Pub Date : 2023-09-07DOI: 10.3390/agriculture13091773
G. Kulczycki, Elżbieta Sacała, Anna Koszelnik-Leszek, Łukasz Milo
The aim of the study was to compare sulfate fertilizers and mixtures of elemental sulfur (S0) and sulfate in terms of yield and nitrogen (N) and sulfur (S) status in perennial ryegrass. Mixtures of sulfate and S0 can reduce the consumption of sulfate alone. The plants were grown in soil cultures. The plants were supplemented with S0, K2SO4, MgSO4, and (NH4)SO4 or a mixture of these salts with So. Two sulfur doses were applied and the ryegrass was harvested three times. Fresh and dry weights of each swath, the N and S content, and their uptake were determined. The total fresh yield of sulfur-fertilized plants was 25 to 94% higher compared to unfertilized plants. The increases in dry matter were even more significant. Fertilizers, being a mixture of S0 and sulfate, showed the same efficiency as those containing sulfate alone. Sulfur fertilization resulted in a higher S content and its uptake, lowered N concentration in second and third swatch, and a decrease in total N uptake. In conclusion, to achieve high crop yields, soil sulfur deficiency should be corrected and fertilizers that are the mixture of elemental sulfur and sulfate are a beneficial and effective approach.
{"title":"Perennial Ryegrass (Lolium perenne L.) Response to Different Forms of Sulfur Fertilizers","authors":"G. Kulczycki, Elżbieta Sacała, Anna Koszelnik-Leszek, Łukasz Milo","doi":"10.3390/agriculture13091773","DOIUrl":"https://doi.org/10.3390/agriculture13091773","url":null,"abstract":"The aim of the study was to compare sulfate fertilizers and mixtures of elemental sulfur (S0) and sulfate in terms of yield and nitrogen (N) and sulfur (S) status in perennial ryegrass. Mixtures of sulfate and S0 can reduce the consumption of sulfate alone. The plants were grown in soil cultures. The plants were supplemented with S0, K2SO4, MgSO4, and (NH4)SO4 or a mixture of these salts with So. Two sulfur doses were applied and the ryegrass was harvested three times. Fresh and dry weights of each swath, the N and S content, and their uptake were determined. The total fresh yield of sulfur-fertilized plants was 25 to 94% higher compared to unfertilized plants. The increases in dry matter were even more significant. Fertilizers, being a mixture of S0 and sulfate, showed the same efficiency as those containing sulfate alone. Sulfur fertilization resulted in a higher S content and its uptake, lowered N concentration in second and third swatch, and a decrease in total N uptake. In conclusion, to achieve high crop yields, soil sulfur deficiency should be corrected and fertilizers that are the mixture of elemental sulfur and sulfate are a beneficial and effective approach.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"78 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79875143","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/agriculture13091771
Fangfang Ning, P. M. Nkebiwe, Jens Hartung, Sebastian Munz, Shoubing Huang, Shunli Zhou, Simone Graeff-Hönninger
In the context of phosphorus (P) exhaustion and low P use efficiency (PUE) in crop production, a field trial was designed on a low-P soil in southwestern Germany in 2020 and 2021 to investigate the effects of P fertilizer type and liming on maize growth and P uptake and PUE. The experimental factors were (i) two P fertilizer types, rock phosphate (RP) and diammonium phosphate (DAP); (ii) lime application, lime and no lime; and (iii) two maize cultivars. The results showed that RP resulted in a lower leaf area index and light interception compared with DAP, a 33% lower silage yield, and a 29% lower P content at harvest. The PUE of RP was 18%, which was 37% lower than DAP. Soil liming reduced shoot biomass and led to 35% less shoot P content at the six-leaf stage. The maize cultivar Stabil expressed higher yielding and P acquisition characteristics. In conclusion, DAP cannot be replaced by placed RP, regardless of the lime application in silage maize production in this study. Future research on the PUE of maize cultivars should also consider root characteristics in response to P fertilizer type and soil pH.
{"title":"Phosphate Fertilizer Type and Liming Affect the Growth and Phosphorus Uptake of Two Maize Cultivars","authors":"Fangfang Ning, P. M. Nkebiwe, Jens Hartung, Sebastian Munz, Shoubing Huang, Shunli Zhou, Simone Graeff-Hönninger","doi":"10.3390/agriculture13091771","DOIUrl":"https://doi.org/10.3390/agriculture13091771","url":null,"abstract":"In the context of phosphorus (P) exhaustion and low P use efficiency (PUE) in crop production, a field trial was designed on a low-P soil in southwestern Germany in 2020 and 2021 to investigate the effects of P fertilizer type and liming on maize growth and P uptake and PUE. The experimental factors were (i) two P fertilizer types, rock phosphate (RP) and diammonium phosphate (DAP); (ii) lime application, lime and no lime; and (iii) two maize cultivars. The results showed that RP resulted in a lower leaf area index and light interception compared with DAP, a 33% lower silage yield, and a 29% lower P content at harvest. The PUE of RP was 18%, which was 37% lower than DAP. Soil liming reduced shoot biomass and led to 35% less shoot P content at the six-leaf stage. The maize cultivar Stabil expressed higher yielding and P acquisition characteristics. In conclusion, DAP cannot be replaced by placed RP, regardless of the lime application in silage maize production in this study. Future research on the PUE of maize cultivars should also consider root characteristics in response to P fertilizer type and soil pH.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"121 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85891796","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/agriculture13091777
Yixin Huang, Rishi Srivastava, Chloe Ngo, Jerry Gao, Jane Wu, Sen Chiao
Food shortage issues affect more and more of the population globally as a consequence of the climate crisis, wars, and the COVID-19 pandemic. Increasing crop output has become one of the urgent priorities for many countries. To raise the productivity of the crop product, it is necessary to monitor and evaluate farmland soil quality by analyzing the physical and chemical properties of soil since the soil is the base to provide nutrition to the crop. As a result, soil analysis contributes greatly to maintaining the sustainability of soil in producing crops regularly. Recently, some agriculture researchers have started using machine learning approaches to conduct soil analysis, targeting the different soil analysis needs separately. The optimal method is to consider all those features (climate, soil chemicals, nutrition, and geolocations) based on the growing crops and production cycle for soil analysis. The contribution of this project is to combine soil analysis, including crop identification, irrigation recommendations, and fertilizer analysis, with data-driven machine learning models and to create an interactive user-friendly system (Soil Analysis System) by using real-time satellite data and remote sensor data. The system provides a more sustainable and efficient way to help farmers harvest with better usages of land, water, and fertilizer. According to our analysis results, this combined approach is promising and efficient for smart farming.
{"title":"Data-Driven Soil Analysis and Evaluation for Smart Farming Using Machine Learning Approaches","authors":"Yixin Huang, Rishi Srivastava, Chloe Ngo, Jerry Gao, Jane Wu, Sen Chiao","doi":"10.3390/agriculture13091777","DOIUrl":"https://doi.org/10.3390/agriculture13091777","url":null,"abstract":"Food shortage issues affect more and more of the population globally as a consequence of the climate crisis, wars, and the COVID-19 pandemic. Increasing crop output has become one of the urgent priorities for many countries. To raise the productivity of the crop product, it is necessary to monitor and evaluate farmland soil quality by analyzing the physical and chemical properties of soil since the soil is the base to provide nutrition to the crop. As a result, soil analysis contributes greatly to maintaining the sustainability of soil in producing crops regularly. Recently, some agriculture researchers have started using machine learning approaches to conduct soil analysis, targeting the different soil analysis needs separately. The optimal method is to consider all those features (climate, soil chemicals, nutrition, and geolocations) based on the growing crops and production cycle for soil analysis. The contribution of this project is to combine soil analysis, including crop identification, irrigation recommendations, and fertilizer analysis, with data-driven machine learning models and to create an interactive user-friendly system (Soil Analysis System) by using real-time satellite data and remote sensor data. The system provides a more sustainable and efficient way to help farmers harvest with better usages of land, water, and fertilizer. According to our analysis results, this combined approach is promising and efficient for smart farming.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"3 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75951723","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/agriculture13091770
Syed Turab Raza, Abid Hameed Khan, Asifa Hameed, Noor Muhammad, Abdul Ghaffar Grewal, Muhammad Tariq Malik, Muhammad Imran, Ghulam Mustafa, Atif Iqbal
The white mango scale (WMS) insect, Aulacaspis tubercularis (Hemiptera: Diaspididae), is a polyphagous, multivoltine pest which is a serious threat to qualitative mango production and export. The WMS insect sucks sap from leaves, branches and fruits. The heavy infestation of this pest may cause the falling of young leaves, drying up of twigs, poor flowering, and, finally, reduce the quality of fruits by producing pink spots on fruits’ surface. This review paper was written to provide comprehensive information about pest biology, ecology and management in different parts of the world. WMS was first reported on the island of Formosa on Mangifera indica in 1929 and later on in the Caribbean Islands, India and Brazil. Now it is found in almost 69 mango-producing countries of the world. The thermal regime may affect the population of pests. In Australia, the life cycle is completed in 35–40 days in summer and 70–85 days in winter. Variety, age of plants, number of trees per acre, canopy size and sunlight penetration affect the density of WMS. Different Coccinellid beetles and parasitoid Encarsia femorosa feed on WMS; however, farmers most commonly use insecticides to get rid of this pest. In Pakistan, WMS is a growing threat to the export of mangoes; hence IPM plan is needed to reduce the pest numbers and enhance qualitative mango production.
{"title":"A Review on White Mango Scale Biology, Ecology, Distribution and Management","authors":"Syed Turab Raza, Abid Hameed Khan, Asifa Hameed, Noor Muhammad, Abdul Ghaffar Grewal, Muhammad Tariq Malik, Muhammad Imran, Ghulam Mustafa, Atif Iqbal","doi":"10.3390/agriculture13091770","DOIUrl":"https://doi.org/10.3390/agriculture13091770","url":null,"abstract":"The white mango scale (WMS) insect, Aulacaspis tubercularis (Hemiptera: Diaspididae), is a polyphagous, multivoltine pest which is a serious threat to qualitative mango production and export. The WMS insect sucks sap from leaves, branches and fruits. The heavy infestation of this pest may cause the falling of young leaves, drying up of twigs, poor flowering, and, finally, reduce the quality of fruits by producing pink spots on fruits’ surface. This review paper was written to provide comprehensive information about pest biology, ecology and management in different parts of the world. WMS was first reported on the island of Formosa on Mangifera indica in 1929 and later on in the Caribbean Islands, India and Brazil. Now it is found in almost 69 mango-producing countries of the world. The thermal regime may affect the population of pests. In Australia, the life cycle is completed in 35–40 days in summer and 70–85 days in winter. Variety, age of plants, number of trees per acre, canopy size and sunlight penetration affect the density of WMS. Different Coccinellid beetles and parasitoid Encarsia femorosa feed on WMS; however, farmers most commonly use insecticides to get rid of this pest. In Pakistan, WMS is a growing threat to the export of mangoes; hence IPM plan is needed to reduce the pest numbers and enhance qualitative mango production.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"12 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80092147","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/agriculture13091778
N. Jurkėnaitė
The EU’s ambition to establish economy-wide climate neutrality by 2050 requires challenging transformations in many economic activities. This paper aims to investigate the nexus of structural changes and greenhouse gas emissions (GHGEs) in an important sector of the livestock system, namely pig farming, during the period of 2010–2020 and to discuss the main directions of GHGE reduction. The academic novelty of this contribution is characterised by a combination of the shift-share and cluster analysis that allows for the investigation of the evolution phenomenon, applying the sustainability prism in order to understand the nexus between pig farming and the livestock system, as well as combining the national and EU levels. Results suggest that the steep decline in the number of holdings and a moderate reduction in livestock units (LSUs) on farms do not bring tangible GHGE reduction results. The cluster analysis confirms that pig farming systems in pre-2004 member states, except for Finland and Greece, demonstrated positive developments or a lower decline in holdings with pigs and live swine LSUs compared to other countries, while in the dominant share of post-2003 member states, the GHGE reduction rate was higher. This research identifies a reduction in the pig population, improvement in feed production and the development of related supply chains, and changes in manure management and utilisation as the main directions of GHGE reduction; however, the identified clusters are related with different potentials of GHGE reduction when applying the aforementioned measures. Recommendations include the development and support of actions that focus on GHGE reduction from swine manure and contribute to the establishment of a circular economy in the EU.
{"title":"Analysis of the Nexus between Structural and Climate Changes in EU Pig Farming","authors":"N. Jurkėnaitė","doi":"10.3390/agriculture13091778","DOIUrl":"https://doi.org/10.3390/agriculture13091778","url":null,"abstract":"The EU’s ambition to establish economy-wide climate neutrality by 2050 requires challenging transformations in many economic activities. This paper aims to investigate the nexus of structural changes and greenhouse gas emissions (GHGEs) in an important sector of the livestock system, namely pig farming, during the period of 2010–2020 and to discuss the main directions of GHGE reduction. The academic novelty of this contribution is characterised by a combination of the shift-share and cluster analysis that allows for the investigation of the evolution phenomenon, applying the sustainability prism in order to understand the nexus between pig farming and the livestock system, as well as combining the national and EU levels. Results suggest that the steep decline in the number of holdings and a moderate reduction in livestock units (LSUs) on farms do not bring tangible GHGE reduction results. The cluster analysis confirms that pig farming systems in pre-2004 member states, except for Finland and Greece, demonstrated positive developments or a lower decline in holdings with pigs and live swine LSUs compared to other countries, while in the dominant share of post-2003 member states, the GHGE reduction rate was higher. This research identifies a reduction in the pig population, improvement in feed production and the development of related supply chains, and changes in manure management and utilisation as the main directions of GHGE reduction; however, the identified clusters are related with different potentials of GHGE reduction when applying the aforementioned measures. Recommendations include the development and support of actions that focus on GHGE reduction from swine manure and contribute to the establishment of a circular economy in the EU.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"110 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":"84365558","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}
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/agriculture13091776
Nguyen T. P. Thao, Nguyen T. Thuy
Typhlodromus ndibu Pritchard and Baker (Acari: Phytoseiidae), collected from citrus orchards in the southern region of Vietnam, has been identified as a natural enemy of the citrus red mite Panonychus citri (McGregor) (Acari: Tetranychidae). It holds potential as a laboratory-reared predator for biological control purposes. However, the research on T. ndibu remains limited. This study focuses on investigating the effects of fenpyroximate, alpha-cypermethrin, pymetrozin, buprofezin, matrine, and azadirachtin on this predatory mite in laboratory conditions. Fenpyroximate was the most toxic substance against T. ndibu, affecting its fertility, egg-hatching rate, and population establishment ability. The mortality rate among adult female T. ndibu is (73.97 ± 2.43%), and (89.09 ± 0.00%) in the immature stages after 72 h of exposure to fenpyroximate. Matrine and azadirachtin—active ingredients of plant origin—were classified as slightly harmful to T. ndibu with mortality rates among adult females and the immature stages being less than 50%. The implications of the obtained results regarding the integration of biological and chemical control methods may facilitate the more effective development of integrated pest management (IPM) programs.
采自越南南部柑橘果园的ndibu Pritchard and Baker恙螨(蜱螨目:植物绥螨科)被鉴定为柑橘红螨(蜱螨目:叶螨科)的天敌。它有潜力作为实验室饲养的捕食者用于生物控制目的。然而，对T. ndibu的研究仍然有限。本研究主要研究了在实验室条件下，苯吡肟酯、高效氯氰菊酯、吡虫嗪、丁丙嗪、苦参碱和印楝素对该捕食性螨的影响。芬吡肟对褐僵菌的毒性最大，影响褐僵菌的繁殖能力、孵化率和种群建立能力。暴露于芬吡肟72 h后，成年雌性尼布氏滴虫死亡率为(73.97±2.43%)，未成熟期死亡率为(89.09±0.00%)。植物源活性成分苦参碱和印楝素对白僵菌有轻微危害，成虫和未成熟虫的死亡率均小于50%。所获得的关于生物和化学防治方法的综合结果的意义可能有助于更有效地制定害虫综合管理(IPM)计划。
{"title":"Effects of Certain Pesticides on the Predatory Mite Typhlodromus ndibu Pritchard and Baker (Acari: Phytoseiidae)","authors":"Nguyen T. P. Thao, Nguyen T. Thuy","doi":"10.3390/agriculture13091776","DOIUrl":"https://doi.org/10.3390/agriculture13091776","url":null,"abstract":"Typhlodromus ndibu Pritchard and Baker (Acari: Phytoseiidae), collected from citrus orchards in the southern region of Vietnam, has been identified as a natural enemy of the citrus red mite Panonychus citri (McGregor) (Acari: Tetranychidae). It holds potential as a laboratory-reared predator for biological control purposes. However, the research on T. ndibu remains limited. This study focuses on investigating the effects of fenpyroximate, alpha-cypermethrin, pymetrozin, buprofezin, matrine, and azadirachtin on this predatory mite in laboratory conditions. Fenpyroximate was the most toxic substance against T. ndibu, affecting its fertility, egg-hatching rate, and population establishment ability. The mortality rate among adult female T. ndibu is (73.97 ± 2.43%), and (89.09 ± 0.00%) in the immature stages after 72 h of exposure to fenpyroximate. Matrine and azadirachtin—active ingredients of plant origin—were classified as slightly harmful to T. ndibu with mortality rates among adult females and the immature stages being less than 50%. The implications of the obtained results regarding the integration of biological and chemical control methods may facilitate the more effective development of integrated pest management (IPM) programs.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"2014 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86605934","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}
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