Agriculture

Exploring the transformation process of urban agricultural functions and its interaction with carbon effects based on regional differences is of great positive significance for achieving a low-carbon sustainable development of agriculture in metropolitan areas. By using the index system method, self-organizing feature maps (SOFM) network modeling, and Granger causality analysis, we divided the agricultural regional types of the Pearl River Delta (PRD) based on the spatio-temporal changes in urban agricultural functions and carbon effects at the county level in the PRD from 2002 to 2020, and analyzed the carbon effects generated by the agricultural functions according to the differences between the three agricultural regional types. The results show the following: (1) The changes in the basic functions of agriculture, the intermediate functions of agriculture, and the advanced functions of agriculture were different from the perspectives of both time and space. (2) The carbon effects produced by the areas with weak agricultural functions, the areas with medium agricultural functions, and the areas with strong agricultural functions were different. (3) The evolution of agricultural production types aggravated the grain risk in the PRD, and urban agriculture has potential in improving food security. (4) Based on the regional types of agricultural functions and considering the constraints of land and water, strategic suggestions such as integrating natural resources, improving utilization efficiency, upgrading technical facilities, and avoiding production pollution are put forward. (5) The green and low-carbon transformation of urban agriculture has its boundaries. The positive effects of the factors, namely the innovation of agricultural production methods, the change in agricultural organization modes, the impact of market orientation, and the transfer of the agricultural labor force, is limited. The findings of this paper provide valuable and meaningful insights for academia, policy makers, producers, and ultimately for the local population in general, driving the development of urban agriculture in a low-carbon and sustainable direction. Full article

Agricultural soils are considered as “hot-spots” of plastic particles; however, due to a lack of standardized method of microplastic determination in soils, as well as no legal regulations requiring the monitoring of the soil environment in the context of microplastic contamination, the data on MP abundance and occurrence in European soils are very limited. In this first study of MPs pollution in agricultural soils in Poland, we developed a method of microplastic extraction from soil samples with different properties (particle size distribution, clay and organic matter content) and used optical microscopy for MP determination and quantification. In this study, we analyzed 44 soil samples from five sampling site locations with differing soil type, agricultural activity, including farmland soils on floodplains and past records of sewage sludge and compost applications. We found evidence that 93% of cultivated soils in the SW part of Poland contained MPs. The content of MP varied between soil types and present/former use of the land. Loamy and clay soils contained more MPs, 1540 ± 912 particles per kg soil and 933 ± 682 particles per kg, respectively, compared with sandy soils at 383 ± 188 particles per kg of soil. The highest MP concentrations were determined in soils amended with sewage sludge, wastewaters and green-waste composts (up to 4050 ± 2831 particles per kg of soil). The wide distribution of MPs with a dominance of plastic fibers (up to 60% of determined MP types) can be associated with agricultural sources such as soil mulching, the use of organic fertilizers, seed coating or unintentional waste dumping and air deposition. Full article

This study proposes an improved link prediction model for predicting the “suitable for people” relationship within the knowledge graph of tea. The relationships between various types of tea and suitable target groups have yet to be fully explored, and the existing InteractE model still does not adequately capture a portion of the complex information around the interactions between entities and relationships. In this study, we integrate SENet into the feature layer of the InteractE model to enhance the capturing of helpful information in the feature channels. Additionally, the GCN layer is employed as the encoder, and the SENet-integrated InteractE model is used as the decoder to further capture the neighbour node information in the knowledge graph. Furthermore, our proposed improved model demonstrates significant improvements compared to several standard models, including the original model from public datasets (WN18RR, Kinship). Finally, we construct a tea dataset comprising 6698 records, including 330 types of tea and 29 relationship types. We predict the “suitable for people” relationship in the tea dataset through transfer learning. When comparing our model with the original model, we observed an improvement of 1.4% in H@10 for the WN18RR dataset, a 7.6% improvement in H@1 for the Kinship dataset, and a 5.2% improvement in MRR. Regarding the tea dataset, we achieved a 4.1% increase in H@3 and a 2.5% increase in H@10. This study will help to fully exploit the value potential of tea varieties and provide a reference for studies assessing healthy tea drinking. Full article

The effect of nitrogen and zinc treatment on quality and yield was studied to provide a theoretical basis for generating high-quality and high-yielding foxtail millet. In the years 2021–2022, ‘Jingu 21’ was utilized as the test material in a split-plot design. The main plot was subjected to nitrogen treatment, while the sub-plot was treated with zinc. An arrangement of random blocks was employed. Four levels of nitrogen application (0 kg/hm², 120 kg/hm², 180 kg/hm², 240 kg/hm²) and three levels of zinc application (20 mg/L, 40 mg/L, 80 mg/L foliar spraying) were set, resulting in a total of twelve treatments. Each treatment was replicated three times, with each plot covering an area of 15 m². (1) The findings indicated that the contents of crude fat and crude protein in foxtail millet increased initially and then decreased with the increase in nitrogen application concentration. Additionally, the protein components were found to be in the following order: gliadin > albumin > glutenin > globulin. (2) Adding an appropriate amount of nitrogen fertilizer under the same zinc level promoted the contents of amylose, total carotenoids, and flavonoids in millet to some extent. Over the course of two years, the content of flavonoids in millet was highest when treated with N180Zn40 (nitrogen 180 kg/hm², zinc 40 mg/L), showing an increase of 50.14% and 58.67%, respectively, compared to the treatment of applying zinc fertilizer alone at the same zinc level. (3) The phytic acid content and phytic acid/zinc molar ratio exhibited a pattern of initially decreasing and then increasing with the rise in nitrogen and zinc concentrations. (4) The application of zinc fertilizer and increased nitrogen fertilizer for two consecutive years had a significant impact on the yield of millet. Additionally, the application of zinc fertilizer had a highly significant effect on both the ear weights and thousand-kernel weights of millet (p < 0.001). The results demonstrated a positive synergistic effect when nitrogen fertilizer and zinc fertilizer were applied together. This combination significantly improved millet yield and thousand-kernel weights, enhanced the nutritional quality, and increased the content of functional components. Additionally, it also improved the availability of zinc. Full article

Leisure agriculture is a crucial carrier for city agriculture and tourism growth. This study aims to explore the overall leisure agriculture and different types of leisure agriculture spatial sub-characteristics and their influencing factors. Taking the city of Xi’an, China, as an example, leisure agriculture was classified into four types: agritainments, agricultural parks, resorts, and rural homestays. According to this study, two ring zones and one core belt zone for leisure agriculture in Xi’an are dispersed unevenly and aggregated. Furthermore, geographic detectors and spatial principal components were employed as empirical techniques to investigate the primary factors influencing the spatial distribution of multiple leisure agriculture heterogeneity. The results about the influence mechanism indicate that the gross domestic product, population density, and accessibility to transportation dominated the overall spatial distribution, while the distance to scenic spots and water areas had a significant impact on the spatial distribution of some types. This research contributes to the reconstruction of leisure agriculture and promotes the sustainable development of agriculture and recreation by merging leisure agriculture spatial resources. Full article

Soil fertility decline is a significant drawback to food and nutritional security in sub-Saharan Africa. However, information and knowledge barriers seriously impede the adoption, effective use, and scaling up of soil fertility management innovations, especially by smallholder farmers who produce the bulk of the region’s food needs. Apart from the knowledge that smallholder farmers seek soil fertility information from diverse sources, which they apply simultaneously, there is limited knowledge of farmers’ information-seeking behaviour regarding which sources are used simultaneously and the factors influencing these choices. We employed a cross-sectional survey study design to determine the simultaneous use of soil fertility information sources of 400 smallholder farming households in the Central Highlands of Kenya. We analysed the data using descriptive statistics, principal component analysis (PCA), and a multivariate probit model. The PCA distinguished seven categories of information sources farmers use: local interpersonal, cosmopolite interpersonal, aggregative, print/demonstration, broadcast media, community-based, and progressive learning sources. The intensity of use revealed that most of the smallholders used soil fertility information sources simultaneously and primarily as complements. The determinants of simultaneous use of soil fertility information sources were farmer location, marital status, main occupation, age, farming experience, exposure to agricultural training, group membership, arable land and livestock units owned, soil fertility status, soil fertility change, and soil testing. This study’s findings have implications for information dissemination strategies involving using multiple complementary sources of knowledge for improved soil health and productivity. Full article

Automatic weight detection is an essential step in the factory production of Pleurotus eryngii. In this study, a data set containing 1154 Pleurotus eryngii images was created, and then machine vision technology was used to extract eight two-dimensional features from the images. Because the fruiting bodies of Pleurotus eryngii have different shapes, these features were less correlated with weight. This paper proposed a multidimensional feature derivation method and an Attention-Based CNN model to solve this problem. This study aimed to realize the traditional feature screening task by deep learning algorithms and built an estimation model. Compared with different regression algorithms, the R², RMSE, MAE, and MAPE of the Attention-Based CNN were 0.971, 7.77, 5.69, and 5.87%, respectively, and showed the best performance. Therefore, it can be used as an accurate, objective, and effective method for automatic weight measurements of Pleurotus eryngii. Full article

Many specialty crop growers are transitioning high-value crops from in-ground production to soilless culture due to the diminishing availability of fumigants, increasing pest pressure, extreme weather, and the need for flexible production practices. The objective of this study was to determine the research and educational needs of specialty crop growers who are transitioning to soilless substrates. North American growers were surveyed using an online instrument that incorporated Likert-type statement matrices, open-ended questions, and demographic questions. Additionally, two virtually led focus groups were conducted to further expand upon the quantitative findings with descriptive data. Respondents indicated the most important factors in considering whether to adopt soilless substrates were improving, managing, and reducing overall plant quality, disease management, and crop loss, respectively. The most important research needs were understanding the effects of substrates on crop quality and uniformity, fertilizer management, and economic costs and benefits/return on investment. In both the grower survey and focus groups, crop quality and uniformity were among the highest-scored responses. Food safety, disease and pest management, consumer perception, substrate disposal-related issues, transportation, and return-on-investment were also identified as important factors when considering soilless substrates. Full article

Previous studies on sugarcane harvester extractors have mainly focused on improving harvest quality and reducing the impurity rate and loss rate, which often ignored the issue of high energy consumption. To reduce the energy consumption of the extractor while maintaining the original impurity rate and loss rate stable, firstly, a blade element analysis method with aerodynamic theory was put forward to analyze the stress of the extractor blade, and the energy consumption equation and influencing factors of extraction were obtained. Subsequently, the computational fluid dynamics model of the exhaust extractor was established. Computational fluid dynamics (CFD) and the SST k-ω model were used to analyze the mechanism of various influencing factors on the energy consumption and internal flow characteristics of the extractor. The changes in various parameters were analyzed and discussed with respect to the resulting variations in internal pressure, velocity, vortex structure, and lift–drag coefficient of the extractor. A test bench of the extractor was built, and orthogonal tests were carried out with energy consumption, impurity rate, and loss rate as test indicators. Considering the results of the simulation and bench test comprehensively, the combination of a rotational speed of 1450 RPM, a blade number of 3, an installation angle of 25°, and a blade chord length of 200 mm was optimal for the extractor. Finally, a comparative test was carried out between the optimized extractor and the original extractor. The results demonstrated that the energy consumption of the optimized extractor was reduced by 15.49%. The impurity rate decreased by 3.51%, and the loss rate decreased by 12.39% compared to the original extractor. The study can provide a theoretical and experimental basis for designing and optimizing extractor performance. Full article

Nutritional grain quality is mainly influenced by the protein fraction content and grain protein content. Quantitative trait loci (QTL) mining for five traits, about 245 and 284 BC₃F₃ individual families of two introgression line (IL) populations were derived from Kongyu 131/Cypress (population-I) and Kongyu 131/Vary Tarva Osla (population-II), respectively. A genetic linkage map was developed using 127 simple sequence repeat (SSR) markers in population-I and 119 SSR markers in population-II. In total, 20 and 5 QTLs were detected in population-I and population-II, respectively. About twenty QTLs were mapped in population-I: five QTLs for albumin, seven QTLs for globulin, six QTLs for prolamin, one QTL for glutelin, and one QTL for grain protein content. In total, five QTLs were mapped in population-II: one QTL for albumin and four QTLs for grain protein content. Out of 25 QTLs, 19 QTLs exhibit co-localization with the previously reported QTLs. QTL-like qGPC7.3 was delineated for total protein content. This QTL was derived from population-I and was successfully validated in NILs (near-isogenic lines). The grain protein phenotype showed a significant variation between two NILs. This investigation serves as groundwork for additional cloning of nutritional quality-related genes in rice grains. Full article

Food security is intrinsically linked to maintaining optimal physical health and promoting active lifestyles. Stored Grain Ecosystems (SGEs) are complex systems comprising a range of grains, microorganisms, and environmental elements. To ensure sustainable grain storage and promote food-friendly SGEs, careful regulation and monitoring of these factors are vital. This review traces the evolution of the Eco-concept of stored grain in China, focusing on micro- and macro-structural composition, the Multi-field/Re-coupling structure, and Smart Construction of SGEs, while introducing the four development lines and Wisdom Methodology of SGEs. The current status and challenges of SGEs in China are also discussed. The Eco-concept of stored grain in China has progressed through the initial exploration period, formation and practice periods, and has now entered its fourth stage, marked by a shift to include interactions of multiple biological fields. This evolution extends beyond the traditional binary relationship and offers emerging technologies greater scope for scientific and intelligent theoretical analysis of grain storage practices. The Wisdom Methodology employs a multifaceted, Mechanism and Data-driven approach, incorporating four driving methods, and is now widely recognized as a leading strategy for researching Smart Grain Systems. Digital Twin technology enables precise simulations and mappings of real-world SGEs in a virtual environment, supporting accurate assessments and early warnings for issues concerning grain conditions. Driven by Mechanism and Data, Digital Twin solutions are a pioneering trend and emerging hotspot with vast potential for enhancing the intelligence and wisdom of future grain storage processes. Overall, this review provides valuable guidance to practitioners for advancing high-quality Smart Grain Systems, enhancing sustainable and intelligent grain storage practices. Full article

In the context of tightening resource and environmental constraints, quantitative measurement and influencing factors of cultivated land use eco-efficiency (CLUE) have become hot topics in current academic research. Existing studies primarily focus on the influence of natural, social, and economic factors on CLUE but ignore exploring the impact mechanism and effect of environmental policies on CLUE. Therefore, this study aims to explore the impact of environmental regulations on CLUE. To achieve this objective, a super-efficiency slack-based measure (super-SBM) model is used to calculate the CLUE for 31 provinces (municipalities and autonomous regions) in China from 2000 to 2009. Additionally, the intermediary effect model and the threshold effect model are used to empirically investigate the transmission mechanism and nonlinear characteristics between environmental regulation and the CLUE. The results show that: (1) the temporal dynamics of CLUE exhibit a pattern of initial fluctuating decline followed by gradual growth in China as a whole and across its eastern, central, and western regions. (2) Environmental regulation has a significant negative impact on CLUE, and the effect exhibits a nonlinear characteristic of decreasing marginal effects. (3) Agricultural technological innovation and agricultural industrial structure play a mediating role between environmental regulation and CLUE, reducing the negative impact of environmental regulation on CLUE. This study provides some implications for formulating scientifically sound environmental policies to optimize land use and enhance resource utilization efficiency. Full article

The product of grapes with the highest added value is wine. Wine grapes play an important role in the evaluation of barren lands, where no other plants generally grow. Viticulture in Türkiye is generally conducted on small areas of agricultural land. In order to develop viticulture, it is important to determine suitable areas. This study presents a model for assessing land suitability for cultivation of grapevines (Vitis vinifera L.) in the Ankara region (Türkiye). The aim is to provide a spatial decision support system based on geographic information system multi-criteria assessment, taking into account the perspectives of expert agricultural engineers and local product growers. In this study, 11 criteria were evaluated to determine the most suitable locations for grapevine cultivation. The best worst method was used to calculate the weights of the determined evaluation criteria. When the spatial distribution of the areas suitable for grapevine cultivation was examined from the resulting map produced, it was seen that 1879.29 km² (7%) of highly suitability areas, 5062.03 km² (20%) of medium suitability areas, 4706.20 km² (18%) of low suitability areas, and 8355.36 km² (33%) of unsuitable areas were detected. According to the results obtained, the southern parts of the study area are more suitable for grapevine cultivation. This study will be an important and useful regional guide for agricultural land use planning and the cultivation of grapevines. Full article

Although chickpea (Cicer arietinum L.) has high yield potential, its seed yield is often low and unstable due to the impact of abiotic stresses, such as drought and heat. As a result of global warming, both drought and heat are estimated to be major yield constraints between one-quarter and one-third per annum. In the present review, genomic-mediated breeding strategies to increase resilience against global warming. Exacerbated drought and heat stresses have been examined to understand the latest advancement happening for better management of these challenges. Resistance mechanisms for drought and heat stresses consist of (i) escape via earliness, (ii) avoidance via morphological traits such as better root traits, compound leaves, or multipinnate leaves and double-/multiple-podded traits, and (iii) tolerance via molecular and physiological traits, such as special tissue and cellular abilities. Both stresses in chickpeas are quantitatively governed by minor genes and are profoundly influenced by edaphic and other environmental conditions. High-yield genotypes have traditionally been screened for resistance to drought and heat stresses in the target selection environment under stress conditions or in the simulacrum mediums under controlled conditions. There are many drought- and heat-tolerant genotypes among domestic and wild Cicer chickpeas, especially in accessions of C. reticulatum Ladiz., C. echinospermum P.H. Davis, and C. turcicum Toker, J. Berger, and Gokturk. The delineation of quantitative trait loci (QTLs) and genes allied to drought- and heat-related attributes have paved the way for designing stress-tolerant cultivars in chickpeas. Transgenic and “omics” technologies hold newer avenues for the basic understanding of background metabolic exchanges of QTLs/candidate genes for their further utilization. The overview of the effect of drought and heat stresses, its mechanisms/adaptive strategies, and markers linked to stress-related traits with their genetics and sources are pre-requisites for framing breeding programs of chickpeas with the intent of imparting drought tolerance. Ideotype chickpeas for resistance to drought and heat stresses were, therefore, developed directly using marker-aided selection over multiple locations. The current understanding of molecular breeding supported by functional genomics and omics technologies in developing drought- and heat-tolerant chickpea is discussed in this review. Full article

Pruning is an essential practice that helps control branch growth, optimize fruit size, and enhance fruit tree productivity. This study focused on ‘Valencia’ orange trees, which had experienced a decline in productivity after being cultivated on reclaimed lands for several years. The aim was to explore the impact of pruning intensity on vegetation growth, fruit yield, productivity, and fruit quality in these orange trees. The study involved 35-year-old ‘Valencia’ orange trees, which were subjected to four different levels of pruning. The pruning treatments included: T1—no pruning (control group), T2—light pruning (removal of 25% of main branches), T3—moderate pruning (removal of 50% of main branches), and T4—heavy pruning (removal of 75% of main branches). Each season, these pruning measures were consistently carried out on 15 February. The results indicated that the severity of pruning directly influenced vegetative growth parameters, such as shoot length and leaf area. As the pruning intensity increased, so did the growth of the vegetation. However, the overall volume of the tree’s canopy decreased compared to the control group. These findings provide insights into the relationship between pruning practices and the growth and productivity of ‘Valencia’ orange trees. The highest fruit yields were observed when pruning was carried out at a severity level of 75%, followed by 50 and 25%. These pruning treatments had a positive impact on various aspects of fruit quality, including weight, size, firmness, juice content, TSS (°Brix), TSS/acid ratio, and vitamin C content. Additionally, pruning contributed to a greater fruit yield per tree and an overall increase in the yield percentage. In essence, the findings suggest that pruning performed at different severity levels in February effectively promotes vegetation growth and enhances the physical and chemical properties of ‘Valencia’ orange trees. Notably, it resulted in a nearly 20% rise in fruit yield compared to the control group. Full article

Allelopathy has garnered considerable attention, but the effects of different allelochemicals on invasive plants remain unclear. This study addressed the knowledge gap surrounding allelopathy and its impact on native and invasive plant species. We focused on the impact of caffeic acid and its derivatives on the growth and competitiveness of the native Lantana indica and the invasive plant Solidago canadensis. We selected three allelochemicals, caffeic acid, methyl caffeic acid, and ethyl caffeic acid, for evaluation at two concentrations (0.1 mM and 1.0 mM). Three planting methods were employed: (1) a single species of S. canadensis, (2) a single species of L. indica, and (3) a combination of S. canadensis and L. indica. In addition, a control group was also included. Results revealed that high concentrations (1 mM) of methyl caffeate (MC) and ethyl caffeate (EC) significantly reduced seed germination rate, seed germination index, and seed germination speed index of L. indica compared to a low concentration (0.1 mM). Plant height, stem diameter, biomass, and root length in the control group (CK) of S. canadensis were significantly higher than those in the treated groups. However, with increasing allelochemical concentration, L. indica’s relative competitiveness gradually decreased. These findings provide insights into the concentration-dependent effects of allelopathic compounds on the growth of L. indica and S. canadensis. By analyzing how these allelochemicals influence the growth and competitiveness of native and invasive plants, the study sheds light on the dynamics of allelochemical interactions between these species. This knowledge can be pivotal for understanding plant competition dynamics in ecosystems and could inform strategies to control invasive species or promote native plant growth. Full article

The mutton sheep breeding industry has transformed significantly in recent years, from traditional grassland free-range farming to a more intelligent approach. As a result, automated sheep face recognition systems have become vital to modern breeding practices and have gradually replaced ear tagging and other manual tracking techniques. Although sheep face datasets have been introduced in previous studies, they have often involved pose or background restrictions (e.g., fixing of the subject’s head, cleaning of the face), which restrict data collection and have limited the size of available sample sets. As a result, a comprehensive benchmark designed exclusively for the evaluation of individual sheep recognition algorithms is lacking. To address this issue, this study developed a large-scale benchmark dataset, Sheepface-107, comprising 5350 images acquired from 107 different subjects. Images were collected from each sheep at multiple angles, including front and back views, in a diverse collection that provides a more comprehensive representation of facial features. In addition to the dataset, an assessment protocol was developed by applying multiple evaluation metrics to the results produced by three different deep learning models: VGG16, GoogLeNet, and ResNet50, which achieved F1-scores of 83.79%, 89.11%, and 93.44%, respectively. A statistical analysis of each algorithm suggested that accuracy and the number of parameters were the most informative metrics for use in evaluating recognition performance. Full article

The objective of this study is to determine the effects of the dietary replacement of soybean oil (SO) with rubber seed oil (RSO) on the growth performance, carcass trait, and lipid metabolism in Pekin ducks. A total of 160 1-day-old Pekin ducks were randomly allocated to four experimental treatments and fed diets with different ratios of SO to RSO as follows: 3:0 (control), 2:1, 1:2, and 0:3. Dietary RSO supplementation had no effect on their growth performance; however, it significantly decreased the yield of abdominal fat (p < 0.05). As the dietary RSO increased, the plasma TG, CHO, LDL-C, and HDL-C contents of ducks decreased (p < 0.05). Additionally, the contents of total fat, triglycerides, and cholesterol in the liver and breast reduced in the ducks fed RSO diets (p < 0.05). Liver n-3 PUFA levels linearly increased (p < 0.05), while the n-6/n-3 PUFA ratios reduced with increasing RSO levels (p < 0.05). Moreover, dietary RSO supplementation resulted in decreased gene expressions of FABP1, ME1, SREBP1c, FASN, DGAT2, and HMGCR (p < 0.05), while there was an increased expression of the ABCA1 gene (p < 0.05) in the liver of the ducks. In conclusion, dietary RSO supplementation reduced fat deposition and enhanced n-3 PUFA levels without affecting the growth performance of Pekin ducks. Full article

Almond production plays a very significant role in the Portuguese socio-economic context, especially with regard to dried fruit production. Indeed, Portugal is the third largest almond producer in Europe, producing 41,450 t of almonds in shells in 2021. This is due to its edaphoclimatic conditions that are favorable for its production. Traditionally, the north region of “Trás-os-Montes” has stood out as one of the most relevant for Portuguese almond production and bioeconomy. However, production in “Alentejo“ and “Beira Interior” will surpass the northern region in a short time as a result of the installation of new orchards. Despite its importance, there is a need to uncover genetic traits underlying phenotypic desirable traits needed to improve yield and quality but also cope and mitigate the impacts of climate change on their production. To address this, it is important to characterize the genetic resources available and the germplasm collection since they are crucial players for conservation and breeding initiatives. In this review, we describe the main cultivars of almonds cultivated in Portugal and their productive challenges. We also provide an overview of the main genetic resources available, breeding goals, and accomplishments regarding their improvement towards biotic and abiotic constraints in both Portugal and the rest of the world. Full article