diffraction Methods Used for Characterization of Organo-Mineral Fertilizers Based on Biosolids

by Ramona Crainic, Elena Mihaela Nagy, Gabriel Fodorean, Mihai Vasilescu, Petru Pascuta, Florin Popa and Radu Fechete

Agriculture 2024, 14(10), 1826; https://doi.org/10.3390/agriculture14101826 - 16 Oct 2024

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Abstract

Biosolids from stabilized sludge present a high fertilization potential, due to their rich content of nutrients and organic matter. The intrinsic and subtle properties of such fertilizers may greatly influence the fertilization efficiency. In this sense, the utility, advantages and limitations of advanced [...] Read more.

Biosolids from stabilized sludge present a high fertilization potential, due to their rich content of nutrients and organic matter. The intrinsic and subtle properties of such fertilizers may greatly influence the fertilization efficiency. In this sense, the utility, advantages and limitations of advanced characterization methods, for the investigation of structural and dynamic properties at the microscopic scale of slightly different formulations of fertilizers were assessed. For that, three formulas of organo-mineral fertilizers based on biosolids (V1, V2 and V3), having at least 2% N, 2% P₂O₅, and 2% K₂O, were characterized by advanced methods, such as ¹H NMR relaxometry, ¹H MAS and ¹³C CP-MAS NMR spectroscopy, ¹H double-quantum NMR and FT-IR spectroscopy. Advanced structural characterization was performed using SEM, EDX and X-ray diffraction. Four dynamical components were identified in the NMR T₂ distribution showing that the rigid component has a percentage larger than 90%, which explains the broad band of NMR spectra confirmed by the distributions of many components in residual dipolar coupling as were revealed by ¹H DQ-NMR measurements. SEM and EDX measurements helped the identification of components from crystalline-like X-ray diffraction patterns. To evaluate the release properties of organo-mineral fertilizers, dynamic measurements of classical electric conductivity and pH were performed by placing 0.25 g of the formulas (V1, V2 and V3) in 200 mL of distilled water. The content of N and P were quantified using specific reactants, combined with VIS-nearIR spectroscopy. Two release mechanisms were observed and characterized. It was found that V3 presents the smallest release velocity but releases the largest number of fertilizers. Full article

(This article belongs to the Special Issue Effects of Fertilizer Application on Soil Physico-Chemical and Biological Properties)

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22 pages, 976 KiB

Open AccessArticle

Successes and Failures of the Implementation of the Rural Development Programme 2014–2020 Measure “Agri-Environment and Climate” in Lithuania

by Aistė Galnaitytė, Irena Kriščiukaitienė and Virginia Namiotko

Agriculture 2024, 14(10), 1825; https://doi.org/10.3390/agriculture14101825 - 16 Oct 2024

Viewed by 376

Abstract

The focus on environment and climate-friendly farming is increasingly important in the European Union (EU) Common Agricultural Policy (CAP). Activities of the Measure M10 “Agri-environment and Climate” of the Rural Development Programme (RDP) 2014–2020 were those policy instruments that pursued environmental and climate [...] Read more.

The focus on environment and climate-friendly farming is increasingly important in the European Union (EU) Common Agricultural Policy (CAP). Activities of the Measure M10 “Agri-environment and Climate” of the Rural Development Programme (RDP) 2014–2020 were those policy instruments that pursued environmental and climate goals over large areas under agricultural activities, but their effectiveness is still being questioned. After evaluating implementation successes and failures of the activities of the Measure M10 “Agri-environment and Climate” of the Lithuanian RDP 2014–2020, we aim to contribute to policy instruments that are better designed, more effective, and more attractive for farmers to achieve environmental and climate goals. This research was conducted in several stages: (1) a thorough analysis of the Measure M10 and its implementation; (2) analysis of the Measure M10 activities’ contribution to the policy target areas; (3) multi-criteria evaluation of the activities; (4) survey of beneficiaries and discussions in the focus groups. The data available from the Ministry of Agriculture of the Republic of Lithuania, Agricultural Data Center, and National Paying Agency under Ministry of Agriculture of the Republic of Lithuania was used for the analysis. Analysis of the strategic documents and data on the implementation of Measure M10 was supplemented with results from studies focused on the environmental impact of the implementation of Measure M10 in Lithuania. Multi-criteria evaluation methods were used to arrange the activities of the Measure with respect to the selected indicators. The results from the survey of beneficiaries and discussions in the focus groups let us better clarify the motives, experiences, and preferences of farmers’ participation in the activities of Measure M10. The questionnaire was distributed to 2455 beneficiaries through the National Paying Agency and 342 answers were received back, i.e., 13.9%. Five discussions in focus groups, formed from farmers participating and not participating in the activities, representatives of implementing institutions, and employees of consulting and scientific institutions, were organized. The research has revealed areas for improvement in Measure M10, and suggestions for improvement were prepared to better achieve environmental and climate objectives. Full article

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

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25 pages, 10670 KiB

Open AccessArticle

Study on a Novel Reseeding Device of a Precision Potato Planter

by Jiarui Wang, Min Liao, Hailong Xia, Rui Chen, Junju Li, Junmin Li and Jie Yang

Agriculture 2024, 14(10), 1824; https://doi.org/10.3390/agriculture14101824 - 16 Oct 2024

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Abstract

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. [...] Read more.

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l₁ and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction d_s is influenced by the initial seeding potato’s speed

v_{0 t}

, dropping height h_s, and the angle between the seeding pipe and the horizontal ground β_s. The horizontal moving distance x_r of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground β_s₂, the distance from its centroid to the reseeding door d, and the dropping height of the potato h_r. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices. Full article

(This article belongs to the Section Agricultural Technology)

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14 pages, 4478 KiB

Open AccessArticle

A New Kiwi Fruit Detection Algorithm Based on an Improved Lightweight Network

by Yi Yang, Lijun Su, Aying Zong, Wanghai Tao, Xiaoping Xu, Yixin Chai and Weiyi Mu

Agriculture 2024, 14(10), 1823; https://doi.org/10.3390/agriculture14101823 - 16 Oct 2024

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Abstract

To address the challenges associated with kiwi fruit detection methods, such as low average accuracy, inaccurate recognition of fruits, and long recognition time, this study proposes a novel kiwi fruit recognition method based on an improved lightweight network S-YOLOv4-tiny detection algorithm. Firstly, the [...] Read more.

To address the challenges associated with kiwi fruit detection methods, such as low average accuracy, inaccurate recognition of fruits, and long recognition time, this study proposes a novel kiwi fruit recognition method based on an improved lightweight network S-YOLOv4-tiny detection algorithm. Firstly, the YOLOv4-tiny algorithm utilizes the CSPdarknet53-tiny network as a backbone feature extraction network, replacing the CSPdarknet53 network in the YOLOv4 algorithm to enhance the speed of kiwi fruit recognition. Additionally, a squeeze-and-excitation network has been incorporated into the S-YOLOv4-tiny detection algorithm to improve accurate image extraction of kiwi fruit characteristics. Finally, enhancing dataset pictures using mosaic methods has improved precision in the characteristic recognition of kiwi fruits. The experimental results demonstrate that the recognition and positioning of kiwi fruits have yielded improved outcomes. The mean average precision (mAP) stands at 89.75%, with a detection precision of 93.96% and a single-picture detection time of 8.50 ms. Compared to the YOLOv4-tiny detection algorithm network, the network in this study exhibits a 7.07% increase in mean average precision and a 1.16% acceleration in detection time. Furthermore, an enhancement method based on the Squeeze-and-Excitation Network (SENet) is proposed, as opposed to the convolutional block attention module (CBAM) and efficient channel attention (ECA). This approach effectively addresses issues related to slow training speed and low recognition accuracy of kiwi fruit, offering valuable technical insights for efficient mechanical picking methods. Full article

(This article belongs to the Special Issue Advanced Image Collection, Processing, and Analysis in Crop and Livestock Management)

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17 pages, 2905 KiB

Open AccessArticle

Raspberry Production Opportunity to Develop an Agricultural Business in the Context of the Circular Economy: Case Study in South-West Romania

by Roxana-Gabriela Popa, Emil Cătălin Șchiopu, Aurelia Pătrașcu, Aniela Bălăcescu and Florentina Alina Toader

Agriculture 2024, 14(10), 1822; https://doi.org/10.3390/agriculture14101822 - 16 Oct 2024

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Abstract

This paper presents a study on the establishment and the capitalization of a remontant red raspberry crop, the Polka variety, on a privately agricultural land area of 0.2 ha in a crop with a support system in V using a geotextile membrane for [...] Read more.

This paper presents a study on the establishment and the capitalization of a remontant red raspberry crop, the Polka variety, on a privately agricultural land area of 0.2 ha in a crop with a support system in V using a geotextile membrane for soil mulching and the method of micro-irrigation by drip. It has been shown that the annual gross profit is advantageous for diversifying the population incomes of rural areas, and the red raspberry is economically profitable regarding cultivation because the recovery of the invested sum is achieved in a maximum of 5 years after the establishment of the culture. The aim of this paper is to explore the growth and commercialization of red raspberry cultivation on privately owned arable land in rural Romania, emphasizing its potential for productivity and sustainability in the context of the circular economy. This initiative not only delivers substantial profits for investors but also fosters rural development and boosts local income levels. The study demonstrates that this cultivation method of red raspberry, aligned with the principles of the circular economy, enhances sustainability by reducing waste, optimizing resource use, and involving local communities in production cycles. Full article

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

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15 pages, 2286 KiB

Open AccessArticle

The Degradation of Polyethylene by Trichoderma and Its Impact on Soil Organic Carbon

by Lixia Zhu, Yaqin Chen, Wenke Ni, Jiaxuan Zeng, Xin Li, Chunhong Hu and Lili Li

Agriculture 2024, 14(10), 1821; https://doi.org/10.3390/agriculture14101821 - 16 Oct 2024

Viewed by 283

Abstract

Polyethylene mulching film, which is widely utilized in arid and semi-arid agriculture, leaves residual pollution. A novel approach to addressing this issue is microbial degradation. To screen the strains that degrade polyethylene efficiently and clarify the effect of degrading strains on the turnover [...] Read more.

Polyethylene mulching film, which is widely utilized in arid and semi-arid agriculture, leaves residual pollution. A novel approach to addressing this issue is microbial degradation. To screen the strains that degrade polyethylene efficiently and clarify the effect of degrading strains on the turnover of soil organic carbon, a polyethylene-degrading fungus PF2, identified as Trichoderma asperellum, was isolated from long-time polyethylene-covered soil. Strain PF2 induced surface damage and ether bonds, ketone groups and other active functional groups in polyethylene, with 4.15% weight loss after 30 days, where laccase plays a key role in the degradation of polyethylene. When applied to soil, the Trichoderma-to-soil weight ratios were the following: B1: 1:100; B2: 1:200; B3: 1:300 and B4: 1:400. Trichoderma asperellum significantly increased the cumulative CO₂ mineralization and soil organic carbon mineralization in the B1 and B2 treatments compared with the control (B0). The treatments B1, B3 and B4 increased the stable organic carbon content in soil. An increase in the soil organic carbon content was observed with the application of Trichoderma asperellum, ranging from 27.87% to 58.38%. A positive correlation between CO₂ emissions and soil organic carbon was observed, with the soil carbon pool management index (CPMI) being most correlated with active organic carbon. Trichoderma treatments improved the CPMI, with B3 showing the most favorable carbon retention value. Thus, Trichoderma asperellum not only degrades polyethylene but also contributes to carbon sequestration and soil fertility when applied appropriately. Full article

(This article belongs to the Special Issue Risk Assessment and Remediation of Agricultural Soil Pollution)

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15 pages, 4872 KiB

Open AccessArticle

Infiltration Characteristics and Hydrodynamic Parameters in Response to Topographic Factors in Bare Soil Surfaces, Laboratory Experiments Based on Cropland Fields of Purple Soil in Southwest China

by Yong Wang, Ziting Ma, Dandan Li, Guirong Hou and Jiangkun Zheng

Agriculture 2024, 14(10), 1820; https://doi.org/10.3390/agriculture14101820 - 16 Oct 2024

Viewed by 261

Abstract

Topography is an important factor that impacts the hydrological processes on sloping farmlands. Yet, few studies have reported the combined influences of slope gradient and slope position on infiltration characteristics and hydrodynamic parameters on sloping croplands in purple soil regions, an important area [...] Read more.

Topography is an important factor that impacts the hydrological processes on sloping farmlands. Yet, few studies have reported the combined influences of slope gradient and slope position on infiltration characteristics and hydrodynamic parameters on sloping croplands in purple soil regions, an important area for agricultural productivity in Southwest China. Here, laboratory-simulated rainfall experiments were conducted in a steel trough (5 m long, 2 m wide, and 0.45 m deep), and rainfall lasted for 1 h at a rate of 90 mm h⁻¹ to examine the variations in the infiltration rates and hydrodynamic parameters under varying slope gradients (i.e., 3°, 6°, 10°, 15°, 21°, and 27°) and slope positions (i.e., upper, middle, and lower), and explore the relationships between the infiltration rate and the soil detachment rate. The results showed that the infiltration rate decreased gradually with duration rainfall and ultimately approached a steady state in the six slope treatments. Cumulative infiltration ranged from 15.54 to 39.32 mm during rainfall, and gradually reduced with the increase of slope gradient. The Horton’s model outperforms other models for predicting the infiltration rate with an R² value of 0.86. Factors such as Darcy–Weisbach friction, flow shear force, Manning friction coefficient, unit energy, and runoff depth varied in the following order: upper slope > middle slope > lower slope, whilst the Reynolds number and Froude number gradually increased along the slope transect from the upper to lower slope positions. A significant linear function was fitted between the soil detachment rate and the infiltration rate at the gentle slopes (3°, 6°, 10°), whereas an exponential relationship was observed at the steep slopes (15°, 21°, and 27°). Observation also suggested that 15° was the critical slope gradient of sediment detachment, infiltration characteristics, and hydrodynamic parameters. Our results provide theoretical insight for developing models that predict the impacts of topographic factors on hydrological characteristic and soil erosion in hilly agricultural landscapes of purple soil fields. Full article

(This article belongs to the Special Issue Effects of Tillage Management on Agricultural Soil Characteristics)

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