Drivable area detection is crucial for the autonomous navigation of agricultural robots. However, semi-structured agricultural roads are generally not marked with lanes and their boundaries are ambiguous, which impedes the accurate segmentation of drivable areas and consequently paralyzes the robots. This paper proposes a deep learning network model for realizing high-resolution segmentation of agricultural roads by leveraging contextual representations to augment road objectness. The backbone adopts HRNet to extract high-resolution road features in parallel at multiple scales. To strengthen the relationship between pixels and corresponding object regions, we use object-contextual representations (OCR) to augment the feature representations of pixels. Finally, a differentiable binarization (DB) decision head is used to perform threshold-adaptive segmentation for road boundaries. To quantify the performance of our method, we used an agricultural semi-structured road dataset and conducted experiments. The experimental results show that the mIoU reaches 97.85%, and the Boundary IoU achieves 90.88%. Both the segmentation accuracy and the boundary quality outperform the existing methods, which shows the tailored segmentation networks with contextual representations are beneficial to improving the detection accuracy of the semi-structured drivable areas in agricultural scene.
{"title":"Drivable Agricultural Road Region Detection Based on Pixel-Level Segmentation with Contextual Representation Augmentation","authors":"Yefeng Sun, Liang Gong, Wei Zhang, Bishu Gao, Yanming Li, Chengliang Liu","doi":"10.3390/agriculture13091736","DOIUrl":"https://doi.org/10.3390/agriculture13091736","url":null,"abstract":"Drivable area detection is crucial for the autonomous navigation of agricultural robots. However, semi-structured agricultural roads are generally not marked with lanes and their boundaries are ambiguous, which impedes the accurate segmentation of drivable areas and consequently paralyzes the robots. This paper proposes a deep learning network model for realizing high-resolution segmentation of agricultural roads by leveraging contextual representations to augment road objectness. The backbone adopts HRNet to extract high-resolution road features in parallel at multiple scales. To strengthen the relationship between pixels and corresponding object regions, we use object-contextual representations (OCR) to augment the feature representations of pixels. Finally, a differentiable binarization (DB) decision head is used to perform threshold-adaptive segmentation for road boundaries. To quantify the performance of our method, we used an agricultural semi-structured road dataset and conducted experiments. The experimental results show that the mIoU reaches 97.85%, and the Boundary IoU achieves 90.88%. Both the segmentation accuracy and the boundary quality outperform the existing methods, which shows the tailored segmentation networks with contextual representations are beneficial to improving the detection accuracy of the semi-structured drivable areas in agricultural scene.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"11 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78406012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091739
Yuhua Wang, Qi Zhang, Jianjuan Li, S. Lin, X. Jia, Qingxu Zhang, J. Ye, Haibin Wang, Zeyan Wu
In order to fully comprehend the impact of soil acidification on the quality of tea, further analyses are essential and are of the utmost importance to the cultivation of tea trees and the simultaneous enhancement of tea quality. In May 2022, Tieguanyin tea trees planted in soils with different pH levels were selected as the research object of this study to analyze the effect of soil pH on the soil chemical index, soil fertility and the aroma quality of tea leaves. The results showed that the organic matter content, cation exchange capacity and the available nitrogen, available phosphorus and available potassium contents in the rhizosphere soil of the tea trees decreased significantly with decreasing soil pH levels (5.32–3.29), while the total nitrogen, total phosphorus and total potassium contents did not change significantly. The results of an aroma quality analysis showed that the aroma of the Tieguanyin tea was mainly floral, and the formation of floral odor characteristics was mainly derived from geraniol. The results of an interaction network analysis showed that the soil chemical indexes were significantly positively correlated with geraniol and floral aromas except for the total phosphorus and total potassium contents. In conclusion, with a decrease in the pH of soil, the soil’s cation exchange capacity, organic matter content and available nutrient content showed decreasing trends which, in turn, hindered the synthesis of geraniol and reduced the floral odor characteristics of tea leaves.
{"title":"Study on the Effect of pH on Rhizosphere Soil Fertility and the Aroma Quality of Tea Trees and Their Interactions","authors":"Yuhua Wang, Qi Zhang, Jianjuan Li, S. Lin, X. Jia, Qingxu Zhang, J. Ye, Haibin Wang, Zeyan Wu","doi":"10.3390/agriculture13091739","DOIUrl":"https://doi.org/10.3390/agriculture13091739","url":null,"abstract":"In order to fully comprehend the impact of soil acidification on the quality of tea, further analyses are essential and are of the utmost importance to the cultivation of tea trees and the simultaneous enhancement of tea quality. In May 2022, Tieguanyin tea trees planted in soils with different pH levels were selected as the research object of this study to analyze the effect of soil pH on the soil chemical index, soil fertility and the aroma quality of tea leaves. The results showed that the organic matter content, cation exchange capacity and the available nitrogen, available phosphorus and available potassium contents in the rhizosphere soil of the tea trees decreased significantly with decreasing soil pH levels (5.32–3.29), while the total nitrogen, total phosphorus and total potassium contents did not change significantly. The results of an aroma quality analysis showed that the aroma of the Tieguanyin tea was mainly floral, and the formation of floral odor characteristics was mainly derived from geraniol. The results of an interaction network analysis showed that the soil chemical indexes were significantly positively correlated with geraniol and floral aromas except for the total phosphorus and total potassium contents. In conclusion, with a decrease in the pH of soil, the soil’s cation exchange capacity, organic matter content and available nutrient content showed decreasing trends which, in turn, hindered the synthesis of geraniol and reduced the floral odor characteristics of tea leaves.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"49 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79774033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091740
Hannah Jona von Czettritz, S. Hosseini-Yekani, Johannes Schuler, K. Kersebaum, Peter Zander
Climate-induced production risk is expected to increase in the future. This study assesses the effectiveness of adapting crop rotations on arable farms in Brandenburg as a tool to enhance climate resilience. Two risk-minimizing measures are investigated: crop diversification and the inclusion of irrigated crops. Based on state-wide simulated yield data, the study compares two different scenarios. In the first scenario, the most profitable crop rotations based on predicted future weather conditions are chosen for each agro-ecological zone. In the second scenario, cropping plans are derived based on an adaption of the Target MOTAD (Minimization of Total Absolute Deviation) model taking climate-induced risks into account. A comparison of the scenarios shows a high risk reduction effect of diversification, while the economic risk reduction effect of irrigation only increases slightly. The trade-off between the highest possible gross margins and lower possible losses varies depending on the soil and climate conditions. Diversification contributed most to economic resilience in areas with moderate to low agricultural productivity. Subsidies focusing on diversification in less productive areas might be a tool to increase economic resilience with low risk-avoidance costs.
{"title":"Adapting Cropping Patterns to Climate Change: Risk Management Effectiveness of Diversification and Irrigation in Brandenburg (Germany)","authors":"Hannah Jona von Czettritz, S. Hosseini-Yekani, Johannes Schuler, K. Kersebaum, Peter Zander","doi":"10.3390/agriculture13091740","DOIUrl":"https://doi.org/10.3390/agriculture13091740","url":null,"abstract":"Climate-induced production risk is expected to increase in the future. This study assesses the effectiveness of adapting crop rotations on arable farms in Brandenburg as a tool to enhance climate resilience. Two risk-minimizing measures are investigated: crop diversification and the inclusion of irrigated crops. Based on state-wide simulated yield data, the study compares two different scenarios. In the first scenario, the most profitable crop rotations based on predicted future weather conditions are chosen for each agro-ecological zone. In the second scenario, cropping plans are derived based on an adaption of the Target MOTAD (Minimization of Total Absolute Deviation) model taking climate-induced risks into account. A comparison of the scenarios shows a high risk reduction effect of diversification, while the economic risk reduction effect of irrigation only increases slightly. The trade-off between the highest possible gross margins and lower possible losses varies depending on the soil and climate conditions. Diversification contributed most to economic resilience in areas with moderate to low agricultural productivity. Subsidies focusing on diversification in less productive areas might be a tool to increase economic resilience with low risk-avoidance costs.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"75 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91237219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091738
Da-Hee An, Dong-Chil Chang, Kwang-Soo Kim, Ji-Eun Lee, Young-Lok Cha, Jae-Hee Jeong, Ji-Bong Choi, Soo-Yeon Kim
As biochar improves soil fertility and crop productivity, there is a growing interest in it as a resource for sustainable agriculture. Miscanthus sacchariflorus has promising applications in various industries because it has a large amount of biomass. However, research on the agricultural utilization of Miscanthus-derived biochar is insufficient. The aim of this study was to demonstrate the effects of Miscanthus biochar on the soil environment and soybean growth. First, Miscanthus biochar was amended at different levels (3 or 10 tons/ha) in upland soil, after which the soil properties, root development, and yield of soybeans were compared with the control (without biochar). In the soil amended with 10 tons/ha of biochar (BC10), organic matter (OM) and available phosphate increased 1.6 and 2.0 times, respectively, compared with that in the control soil (CON). In addition, the soil dehydrogenase activity increased by 70% in BC10, and 16S rRNA gene sequence analysis revealed that the structure of the microbial community changed after amendment with biochar. The bacterial phyla that differed between CON and BC10 were Acidobacteria and Chloroflexi, which are known to be involved in carbon cycling. Owing to these changes in soil properties, the root dry weight and number of nodules in soybeans increased by 23% and 27%, respectively, and the seed yield increased 1.5-fold in BC10. In conclusion, Miscanthus biochar increased the fertility of soybean-growing soil and consequently increased seed yield. This study is valuable for the practical application of biochar for sustainable agriculture.
由于生物炭可以提高土壤肥力和作物生产力，人们对它作为可持续农业资源的兴趣日益浓厚。芒草生物量大，在工业生产中具有广阔的应用前景。然而，对芒草生物炭的农业利用研究还很不足。本研究旨在探讨芒草生物炭对土壤环境和大豆生长的影响。首先，在旱地土壤中添加不同水平(3或10吨/公顷)的芒草生物炭，然后与对照(不添加生物炭)比较土壤性质、根系发育和大豆产量。施用10 t / hm2生物炭(BC10)的土壤有机质(OM)和有效磷(速效磷)分别比对照土壤(CON)增加1.6倍和2.0倍。此外，土壤脱氢酶活性增加了70%，16S rRNA基因序列分析显示，生物炭改性后土壤微生物群落结构发生了变化。CON和BC10的细菌门类分别是参与碳循环的酸杆菌和氯氟菌。由于这些土壤性质的变化，大豆根系干重和根瘤数分别增加了23%和27%，种子产量增加了1.5倍。综上所述，芒草生物炭提高了大豆生长土壤的肥力，从而提高了种子产量。本研究对生物炭在可持续农业中的实际应用具有一定的参考价值。
{"title":"Miscanthus-Derived Biochar Enhanced Soil Fertility and Soybean Growth in Upland Soil","authors":"Da-Hee An, Dong-Chil Chang, Kwang-Soo Kim, Ji-Eun Lee, Young-Lok Cha, Jae-Hee Jeong, Ji-Bong Choi, Soo-Yeon Kim","doi":"10.3390/agriculture13091738","DOIUrl":"https://doi.org/10.3390/agriculture13091738","url":null,"abstract":"As biochar improves soil fertility and crop productivity, there is a growing interest in it as a resource for sustainable agriculture. Miscanthus sacchariflorus has promising applications in various industries because it has a large amount of biomass. However, research on the agricultural utilization of Miscanthus-derived biochar is insufficient. The aim of this study was to demonstrate the effects of Miscanthus biochar on the soil environment and soybean growth. First, Miscanthus biochar was amended at different levels (3 or 10 tons/ha) in upland soil, after which the soil properties, root development, and yield of soybeans were compared with the control (without biochar). In the soil amended with 10 tons/ha of biochar (BC10), organic matter (OM) and available phosphate increased 1.6 and 2.0 times, respectively, compared with that in the control soil (CON). In addition, the soil dehydrogenase activity increased by 70% in BC10, and 16S rRNA gene sequence analysis revealed that the structure of the microbial community changed after amendment with biochar. The bacterial phyla that differed between CON and BC10 were Acidobacteria and Chloroflexi, which are known to be involved in carbon cycling. Owing to these changes in soil properties, the root dry weight and number of nodules in soybeans increased by 23% and 27%, respectively, and the seed yield increased 1.5-fold in BC10. In conclusion, Miscanthus biochar increased the fertility of soybean-growing soil and consequently increased seed yield. This study is valuable for the practical application of biochar for sustainable agriculture.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"41 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76156691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091743
Yan-Shiang Chiou, Pei-Ing Wu, J. Liou, Ta-Ken Huang, Chu-Wei Chen
The purpose of this study is to construct a model by combining the theory of planned behavior (TPB) with conjoint analysis to evaluate baskets of agricultural goods. Each basket of agricultural goods contains various different products, including white rice and leaf vegetables are either organic or non-organic, hens’ eggs and chicken drumsticks obtained from chickens bred with and without due consideration for animal welfare, and soy sauce and jam with or without additives. The evaluation of these various features is innovative and in accordance with the shopping behavior of most consumers who, most of the time, concurrently evaluate these multi-features and multi-products. The price premium for each feature and the willingness to pay, the highest amount that a consumer is willing to pay, for a specific basket of agricultural goods is evaluated by using the multinomial logit model and the linear regression model. The relationship between essential factors in the TPB and the sociodemographic characteristics of consumers is examined. In general, the ranking of the price premium paid for products from the highest to the lowest is soy sauce, jam, chicken drumsticks, white rice, hens’ eggs, and leaf vegetables, respectively. The price premium for natural products with no additives is higher than that for organic and animal welfare-based products. The evaluation of these multi-features of agricultural goods allows us to observe the relative importance of an agricultural product through the price premium, with different combinations of other products. This indicates that the evaluation of the price premium for only a single product or for multiple products with a single feature might be either over-estimated or under-estimated.
{"title":"What Is the Willingness to Pay for a Basket of Agricultural Goods? Multi-Features of Organic, Animal Welfare-Based and Natural Products with No Additives","authors":"Yan-Shiang Chiou, Pei-Ing Wu, J. Liou, Ta-Ken Huang, Chu-Wei Chen","doi":"10.3390/agriculture13091743","DOIUrl":"https://doi.org/10.3390/agriculture13091743","url":null,"abstract":"The purpose of this study is to construct a model by combining the theory of planned behavior (TPB) with conjoint analysis to evaluate baskets of agricultural goods. Each basket of agricultural goods contains various different products, including white rice and leaf vegetables are either organic or non-organic, hens’ eggs and chicken drumsticks obtained from chickens bred with and without due consideration for animal welfare, and soy sauce and jam with or without additives. The evaluation of these various features is innovative and in accordance with the shopping behavior of most consumers who, most of the time, concurrently evaluate these multi-features and multi-products. The price premium for each feature and the willingness to pay, the highest amount that a consumer is willing to pay, for a specific basket of agricultural goods is evaluated by using the multinomial logit model and the linear regression model. The relationship between essential factors in the TPB and the sociodemographic characteristics of consumers is examined. In general, the ranking of the price premium paid for products from the highest to the lowest is soy sauce, jam, chicken drumsticks, white rice, hens’ eggs, and leaf vegetables, respectively. The price premium for natural products with no additives is higher than that for organic and animal welfare-based products. The evaluation of these multi-features of agricultural goods allows us to observe the relative importance of an agricultural product through the price premium, with different combinations of other products. This indicates that the evaluation of the price premium for only a single product or for multiple products with a single feature might be either over-estimated or under-estimated.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"9 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89249900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Pitaya industry is a specialty fruit industry in the mountainous region of Guizhou, China. The planted area in Guizhou reaches 7200 ha, ranking first in the country. At present, Pitaya planting lacks efficient yield estimation methods, which has a negative impact on the Pitaya downstream industry chain, stymying the constant growing market. The fragmented and complex terrain in karst mountainous areas and the capricious local weather have hindered accurate crop identification using traditional satellite remote sensing methods, and there is currently little attempt made to tackle the mountainous specialty crops’ yield estimation. In this paper, based on UAV (unmanned aerial vehicle) remote sensing images, the complexity of Pitaya planting sites in the karst background has been divided into three different scenes as complex scenes with similar colors, with topographic variations, and with the coexistence of multiple crops. In scenes with similar colors, using the Close Color Vegetation Index (CCVI) to extract Pitaya plants, the accuracy reached 92.37% on average in the sample sites; in scenes with complex topographic variations, using point clouds data based on the Canopy Height Model (CHM) to extract Pitaya plants, the accuracy reached 89.09%; and in scenes with the coexistence of multiple crops, using the U-Net Deep Learning Model (DLM) to identify Pitaya plants, the accuracy reached 92.76%. Thereafter, the Pitaya yield estimation model was constructed based on the fruit yield data measured in the field for several periods, and the fast yield estimations were carried out and examined for three application scenes. The results showed that the average accuracy of yield estimation in complex scenes with similar colors was 91.25%, the average accuracy of yield estimation in scenes with topographic variations was 93.40%, and the accuracy of yield estimation in scenes with the coexistence of multiple crops was 95.18%. The overall yield estimation results show a high accuracy. The experimental results show that it is feasible to use UAV remote sensing images to identify and rapidly estimate the characteristic crops in the complex karst habitat, which can also provide scientific reference for the rapid yield estimation of other crops in mountainous regions.
{"title":"Remote Sensing Identification and Rapid Yield Estimation of Pitaya Plants in Different Karst Mountainous Complex Habitats","authors":"Zhongfa Zhou, Ruiwen Peng, Ruoshuang Li, Yiqiu Li, Denghong Huang, Meng Zhu","doi":"10.3390/agriculture13091742","DOIUrl":"https://doi.org/10.3390/agriculture13091742","url":null,"abstract":"The Pitaya industry is a specialty fruit industry in the mountainous region of Guizhou, China. The planted area in Guizhou reaches 7200 ha, ranking first in the country. At present, Pitaya planting lacks efficient yield estimation methods, which has a negative impact on the Pitaya downstream industry chain, stymying the constant growing market. The fragmented and complex terrain in karst mountainous areas and the capricious local weather have hindered accurate crop identification using traditional satellite remote sensing methods, and there is currently little attempt made to tackle the mountainous specialty crops’ yield estimation. In this paper, based on UAV (unmanned aerial vehicle) remote sensing images, the complexity of Pitaya planting sites in the karst background has been divided into three different scenes as complex scenes with similar colors, with topographic variations, and with the coexistence of multiple crops. In scenes with similar colors, using the Close Color Vegetation Index (CCVI) to extract Pitaya plants, the accuracy reached 92.37% on average in the sample sites; in scenes with complex topographic variations, using point clouds data based on the Canopy Height Model (CHM) to extract Pitaya plants, the accuracy reached 89.09%; and in scenes with the coexistence of multiple crops, using the U-Net Deep Learning Model (DLM) to identify Pitaya plants, the accuracy reached 92.76%. Thereafter, the Pitaya yield estimation model was constructed based on the fruit yield data measured in the field for several periods, and the fast yield estimations were carried out and examined for three application scenes. The results showed that the average accuracy of yield estimation in complex scenes with similar colors was 91.25%, the average accuracy of yield estimation in scenes with topographic variations was 93.40%, and the accuracy of yield estimation in scenes with the coexistence of multiple crops was 95.18%. The overall yield estimation results show a high accuracy. The experimental results show that it is feasible to use UAV remote sensing images to identify and rapidly estimate the characteristic crops in the complex karst habitat, which can also provide scientific reference for the rapid yield estimation of other crops in mountainous regions.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"28 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82082358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091737
J. R. Arévalo, J. A. ENCINA-DOMÍNGUEZ, Cristina González-Montelongo, Miguel Mellado, Arturo CRUZ-ANAYA
Grasslands and pastures are extensively studied due to their geographic variation, species richness, ecological functioning, and economic importance. They are vital components of land use in many parts of the world. The impact of grassland management on species diversity and species composition has also been widely discussed, but results have been contradictory. It is well known that the relationship between species richness and the sampled area is perhaps one of the most consistent rules in plant ecology. This relationship is particularly important in biodiversity studies as it helps to predict richness at larger scales. Additionally, species richness is also influenced by absolute plant abundance, spatial patterns, and the degree of species mixing. However, species richness also depends on absolute plant abundance, spatial patterns, and the degree of mixing species. To assess this relationship, we analyzed the impact of cattle grazing on species richness at a sampling scale in the Sierra of Zapaliname, a protected area in northern Mexico. Our results revealed that the increase in plant species concerning the sampling area significantly differed in the plots excluded from grazing from the control (grazed) plots, and these relationships are differently detected in the function of the scale. Despite the lack of differences in previous studies on species richness without considering the scale, once the scale is incorporated, differences arise among both treatments. As indicated in previous studies, grazing exclusion can lead to a decrease in species richness, but we suggest that some areas of the pasture could be excluded from grazing for longer periods, as long as it is compatible with the economic needs of the local inhabitants, to investigate changes and promote diversity, especially for plant species associated with areas excluded from grazing.
{"title":"Effects of Scale, Temporal Variation and Grazing on Diversity in an Endemic Pasture in Sierra de Zapaliname, Coahuila, Mexico","authors":"J. R. Arévalo, J. A. ENCINA-DOMÍNGUEZ, Cristina González-Montelongo, Miguel Mellado, Arturo CRUZ-ANAYA","doi":"10.3390/agriculture13091737","DOIUrl":"https://doi.org/10.3390/agriculture13091737","url":null,"abstract":"Grasslands and pastures are extensively studied due to their geographic variation, species richness, ecological functioning, and economic importance. They are vital components of land use in many parts of the world. The impact of grassland management on species diversity and species composition has also been widely discussed, but results have been contradictory. It is well known that the relationship between species richness and the sampled area is perhaps one of the most consistent rules in plant ecology. This relationship is particularly important in biodiversity studies as it helps to predict richness at larger scales. Additionally, species richness is also influenced by absolute plant abundance, spatial patterns, and the degree of species mixing. However, species richness also depends on absolute plant abundance, spatial patterns, and the degree of mixing species. To assess this relationship, we analyzed the impact of cattle grazing on species richness at a sampling scale in the Sierra of Zapaliname, a protected area in northern Mexico. Our results revealed that the increase in plant species concerning the sampling area significantly differed in the plots excluded from grazing from the control (grazed) plots, and these relationships are differently detected in the function of the scale. Despite the lack of differences in previous studies on species richness without considering the scale, once the scale is incorporated, differences arise among both treatments. As indicated in previous studies, grazing exclusion can lead to a decrease in species richness, but we suggest that some areas of the pasture could be excluded from grazing for longer periods, as long as it is compatible with the economic needs of the local inhabitants, to investigate changes and promote diversity, especially for plant species associated with areas excluded from grazing.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"15 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88199317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091735
A. Dorokhov, Otari Didmanidze, A. Aksenov, Alexey Sibirev, M. Mosyakov, N. Sazonov, M. Godyaeva
The obtained results of experimental studies on the influence of the physical and mechanical properties of an elastoplastic material (clods of soil and potato tubers) on the factors of its destruction when interacting with an absolutely solid body (separating working body) established that an increase in the density of a soil clod leads to an increase in the effort expended on dynamic destruction, regardless of the size fraction. Within one fractional group, the increase in force from the minimum value necessary for the destruction of the soil clod in the density range from 1300 to 1700 kg/m3 is on average 56–67 N. However, there is a tendency to increase the effort to destroy the soil clod with an increase in the size fraction, including identical density, by 7–8 N, which is 4–5% of the initial value of the destruction force of a given density. The greatest destruction of soil clods is provided at a moisture content of 22–24%, which should be explained by the formation of the physical ripeness of the leached chernozem. In addition, a decrease in soil moisture leads to a more intense adhesion of soil particles to each other and, consequently, to an increase in the force on the soil clod to destroy it.
{"title":"The Results of Experimental Studies of the Physical and Mechanical Properties of an Elastic-Plastic Material for Tribological Properties during Separation","authors":"A. Dorokhov, Otari Didmanidze, A. Aksenov, Alexey Sibirev, M. Mosyakov, N. Sazonov, M. Godyaeva","doi":"10.3390/agriculture13091735","DOIUrl":"https://doi.org/10.3390/agriculture13091735","url":null,"abstract":"The obtained results of experimental studies on the influence of the physical and mechanical properties of an elastoplastic material (clods of soil and potato tubers) on the factors of its destruction when interacting with an absolutely solid body (separating working body) established that an increase in the density of a soil clod leads to an increase in the effort expended on dynamic destruction, regardless of the size fraction. Within one fractional group, the increase in force from the minimum value necessary for the destruction of the soil clod in the density range from 1300 to 1700 kg/m3 is on average 56–67 N. However, there is a tendency to increase the effort to destroy the soil clod with an increase in the size fraction, including identical density, by 7–8 N, which is 4–5% of the initial value of the destruction force of a given density. The greatest destruction of soil clods is provided at a moisture content of 22–24%, which should be explained by the formation of the physical ripeness of the leached chernozem. In addition, a decrease in soil moisture leads to a more intense adhesion of soil particles to each other and, consequently, to an increase in the force on the soil clod to destroy it.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"51 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90095954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091734
Zuxuan Song, Fangmei Liu, Wenbo Lv, Jianwu Yan
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.
{"title":"Classification of Urban Agricultural Functional Regions and Their Carbon Effects at the County Level in the Pearl River Delta, China","authors":"Zuxuan Song, Fangmei Liu, Wenbo Lv, Jianwu Yan","doi":"10.3390/agriculture13091734","DOIUrl":"https://doi.org/10.3390/agriculture13091734","url":null,"abstract":"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.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"5 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75149304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.3390/agriculture13091733
Agnieszka Medyńska-Juraszek, Anna Szczepańska
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.
{"title":"Microplastic Pollution in EU Farmland Soils: Preliminary Findings from Agricultural Soils (Southwestern Poland)","authors":"Agnieszka Medyńska-Juraszek, Anna Szczepańska","doi":"10.3390/agriculture13091733","DOIUrl":"https://doi.org/10.3390/agriculture13091733","url":null,"abstract":"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.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"59 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91013683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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