Rapid and non-destructive estimation of the chlorophyll content in cotton leaves is of great significance for the real-time monitoring of cotton growth under verticillium wilt (VW) stress. The spectral reflectance of healthy and VW cotton leaves was determined using hyperspectral technology, and the original spectra were processed using Savitzky–Golay (SG) smoothing, and on its basis through mean centering, standard normal variate (SG-SNV), multiplicative scatter correction (SG-MSC), reciprocal second-order differentiation, and logarithmic second-order differentiation ([lg(SG)]″) preprocessing operations. The characteristic bands were selected based on the correlation coefficient, vegetation index, successive projection algorithm (SPA), and competitive adaptive reweighted sampling (CARS). The single-factor model, back propagation neural network of particle swarm optimization algorithm, and extreme learning machine (ELM) of a grey wolf optimizer (GWO) algorithm were constructed to compare and explore the ability of each model to estimate the soil plant analysis development (SPAD) value of cotton under VW stress. The results showed that spectral pretreatment could improve the correlation between characteristic bands and SPAD values. SG-MSC and SG-SNV showed better changes in the five pretreatments, and the maximum correlation coefficients of healthy and VW cotton leaves were higher than 0.74. Compared with SPA, the accuracy of model estimation based on CARS-extracted characteristic bands was higher, and the estimation accuracy of the multi-factor model was better than that of the single-factor model under each pretreatment. For healthy cotton leaves, [lg(SG)]″–CARS–GWO–ELM was the optimal model, with a modeling and validation set R2 of 0.956 and 0.887, respectively. For VW cotton leaves, SG-MSC–CARS–GWO–ELM was the optimal model, with a modeling and validation set R2 of 0.832 and 0.824, respectively. Therefore, the GWO–ELM model constructed under different pretreatments combined with characteristic extraction methods can be used for the estimation of leaf SPAD values under VW stress to dynamically monitor VW stress in cotton and provide a theoretical reference for precision agriculture.
{"title":"Hyperspectral Estimation of SPAD Value of Cotton Leaves under Verticillium Wilt Stress Based on GWO–ELM","authors":"Xin-Ya Yuan, Xiao Zhang, Nannan Zhang, Rui Ma, Daidi He, Hao Bao, Wujun Sun","doi":"10.3390/agriculture13091779","DOIUrl":"https://doi.org/10.3390/agriculture13091779","url":null,"abstract":"Rapid and non-destructive estimation of the chlorophyll content in cotton leaves is of great significance for the real-time monitoring of cotton growth under verticillium wilt (VW) stress. The spectral reflectance of healthy and VW cotton leaves was determined using hyperspectral technology, and the original spectra were processed using Savitzky–Golay (SG) smoothing, and on its basis through mean centering, standard normal variate (SG-SNV), multiplicative scatter correction (SG-MSC), reciprocal second-order differentiation, and logarithmic second-order differentiation ([lg(SG)]″) preprocessing operations. The characteristic bands were selected based on the correlation coefficient, vegetation index, successive projection algorithm (SPA), and competitive adaptive reweighted sampling (CARS). The single-factor model, back propagation neural network of particle swarm optimization algorithm, and extreme learning machine (ELM) of a grey wolf optimizer (GWO) algorithm were constructed to compare and explore the ability of each model to estimate the soil plant analysis development (SPAD) value of cotton under VW stress. The results showed that spectral pretreatment could improve the correlation between characteristic bands and SPAD values. SG-MSC and SG-SNV showed better changes in the five pretreatments, and the maximum correlation coefficients of healthy and VW cotton leaves were higher than 0.74. Compared with SPA, the accuracy of model estimation based on CARS-extracted characteristic bands was higher, and the estimation accuracy of the multi-factor model was better than that of the single-factor model under each pretreatment. For healthy cotton leaves, [lg(SG)]″–CARS–GWO–ELM was the optimal model, with a modeling and validation set R2 of 0.956 and 0.887, respectively. For VW cotton leaves, SG-MSC–CARS–GWO–ELM was the optimal model, with a modeling and validation set R2 of 0.832 and 0.824, respectively. Therefore, the GWO–ELM model constructed under different pretreatments combined with characteristic extraction methods can be used for the estimation of leaf SPAD values under VW stress to dynamically monitor VW stress in cotton and provide a theoretical reference for precision agriculture.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"117 4 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82795515","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 : 2023-09-07DOI: 10.3390/agriculture13091775
Atif Kamran, Munazza Ghazanfar, Jan Sher Khan, Sana Pervaiz, M. H. Siddiqui, S. Alamri
Agronomic biofortification could possibly be a promising strategy to overcome zinc (Zn) deficiency in wheat; however, the cultivar’s response to foliar applications is enigmatic when it comes to the relative efficiency of Zn absorption and accumulation. To decipher that enigmatic response, this study was designed with the objectives (i) to track the amount of Zn absorbed through leaves after foliar application, (ii) to calculate the amount of the absorbed Zn actually translocated and stored in the grains, and (iii) to calculate the relative efficiency of the high yielding cultivars in terms of their Zn absorption and translocation. The results reveal that 0.90% of the zinc sprayed was absorbed through leaves, and 43% of the absorbed Zn was translocated to the grains. The cultivars significantly varied for their Zn absorption (0.71–1.07%) and subsequent translocation of the absorbed Zn (23–66%). Foliar zinc treatment also improved growth attributes such as leaf area, height, spikelet per spike, number of grains per spike, grain yield, leaf and grain Zn content, and grain protein content. These findings suggest a need for cautious parent selection in devising the breeding strategies intended for biofortification.
{"title":"Zinc Absorption through Leaves and Subsequent Translocation to the Grains of Bread Wheat after Foliar Spray","authors":"Atif Kamran, Munazza Ghazanfar, Jan Sher Khan, Sana Pervaiz, M. H. Siddiqui, S. Alamri","doi":"10.3390/agriculture13091775","DOIUrl":"https://doi.org/10.3390/agriculture13091775","url":null,"abstract":"Agronomic biofortification could possibly be a promising strategy to overcome zinc (Zn) deficiency in wheat; however, the cultivar’s response to foliar applications is enigmatic when it comes to the relative efficiency of Zn absorption and accumulation. To decipher that enigmatic response, this study was designed with the objectives (i) to track the amount of Zn absorbed through leaves after foliar application, (ii) to calculate the amount of the absorbed Zn actually translocated and stored in the grains, and (iii) to calculate the relative efficiency of the high yielding cultivars in terms of their Zn absorption and translocation. The results reveal that 0.90% of the zinc sprayed was absorbed through leaves, and 43% of the absorbed Zn was translocated to the grains. The cultivars significantly varied for their Zn absorption (0.71–1.07%) and subsequent translocation of the absorbed Zn (23–66%). Foliar zinc treatment also improved growth attributes such as leaf area, height, spikelet per spike, number of grains per spike, grain yield, leaf and grain Zn content, and grain protein content. These findings suggest a need for cautious parent selection in devising the breeding strategies intended for biofortification.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"15 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74420461","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 : 2023-09-06DOI: 10.3390/agriculture13091763
G. El Afandi, Hossam Ismael, S. Fall
Pesticides have been widely used in agriculture, resulting in significant pollution that affects both the environment and human health. This pollution is particularly prevalent in nearby agricultural areas, where sensitive resources are contaminated through spray drift exposure and surface runoff. Spray drift is a critical concern when it comes to environmental hazards. It poses health risks not only to farmers and pesticide applicators, but also to individuals living in nearby farm areas. To address this issue, developing reliable models and techniques for estimating spray drift and reducing its impact has become a crucial and efficient research topic. The current research has three primary objectives: firstly, to estimate the average pesticide application rates, trend analysis, and concentration distribution; secondly, to estimate the temporal variations of pesticide concentrations and identify the areas most likely to be affected by pesticide spray drift close to agricultural fields; and lastly, to develop a model for field spray drift and deposition integration between the OpenAir package for the R programming environment and the AgDRIFT atmospheric model. The drift model, along with precise supervised classifications, allowed for a more accurate estimation of potential drift in agricultural areas at a spatial resolution of 15 m. Additionally, multiple scenarios were conducted to evaluate the potential risks of pesticide drift outside of the target areas. This novel method effectively estimated organophosphate pesticide spray drift over two case studies in Macon County using a combination of OpenAir and AgDRIFT models and remotely sensed data. This method allowed for field simulations within completely defined exposure areas with little prior knowledge of pesticide quantities. This study concluded that 6% of total cropland is in danger of pesticide spray drift, with around 8% of crop areas exposed to potential strong drift on land use. Furthermore, 11% of cropped land is vulnerable to moderate drift, whereas around 75% of land use land cover is not vulnerable to pesticide drift. Through this research, an accurate and efficient approach has been developed to estimate spray drift and reduce its impact in agricultural areas, contributing to a safer and healthier environment for all.
{"title":"Application of OpenAir and AgDRIFT Models to Estimate Organophosphate Pesticide Spray Drift: A Case Study in Macon County, Alabama","authors":"G. El Afandi, Hossam Ismael, S. Fall","doi":"10.3390/agriculture13091763","DOIUrl":"https://doi.org/10.3390/agriculture13091763","url":null,"abstract":"Pesticides have been widely used in agriculture, resulting in significant pollution that affects both the environment and human health. This pollution is particularly prevalent in nearby agricultural areas, where sensitive resources are contaminated through spray drift exposure and surface runoff. Spray drift is a critical concern when it comes to environmental hazards. It poses health risks not only to farmers and pesticide applicators, but also to individuals living in nearby farm areas. To address this issue, developing reliable models and techniques for estimating spray drift and reducing its impact has become a crucial and efficient research topic. The current research has three primary objectives: firstly, to estimate the average pesticide application rates, trend analysis, and concentration distribution; secondly, to estimate the temporal variations of pesticide concentrations and identify the areas most likely to be affected by pesticide spray drift close to agricultural fields; and lastly, to develop a model for field spray drift and deposition integration between the OpenAir package for the R programming environment and the AgDRIFT atmospheric model. The drift model, along with precise supervised classifications, allowed for a more accurate estimation of potential drift in agricultural areas at a spatial resolution of 15 m. Additionally, multiple scenarios were conducted to evaluate the potential risks of pesticide drift outside of the target areas. This novel method effectively estimated organophosphate pesticide spray drift over two case studies in Macon County using a combination of OpenAir and AgDRIFT models and remotely sensed data. This method allowed for field simulations within completely defined exposure areas with little prior knowledge of pesticide quantities. This study concluded that 6% of total cropland is in danger of pesticide spray drift, with around 8% of crop areas exposed to potential strong drift on land use. Furthermore, 11% of cropped land is vulnerable to moderate drift, whereas around 75% of land use land cover is not vulnerable to pesticide drift. Through this research, an accurate and efficient approach has been developed to estimate spray drift and reduce its impact in agricultural areas, contributing to a safer and healthier environment for all.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"62 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74399269","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 : 2023-09-06DOI: 10.3390/agriculture13091766
Fang Wang, Jingyi Mao, Yafu Liu, Qihua Cai
The livelihood capital of rural households is an essential basis for their selection of livelihood strategy. This paper uses rural household data from the 2018 CFPS to construct a “hexagonal” framework for the analysis of livelihood capital. Natural capital, material capital, financial capital, social capital, human capital, psychological capital, and total livelihood capital are measured using entropy weight method. The paper uses logit and tobit models to analyze how livelihood capital affects rural households’ entrepreneurship. Finally, the heterogeneous impact of livelihood capital on rural households’ entrepreneurial behavior is discussed from the view of household head gender, household education level, and regional differences. The results show that rural households’ livelihood capital distribution in each dimension is uneven and the difference is great. Rural households’ capital of livelihood and finance have positive effects on their entrepreneurial behavior. Heterogeneity analysis shows that the increase in livelihood capital impacts entrepreneurship in female-headed households more positively and significantly. Livelihood capital can significantly promote the entrepreneurial behavior of rural households with lower education levels. The impact of livelihood capital on rural household entrepreneurship presents a decreasing distribution pattern from east to the middle to west. The results of the robustness test show that the conclusion of the positive impact of livelihood capital on rural household entrepreneurship is reliable. The main conclusions provide guidance and a foundation for further optimizing rural household entrepreneurship policies and promoting rural household entrepreneurship.
{"title":"Influencing Mechanism of Rural Households’ Livelihood Capital on Entrepreneurial Behavior: Evidence from the CFPS","authors":"Fang Wang, Jingyi Mao, Yafu Liu, Qihua Cai","doi":"10.3390/agriculture13091766","DOIUrl":"https://doi.org/10.3390/agriculture13091766","url":null,"abstract":"The livelihood capital of rural households is an essential basis for their selection of livelihood strategy. This paper uses rural household data from the 2018 CFPS to construct a “hexagonal” framework for the analysis of livelihood capital. Natural capital, material capital, financial capital, social capital, human capital, psychological capital, and total livelihood capital are measured using entropy weight method. The paper uses logit and tobit models to analyze how livelihood capital affects rural households’ entrepreneurship. Finally, the heterogeneous impact of livelihood capital on rural households’ entrepreneurial behavior is discussed from the view of household head gender, household education level, and regional differences. The results show that rural households’ livelihood capital distribution in each dimension is uneven and the difference is great. Rural households’ capital of livelihood and finance have positive effects on their entrepreneurial behavior. Heterogeneity analysis shows that the increase in livelihood capital impacts entrepreneurship in female-headed households more positively and significantly. Livelihood capital can significantly promote the entrepreneurial behavior of rural households with lower education levels. The impact of livelihood capital on rural household entrepreneurship presents a decreasing distribution pattern from east to the middle to west. The results of the robustness test show that the conclusion of the positive impact of livelihood capital on rural household entrepreneurship is reliable. The main conclusions provide guidance and a foundation for further optimizing rural household entrepreneurship policies and promoting rural household entrepreneurship.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"15 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75276334","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 : 2023-09-06DOI: 10.3390/agriculture13091767
Ching-Cheng Shen, Danhe Wang
Maintaining the sustainable development of fascinating resources in Taiwan’s Hualien and Taitung (Huatung) regions is the basis of organic agritourism. Loyalty not only represents tourists’ commitment to return and recommend but also serves as a goal for destination development. The purpose of this study is to propose and examine the effect of destination fascination on loyalty through a conceptualized Reasonable Person Model (RPM), mediated by place attachment and pro-environmental behaviors. SPSS21 and the linear structure relationship model (LISREL) were used as data analysis tools in this study. A total of 500 valid online questionnaires were collected through snowballing and convenience sampling. The data analysis results revealed that destination fascination has a positive and significant impact on loyalty through place attachment and pro-environmental behavior. Another finding is that place dependence, place identity, and pro-environmental behavior all have mediating effects, with place identity being the main mediating variable. The contributions of this study are mainly reflected in examining the application of RPM in fascination and loyalty, as well as providing practical suggestions for destination fascination and place identity.
{"title":"Using the RPM Model to Explore the Impact of Organic Agritourism Destination Fascination on Loyalty—The Mediating Roles of Place Attachment and Pro-Environmental Behavior","authors":"Ching-Cheng Shen, Danhe Wang","doi":"10.3390/agriculture13091767","DOIUrl":"https://doi.org/10.3390/agriculture13091767","url":null,"abstract":"Maintaining the sustainable development of fascinating resources in Taiwan’s Hualien and Taitung (Huatung) regions is the basis of organic agritourism. Loyalty not only represents tourists’ commitment to return and recommend but also serves as a goal for destination development. The purpose of this study is to propose and examine the effect of destination fascination on loyalty through a conceptualized Reasonable Person Model (RPM), mediated by place attachment and pro-environmental behaviors. SPSS21 and the linear structure relationship model (LISREL) were used as data analysis tools in this study. A total of 500 valid online questionnaires were collected through snowballing and convenience sampling. The data analysis results revealed that destination fascination has a positive and significant impact on loyalty through place attachment and pro-environmental behavior. Another finding is that place dependence, place identity, and pro-environmental behavior all have mediating effects, with place identity being the main mediating variable. The contributions of this study are mainly reflected in examining the application of RPM in fascination and loyalty, as well as providing practical suggestions for destination fascination and place identity.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"18 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74474307","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 : 2023-09-06DOI: 10.3390/agriculture13091765
Kai Qiu, Zhimin Chen, A. Zheng, Wenhuan Chang, Huiyi Cai, Xin Zhang, Guohua Liu
This study aimed to disclose the effects of a new compound organic acidifier mixing with L-malic acid and L-lactic acid on broiler production. A total of 1000 1-day-old Arbor acres broiler chicks were randomly divided into two treatments of 10 replicates each, with 50 birds per replicate. The feeding trial lasted for 42 days. The treatment group was offered 0.8% of the acidifier based on the control. The growth performance of the broiler chickens was improved by treatment. The broiler chickens in treatment had lower triglyceride but higher high-density lipoprotein content in serum. Superoxide dismutase activity, total antioxidant capacity and the concentrations of immunoglobulin A, complement 3 and lysozyme were increased in the serum of the broiler chickens, while the concentrations of interleukin-2 and tumor necrosis factor-α in the mucosa of jejunum were decreased by treatment. The expressions of AMPK, CD36, FABP1, MTTP and PPARα were increased but expressions of APOB100 and PCSK9 were decreased by treatment. In conclusion, the acidifier was effective at promoting broiler production, which was probably through the improved immunity, antioxidant and hepatic lipid metabolism capacities. The acidifier may be accelerating lipid metabolism in broiler chicken liver through regulating the expression of the genes related to fat metabolism.
{"title":"Augmentation of Performance, Carcass Trait, Biochemical Profile and Lipid Metabolism Concerning the Use of Organic Acidifier in Broiler Chickens","authors":"Kai Qiu, Zhimin Chen, A. Zheng, Wenhuan Chang, Huiyi Cai, Xin Zhang, Guohua Liu","doi":"10.3390/agriculture13091765","DOIUrl":"https://doi.org/10.3390/agriculture13091765","url":null,"abstract":"This study aimed to disclose the effects of a new compound organic acidifier mixing with L-malic acid and L-lactic acid on broiler production. A total of 1000 1-day-old Arbor acres broiler chicks were randomly divided into two treatments of 10 replicates each, with 50 birds per replicate. The feeding trial lasted for 42 days. The treatment group was offered 0.8% of the acidifier based on the control. The growth performance of the broiler chickens was improved by treatment. The broiler chickens in treatment had lower triglyceride but higher high-density lipoprotein content in serum. Superoxide dismutase activity, total antioxidant capacity and the concentrations of immunoglobulin A, complement 3 and lysozyme were increased in the serum of the broiler chickens, while the concentrations of interleukin-2 and tumor necrosis factor-α in the mucosa of jejunum were decreased by treatment. The expressions of AMPK, CD36, FABP1, MTTP and PPARα were increased but expressions of APOB100 and PCSK9 were decreased by treatment. In conclusion, the acidifier was effective at promoting broiler production, which was probably through the improved immunity, antioxidant and hepatic lipid metabolism capacities. The acidifier may be accelerating lipid metabolism in broiler chicken liver through regulating the expression of the genes related to fat metabolism.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"40 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89356101","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 : 2023-09-06DOI: 10.3390/agriculture13091764
Fabrício Lopes Macedo, C. Ragonezi, Fábio Reis, José G. R. de Freitas, David Horta Lopes, António Miguel Franquinho Aguiar, Délia Cravo, Miguel A. A. Pinheiro de Carvalho
Drosophila suzukii is one of the main pests that attack soft-skinned fruits and cause significant economic damage worldwide. Madeira Island (Portugal) is already affected by this pest. The present work aimed to investigate the potential distribution of D. suzukii on Madeira Island to better understand the limits of its geographical distribution on the island using the Maximum Entropy modeling (MaxEnt). The resultant model provided by MaxEnt was rated as regular discrimination with the area under the curve (AUC, 0.7–0.8). Upon scrutinizing the environmental variables with the greatest impact on the distribution of D. suzukii, altitude emerged as the dominant contributor, with the highest percentage (71.2%). Additionally, elevations ranging from 0 to 500 m were identified as appropriate for the species distribution. With the results of the model, it becomes possible to understand/predict which locations will be most suitable for the establishment of the analyzed pest and could be further applied not only for D. suzukii but also for other species that hold the potential for substantial economic losses in this insular region.
{"title":"Prediction of the Potential Distribution of Drosophila suzukii on Madeira Island Using the Maximum Entropy Modeling","authors":"Fabrício Lopes Macedo, C. Ragonezi, Fábio Reis, José G. R. de Freitas, David Horta Lopes, António Miguel Franquinho Aguiar, Délia Cravo, Miguel A. A. Pinheiro de Carvalho","doi":"10.3390/agriculture13091764","DOIUrl":"https://doi.org/10.3390/agriculture13091764","url":null,"abstract":"Drosophila suzukii is one of the main pests that attack soft-skinned fruits and cause significant economic damage worldwide. Madeira Island (Portugal) is already affected by this pest. The present work aimed to investigate the potential distribution of D. suzukii on Madeira Island to better understand the limits of its geographical distribution on the island using the Maximum Entropy modeling (MaxEnt). The resultant model provided by MaxEnt was rated as regular discrimination with the area under the curve (AUC, 0.7–0.8). Upon scrutinizing the environmental variables with the greatest impact on the distribution of D. suzukii, altitude emerged as the dominant contributor, with the highest percentage (71.2%). Additionally, elevations ranging from 0 to 500 m were identified as appropriate for the species distribution. With the results of the model, it becomes possible to understand/predict which locations will be most suitable for the establishment of the analyzed pest and could be further applied not only for D. suzukii but also for other species that hold the potential for substantial economic losses in this insular region.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"118 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86824190","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 : 2023-09-06DOI: 10.3390/agriculture13091769
Dansong Yue, Shuqi Shang, Kai Feng, Haiqing Wang, Xiaoning He, Zelong Zhao, Ning Zhang, Baiqiang Zuo, Dongwei Wang
Improving the positioning accuracy and stability of a single BDS/INS sensor system in agricultural machinery is important for expanding the application scenarios of agricultural machinery. This paper proposes a navigation and positioning model based on an improved bee-colony-algorithm-optimized BP network (the IABC-BP model). The main aspect of this work involves introducing adaptive coefficients and speed adjustment coefficients that obey Gaussian distribution to ensure the balance between the rate of convergence, group flexibility, and searchability in the search process. The implicit adaptive layer formula of the BP network is proposed, and the BDS/INS navigation and positioning model for agricultural machinery is established using the IABC algorithm and the Kalman filter. Simulation tests and analyses of real-world application scenarios were conducted on the model, and the results showed that, compared with the original model, the performance of the model improved by 90.65%, 84.11%, and 25.96%, indicating that the proposed model has high accuracy and effectiveness. In the information fusion and compensation correction mode, the algorithm processes errors such as longitude and latitude within the target range and can achieve reliable navigation and positioning accuracy in a short period. At the same time, the model has good stability and generalization ability, and can be applied to other navigation scenarios in the future to expand its application scope.
{"title":"Research on the Model of a Navigation and Positioning Algorithm for Agricultural Machinery Based on the IABC-BP Network","authors":"Dansong Yue, Shuqi Shang, Kai Feng, Haiqing Wang, Xiaoning He, Zelong Zhao, Ning Zhang, Baiqiang Zuo, Dongwei Wang","doi":"10.3390/agriculture13091769","DOIUrl":"https://doi.org/10.3390/agriculture13091769","url":null,"abstract":"Improving the positioning accuracy and stability of a single BDS/INS sensor system in agricultural machinery is important for expanding the application scenarios of agricultural machinery. This paper proposes a navigation and positioning model based on an improved bee-colony-algorithm-optimized BP network (the IABC-BP model). The main aspect of this work involves introducing adaptive coefficients and speed adjustment coefficients that obey Gaussian distribution to ensure the balance between the rate of convergence, group flexibility, and searchability in the search process. The implicit adaptive layer formula of the BP network is proposed, and the BDS/INS navigation and positioning model for agricultural machinery is established using the IABC algorithm and the Kalman filter. Simulation tests and analyses of real-world application scenarios were conducted on the model, and the results showed that, compared with the original model, the performance of the model improved by 90.65%, 84.11%, and 25.96%, indicating that the proposed model has high accuracy and effectiveness. In the information fusion and compensation correction mode, the algorithm processes errors such as longitude and latitude within the target range and can achieve reliable navigation and positioning accuracy in a short period. At the same time, the model has good stability and generalization ability, and can be applied to other navigation scenarios in the future to expand its application scope.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"124 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87845829","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 : 2023-09-06DOI: 10.3390/agriculture13091768
S. Vršič, Mojca Gumzej, Mario Lešnik, Andrej Perko, B. Pulko
The long-term use of copper (Cu) fungicides in viticulture in Europe has led to Cu accumulation in vineyard top soils. However, less is known about the accumulation of Cu in grapevine grafts after the callusing process/before planting in the nursery. This paper presents the capacity of 5BB and SO4 rootstocks to accumulate Cu, as well as the patterns of translocation in the grafts. After heat forcing (callusing), the grapevine grafts of Sauvignon Blanc on 5BB and SO4 rootstocks were grown in pots for six months in a glasshouse and exposed to various Cu formulations (Cu-oxychloride, Cu-gluconate) and concentrations in peat (50, 150, 500, and 1000 mg Cu of dry weight (DW)). In addition to monitoring the shoot growth dynamics and analyzing the copper content in graft organs, bioaccumulation (BAFs) and translocation factors (TFs) of Cu were calculated. The mean Cu concentrations were ranked as follows: roots (15–164) > rootstock trunks (8–38) > canes (5–21) mg kg−1 DW. The Cu concentrations depended on the Cu formulation and concentration in the substrate. Higher Cu content was found in the roots of both rootstocks (5BB and SO4, 23–155 and 15–164 mg kg−1 DW, respectively) and the lowest in the canes (less than 10 mg kg−1 DW) of grafts grown in Cu-oxychloride-treated peat. Based on the BAFs and TFs, both rootstocks could be considered as Cu exclusive. A higher translocation rate was determined in systemic Cu-gluconate and SO4 rootstock. With shoot length measurements, the significant inhibitory effects of Cu on grapevine grafts growth could not be confirmed, despite the inhibitory effects that were clearly expressed in the first two months of growth. Soils containing more than 500 mg Cu/kg−1 are less suitable for growing vine grafts.
{"title":"Patterns of Copper Bioaccumulation and Translocation in Grapevine Grafts Depending on Rootstocks","authors":"S. Vršič, Mojca Gumzej, Mario Lešnik, Andrej Perko, B. Pulko","doi":"10.3390/agriculture13091768","DOIUrl":"https://doi.org/10.3390/agriculture13091768","url":null,"abstract":"The long-term use of copper (Cu) fungicides in viticulture in Europe has led to Cu accumulation in vineyard top soils. However, less is known about the accumulation of Cu in grapevine grafts after the callusing process/before planting in the nursery. This paper presents the capacity of 5BB and SO4 rootstocks to accumulate Cu, as well as the patterns of translocation in the grafts. After heat forcing (callusing), the grapevine grafts of Sauvignon Blanc on 5BB and SO4 rootstocks were grown in pots for six months in a glasshouse and exposed to various Cu formulations (Cu-oxychloride, Cu-gluconate) and concentrations in peat (50, 150, 500, and 1000 mg Cu of dry weight (DW)). In addition to monitoring the shoot growth dynamics and analyzing the copper content in graft organs, bioaccumulation (BAFs) and translocation factors (TFs) of Cu were calculated. The mean Cu concentrations were ranked as follows: roots (15–164) > rootstock trunks (8–38) > canes (5–21) mg kg−1 DW. The Cu concentrations depended on the Cu formulation and concentration in the substrate. Higher Cu content was found in the roots of both rootstocks (5BB and SO4, 23–155 and 15–164 mg kg−1 DW, respectively) and the lowest in the canes (less than 10 mg kg−1 DW) of grafts grown in Cu-oxychloride-treated peat. Based on the BAFs and TFs, both rootstocks could be considered as Cu exclusive. A higher translocation rate was determined in systemic Cu-gluconate and SO4 rootstock. With shoot length measurements, the significant inhibitory effects of Cu on grapevine grafts growth could not be confirmed, despite the inhibitory effects that were clearly expressed in the first two months of growth. Soils containing more than 500 mg Cu/kg−1 are less suitable for growing vine grafts.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"35 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90741679","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 : 2023-09-05DOI: 10.3390/agriculture13091761
N. Khuong, Nguyen Thi Thuy Dung, Lê Thị Mỹ Thu, L. T. Quang, L. Xuan, Ngô Thanh Phong
Saline soils negatively affect and cause serious problems for rice cultivation. This study aimed to evaluate the efficacy of the purple nonsulfur bacteria (PNSB) capable of secreting 5-aminolevulinic acid (ALA) to reduce soil salinity, improve soil fertility, and enhance rice growth and yield. A two-factorial experiment was conducted in a randomized complete block design with four replications. Factor one was the salinity of the irrigated water, and factor two was the supplementation of the ALA-producing PNSB. The results indicated that watering with saline water above 3‰ led to decreases in plant growth and rice yield compared to the treatments watered with tap water. Application of either an individual strain or the mixture of W01, W14, and W22 ameliorated soil properties and increased total NPK uptake, whereas treatments supplied with the mixed strains reduced total Na uptake (9.50 mg Na pot−1). Supplying the W01, W14, and W22 strains individually or in a mixture enhanced the plant height by 3.51–5.45% and rice grain yield by 14.7–26.2%, compared with those of the control treatment. From the study, the combination of the L. sphaeroides W01, W14, and W22 strains is promising for application in saline or salt-contaminated regions to aid the damages caused by salinity on cultivars there, especially rice. Furthermore, this is a biological approach to ease an environmental problem and improve crop performance, which is supposed to be a trend in the sustainable agriculture.
盐碱地对水稻种植产生负面影响并造成严重问题。本研究旨在评价能分泌5-氨基乙酰丙酸(ALA)的紫色非硫细菌(PNSB)降低土壤盐分、提高土壤肥力、促进水稻生长和产量的效果。双因子试验采用随机完全区组设计，共4个重复。因子一是灌溉水的盐度，因子二是产生ala的PNSB的补充。结果表明，与自来水处理相比，施用高于3‰的咸水对水稻植株生长和产量有一定的影响。单独施用或W01、W14和W22混合施用均改善了土壤性质，增加了氮磷钾的总吸收量，而混合施用则降低了总钠吸收量(9.50 mg Na pot - 1)。与对照处理相比，单独或混合施用W01、W14和W22株可使水稻株高提高3.51 ~ 5.45%，稻米产量提高14.7 ~ 26.2%。研究结果表明，sphaeroides W01、W14和W22菌株组合应用于盐渍或盐污染地区，可以缓解盐渍对当地品种特别是水稻造成的危害。此外，这是一种缓解环境问题和提高作物性能的生物方法，这应该是可持续农业的一个趋势。
{"title":"The Efficacy of 5-Aminolevulinic Acid-Producing Luteovulum sphaeroides Strains on Saline Soil Fertility, Nutrient Uptakes, and Yield of Rice","authors":"N. Khuong, Nguyen Thi Thuy Dung, Lê Thị Mỹ Thu, L. T. Quang, L. Xuan, Ngô Thanh Phong","doi":"10.3390/agriculture13091761","DOIUrl":"https://doi.org/10.3390/agriculture13091761","url":null,"abstract":"Saline soils negatively affect and cause serious problems for rice cultivation. This study aimed to evaluate the efficacy of the purple nonsulfur bacteria (PNSB) capable of secreting 5-aminolevulinic acid (ALA) to reduce soil salinity, improve soil fertility, and enhance rice growth and yield. A two-factorial experiment was conducted in a randomized complete block design with four replications. Factor one was the salinity of the irrigated water, and factor two was the supplementation of the ALA-producing PNSB. The results indicated that watering with saline water above 3‰ led to decreases in plant growth and rice yield compared to the treatments watered with tap water. Application of either an individual strain or the mixture of W01, W14, and W22 ameliorated soil properties and increased total NPK uptake, whereas treatments supplied with the mixed strains reduced total Na uptake (9.50 mg Na pot−1). Supplying the W01, W14, and W22 strains individually or in a mixture enhanced the plant height by 3.51–5.45% and rice grain yield by 14.7–26.2%, compared with those of the control treatment. From the study, the combination of the L. sphaeroides W01, W14, and W22 strains is promising for application in saline or salt-contaminated regions to aid the damages caused by salinity on cultivars there, especially rice. Furthermore, this is a biological approach to ease an environmental problem and improve crop performance, which is supposed to be a trend in the sustainable agriculture.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"92 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91112374","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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