Pub Date : 2023-08-29DOI: 10.3390/agriculture13091702
Yanling Gong, Yingliang Zhang, Yu Chen
The shift from increasing grain production to improving grain quality is a key measure to adapt to the changing structure of residents’ food consumption demand. High-standard farmland construction is an important means to achieve high grain production and excellent quality. To estimate the intervention effect of high-standard farmland construction policy, this paper analyzes it from the perspective of policy evaluation. The continuous DID model, moderating effect model, and the mediating effect model are used to systematically analyze the mechanism of high-standard farmland construction policy and its influence on grain quality. The findings are as follows: (1) The high-standard farmland construction policy has a significant promoting effect on grain quality, and the interaction coefficient of policy implementation is 0.074. is the results are still significant under the robustness test of lagging the explanatory variable by one period, replacing the core explanatory variable, changing the timing of policy implementation, and eliminating the interference of other relevant policies. (2) The adoption of environmentally friendly technology has played a positive moderating role in the process by which high-standard farmland construction policy promotes grain quality, with a moderating effect of 0.044. (3) The high-standard farmland construction policy can improve grain quality by improving cultivated land quality and adoption level of agricultural mechanization. (4) Heterogeneity analysis shows that high-standard farmland construction policy in major grain-producing areas and also non-major grain-producing areas can increase grain quality; the implementation of the policy has a more obvious effect on improving grain quality in areas with low distribution of grain quality. Accordingly, it is suggested to continue to promote high-standard farmland construction and implement special actions for farmland protection, focus on key technologies, encourage farmers to adopt environment-friendly technologies, accelerate the cultivation of diversified agricultural machinery service entities, and enhance the abilities of agricultural mechanization operations. This study provides a new perspective for improving grain quality and proves that a high-standard farmland construction policy is an important strategy for increasing grain quality.
{"title":"The Impact of High-Standard Farmland Construction Policy on Grain Quality from the Perspectives of Technology Adoption and Cultivated Land Quality","authors":"Yanling Gong, Yingliang Zhang, Yu Chen","doi":"10.3390/agriculture13091702","DOIUrl":"https://doi.org/10.3390/agriculture13091702","url":null,"abstract":"The shift from increasing grain production to improving grain quality is a key measure to adapt to the changing structure of residents’ food consumption demand. High-standard farmland construction is an important means to achieve high grain production and excellent quality. To estimate the intervention effect of high-standard farmland construction policy, this paper analyzes it from the perspective of policy evaluation. The continuous DID model, moderating effect model, and the mediating effect model are used to systematically analyze the mechanism of high-standard farmland construction policy and its influence on grain quality. The findings are as follows: (1) The high-standard farmland construction policy has a significant promoting effect on grain quality, and the interaction coefficient of policy implementation is 0.074. is the results are still significant under the robustness test of lagging the explanatory variable by one period, replacing the core explanatory variable, changing the timing of policy implementation, and eliminating the interference of other relevant policies. (2) The adoption of environmentally friendly technology has played a positive moderating role in the process by which high-standard farmland construction policy promotes grain quality, with a moderating effect of 0.044. (3) The high-standard farmland construction policy can improve grain quality by improving cultivated land quality and adoption level of agricultural mechanization. (4) Heterogeneity analysis shows that high-standard farmland construction policy in major grain-producing areas and also non-major grain-producing areas can increase grain quality; the implementation of the policy has a more obvious effect on improving grain quality in areas with low distribution of grain quality. Accordingly, it is suggested to continue to promote high-standard farmland construction and implement special actions for farmland protection, focus on key technologies, encourage farmers to adopt environment-friendly technologies, accelerate the cultivation of diversified agricultural machinery service entities, and enhance the abilities of agricultural mechanization operations. This study provides a new perspective for improving grain quality and proves that a high-standard farmland construction policy is an important strategy for increasing grain quality.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"22 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78779030","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 : 2023-08-29DOI: 10.3390/agriculture13091707
Jiyoung Ha, Seunghyun Lee, Sangtae Kim
This study aimed to verify the influence relationship between the news articles on onions produced in Korea and the consumer selling price of onions. The analysis methods were the LDA topic modeling technique and the multiple regression analysis. As a result of the analysis, a total of eight topics were found in onion-related news articles. This study analyzed which articles out of the eight topics affected the consumer selling price of onions. As a result, Topic 1 (hypermarket onion sales-related articles), Topic 5 (onion supply and demand stabilization measures), and Topic 6 (inflation) had a statistically significant influence relationship. These results meant that as the number of hypermarket-related articles increased, the consumer selling price increased, and as the macroeconomic articles such as supply and demand stabilization measures and inflation increased, the selling price decreased. The significance of this study was that it revealed that news articles related to onions did not affect the selling price in the consumer market as a whole, and that only the articles directly related to the consumption market (distributors, macroeconomic indicators, etc.) had an effect.
{"title":"Influence Relationship between Online News Articles and the Consumer Selling Price of Agricultural Products—Focusing on Onions","authors":"Jiyoung Ha, Seunghyun Lee, Sangtae Kim","doi":"10.3390/agriculture13091707","DOIUrl":"https://doi.org/10.3390/agriculture13091707","url":null,"abstract":"This study aimed to verify the influence relationship between the news articles on onions produced in Korea and the consumer selling price of onions. The analysis methods were the LDA topic modeling technique and the multiple regression analysis. As a result of the analysis, a total of eight topics were found in onion-related news articles. This study analyzed which articles out of the eight topics affected the consumer selling price of onions. As a result, Topic 1 (hypermarket onion sales-related articles), Topic 5 (onion supply and demand stabilization measures), and Topic 6 (inflation) had a statistically significant influence relationship. These results meant that as the number of hypermarket-related articles increased, the consumer selling price increased, and as the macroeconomic articles such as supply and demand stabilization measures and inflation increased, the selling price decreased. The significance of this study was that it revealed that news articles related to onions did not affect the selling price in the consumer market as a whole, and that only the articles directly related to the consumption market (distributors, macroeconomic indicators, etc.) had an effect.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"63 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83998021","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 : 2023-08-29DOI: 10.3390/agriculture13091704
X. Lei, Wencheng Wu, X. Deng, Tao Li, Hongnan Liu, Jinyue Guo, Ju Li, Peixu Zhu, Ke Yang
The discrete element method (DEM) is an effective tool for obtaining qualitative and quantitative information on particle motion, which aids in the design and optimization of agricultural equipment structures. The accuracy of the DEM simulation parameters significantly impacts the simulation results. This study employed a combination of high-speed camera measurement, DEM simulation, and validation tests to determine the material and interaction property parameters for fertilizer particles. The basic parameters (triaxial size, bulk density, density, and coefficient of static friction) and coefficients of restitution between fertilizer and material were measured for three fertilizer varieties. There was a significant difference in the angle of repose between various material plates and fertilizer particles. The calibration values of coefficients of restitution and coefficients of rolling friction between fertilizer particles were optimized using the Box–Behnken method. The angle of repose was significantly affected by the coefficient of static friction and the coefficient of rolling friction between the fertilizer particles. The determined values for the coefficient of restitution, coefficient of static friction, and coefficient of rolling friction between the fertilizer particles were 0.323, 0.381, and 0.173, respectively. The error in the angle of the repose test was less than 3.0%, and the variation coefficient for each row consistency was less than 1.68 percentage points under the optimal simulation parameters. DEM simulations of the angle of repose and each row consistency variation coefficient test using the measured parameters can accurately predict the experimental results. The findings of this paper provide a theoretical basis for the DEM study of fertilizer particles.
{"title":"Determination of Material and Interaction Properties of Granular Fertilizer Particles Using DEM Simulation and Bench Testing","authors":"X. Lei, Wencheng Wu, X. Deng, Tao Li, Hongnan Liu, Jinyue Guo, Ju Li, Peixu Zhu, Ke Yang","doi":"10.3390/agriculture13091704","DOIUrl":"https://doi.org/10.3390/agriculture13091704","url":null,"abstract":"The discrete element method (DEM) is an effective tool for obtaining qualitative and quantitative information on particle motion, which aids in the design and optimization of agricultural equipment structures. The accuracy of the DEM simulation parameters significantly impacts the simulation results. This study employed a combination of high-speed camera measurement, DEM simulation, and validation tests to determine the material and interaction property parameters for fertilizer particles. The basic parameters (triaxial size, bulk density, density, and coefficient of static friction) and coefficients of restitution between fertilizer and material were measured for three fertilizer varieties. There was a significant difference in the angle of repose between various material plates and fertilizer particles. The calibration values of coefficients of restitution and coefficients of rolling friction between fertilizer particles were optimized using the Box–Behnken method. The angle of repose was significantly affected by the coefficient of static friction and the coefficient of rolling friction between the fertilizer particles. The determined values for the coefficient of restitution, coefficient of static friction, and coefficient of rolling friction between the fertilizer particles were 0.323, 0.381, and 0.173, respectively. The error in the angle of the repose test was less than 3.0%, and the variation coefficient for each row consistency was less than 1.68 percentage points under the optimal simulation parameters. DEM simulations of the angle of repose and each row consistency variation coefficient test using the measured parameters can accurately predict the experimental results. The findings of this paper provide a theoretical basis for the DEM study of fertilizer particles.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"24 3 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89563465","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 : 2023-08-29DOI: 10.3390/agriculture13091705
M. Pérgola, A. Maffia, Giuseppe Carlucci, A. Persiani, A. M. Palese, M. Zaccardelli, Gessica Altieri, G. Celano
This paper aims to provide an evaluation of the environmental and economic aspects of strawberry cultivation in the Campania and Basilicata regions of Southern Italy, and to consider the effects on strawberry productivity following compost tea (CT) application. Eight strawberry-growing systems were tested. To this end, compost tea production and characterization were described; a quantitative analysis of the strawberries’ yield was performed, and environmental impact per ha and per kg of strawberries was estimated using the life cycle assessment methodology. To compare the profitability of the systems analyzed, the gross profit of the farmers was calculated, also considering the social cost of pollution. One of the two organic systems analyzed, using solarization for soil disinfestation, biological fight for pest control, and corrugated boxes as packaging recycled at the end-of-life, was the most sustainable system with carbon credits. At the same time, organic crops are not always the most sustainable and profitable systems if significant irrigation and fertigation interventions are carried out, as in another organic system analyzed. Plastic materials and zinc structures were the most impacting items in almost all analyzed systems. The use of a CT with an elevated number of beneficial microorganisms with a high suppressive action allowed to obtain a good increase of the yield, in both systems that used it, and to have a higher gross profit. On the other hand, the validity of this technique was strongly linked to the finding of high-quality green compost.
{"title":"An Environmental and Economic Analysis of Strawberry Production in Southern Italy","authors":"M. Pérgola, A. Maffia, Giuseppe Carlucci, A. Persiani, A. M. Palese, M. Zaccardelli, Gessica Altieri, G. Celano","doi":"10.3390/agriculture13091705","DOIUrl":"https://doi.org/10.3390/agriculture13091705","url":null,"abstract":"This paper aims to provide an evaluation of the environmental and economic aspects of strawberry cultivation in the Campania and Basilicata regions of Southern Italy, and to consider the effects on strawberry productivity following compost tea (CT) application. Eight strawberry-growing systems were tested. To this end, compost tea production and characterization were described; a quantitative analysis of the strawberries’ yield was performed, and environmental impact per ha and per kg of strawberries was estimated using the life cycle assessment methodology. To compare the profitability of the systems analyzed, the gross profit of the farmers was calculated, also considering the social cost of pollution. One of the two organic systems analyzed, using solarization for soil disinfestation, biological fight for pest control, and corrugated boxes as packaging recycled at the end-of-life, was the most sustainable system with carbon credits. At the same time, organic crops are not always the most sustainable and profitable systems if significant irrigation and fertigation interventions are carried out, as in another organic system analyzed. Plastic materials and zinc structures were the most impacting items in almost all analyzed systems. The use of a CT with an elevated number of beneficial microorganisms with a high suppressive action allowed to obtain a good increase of the yield, in both systems that used it, and to have a higher gross profit. On the other hand, the validity of this technique was strongly linked to the finding of high-quality green compost.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"227 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75333672","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 : 2023-08-29DOI: 10.3390/agriculture13091709
Liming Zhu, Huifeng Wu, Min Li, Chaoyin Dou, A. Zhu
Accurate irrigation water-use data are essential to agricultural water resources management and optimal allocation. The obscuration presented by ground cover in farmland and the subjectivity of irrigation-related decision-making processes mean that effectively identifying regional irrigation water use remains a critical problem to be solved. In view of the advantages of satellite microwave remote sensing in monitoring soil moisture, previous studies have proposed a method for estimating irrigation water use using the satellite microwave remote sensing of soil moisture. However, the method is affected by false irrigation signals from soil moisture increases caused by non-irrigation factors, causing irrigation water use to be overestimated. Therefore, the purpose of this study is to improve the estimation of irrigation water use in drylands by using irrigation signals from SMAP soil moisture data. In this paper, the irrigation water use in Henan Province is estimated by using the irrigation signals from SMAP (soil moisture active and passive) soil moisture data. Firstly, a method for recognizing irrigation signals in soil moisture data obtained by microwave satellite remote sensing was used. Then, an estimation model of the amount of irrigation water (SM2Rainfall model) was built on each data pixel of the satellite microwave remote sensing of soil moisture. Finally, the amount of irrigation water utilized in Henan Province was estimated by combining the irrigation signals and irrigation water-use estimation model, and the results were evaluated. According to the findings, this study improved the estimation accuracy of irrigation water use by using the irrigation signals in Henan Province. The result of this study is of great importance to accurately obtain irrigation water use in the region.
准确的灌溉用水数据对农业水资源管理和优化配置至关重要。农田地被覆盖的隐蔽性和灌溉决策过程的主观性意味着有效识别区域灌溉用水仍然是一个亟待解决的关键问题。鉴于卫星微波遥感在土壤水分监测方面的优势，已有研究提出了利用卫星微波遥感土壤水分估算灌溉用水量的方法。然而，该方法受非灌溉因素引起的土壤水分增加所产生的虚假灌溉信号的影响，导致灌溉用水量被高估。因此，本研究的目的是利用SMAP土壤水分数据中的灌溉信号来改进旱地灌溉用水量的估算。本文利用SMAP (soil moisture active and passive soil moisture)土壤水分数据的灌溉信号，估算了河南省灌溉用水量。首先，采用微波卫星遥感土壤水分数据中灌溉信号的识别方法。然后，基于卫星微波遥感土壤湿度的每个数据像元，建立灌溉水量估算模型(SM2Rainfall模型)。最后，结合灌溉信号和灌溉用水量估算模型对河南省灌溉用水量进行估算，并对结果进行评价。根据研究结果，本研究提高了利用河南省灌溉信号估算灌溉用水量的精度。研究结果对准确获取该地区灌溉用水量具有重要意义。
{"title":"Estimation of Irrigation Water Use by Using Irrigation Signals from SMAP Soil Moisture Data","authors":"Liming Zhu, Huifeng Wu, Min Li, Chaoyin Dou, A. Zhu","doi":"10.3390/agriculture13091709","DOIUrl":"https://doi.org/10.3390/agriculture13091709","url":null,"abstract":"Accurate irrigation water-use data are essential to agricultural water resources management and optimal allocation. The obscuration presented by ground cover in farmland and the subjectivity of irrigation-related decision-making processes mean that effectively identifying regional irrigation water use remains a critical problem to be solved. In view of the advantages of satellite microwave remote sensing in monitoring soil moisture, previous studies have proposed a method for estimating irrigation water use using the satellite microwave remote sensing of soil moisture. However, the method is affected by false irrigation signals from soil moisture increases caused by non-irrigation factors, causing irrigation water use to be overestimated. Therefore, the purpose of this study is to improve the estimation of irrigation water use in drylands by using irrigation signals from SMAP soil moisture data. In this paper, the irrigation water use in Henan Province is estimated by using the irrigation signals from SMAP (soil moisture active and passive) soil moisture data. Firstly, a method for recognizing irrigation signals in soil moisture data obtained by microwave satellite remote sensing was used. Then, an estimation model of the amount of irrigation water (SM2Rainfall model) was built on each data pixel of the satellite microwave remote sensing of soil moisture. Finally, the amount of irrigation water utilized in Henan Province was estimated by combining the irrigation signals and irrigation water-use estimation model, and the results were evaluated. According to the findings, this study improved the estimation accuracy of irrigation water use by using the irrigation signals in Henan Province. The result of this study is of great importance to accurately obtain irrigation water use in the region.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"42 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75903315","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 nondestructive prediction of chlorophyll content and response to the growth of various crops using remote sensing technology is a prominent topic in agricultural remote sensing research. Bordeaux mixture has been extensively employed for managing citrus diseases, such as black star and ulcer disease. However, the presence of pesticide residues in Bordeaux mixture can significantly modify the spectral response of the citrus canopy, thereby exerting a substantial influence on the accurate prediction of agronomic indices in fruit trees. In this study, we used unmanned aerial vehicle (UAV) multispectral imaging technology to obtain remote sensing imagery of Bordeaux-covered citrus canopies during the months of July, September, and November. We integrated spectral and texture information to construct a high-dimensional feature dataset and performed data downscaling and feature optimization. Furthermore, we established four machine learning models, namely, partial least squares regression (PLS), ridge regression (RR), ridge, random forest (RF), and support vector regression (SVR). Our objectives were to identify the most effective prediction model for estimating the SPAD (soil plant analysis development) value of Bordeaux-covered citrus canopies, assess the variation in prediction accuracy between fused features and individual features, and investigate the impact of Bordeaux solution on the spectral reflectance of the citrus canopy. The results showed that (1) the impact of Bordeaux mixture on citrus canopy reflectance bands ranked from the highest to the lowest as follows: near-infrared band at 840 nm, red-edge band at 730 nm, blue band at 450 nm, green band at 560 nm, and red band at 650 nm. (2) Fused feature models had better prediction ability than single-feature modeling, with an average R2 value of 0.641 for the four model test sets, improving by 0.117 and 0.039, respectively, compared with single-TF (texture feature) and -VI (vegetation index) modeling, and the test-set root-mean-square error (RMSE) was 2.594 on average, which was 0.533 and 0.264 lower than single-TF and -VI modeling, respectively. (3) Multiperiod data fusion effectively enhanced the correlation between features and SPAD values and consequently improved model prediction accuracy. Compared with accuracy based on individual months, R improved by 0.013 and 0.011, while RMSE decreased by 0.112 and 0.305. (4) The SVR model demonstrated the best performance in predicting citrus canopy SPAD under Bordeaux solution coverage, with R2 values of 0.629 and 0.658, and RMSE values of 2.722 and 2.752 for the training and test sets, respectively.
{"title":"Citrus Canopy SPAD Prediction under Bordeaux Solution Coverage Based on Texture- and Spectral-Information Fusion","authors":"Shunshun Ding, Juanli Jing, Shiqing Dou, Menglin Zhai, Wenjie Zhang","doi":"10.3390/agriculture13091701","DOIUrl":"https://doi.org/10.3390/agriculture13091701","url":null,"abstract":"Rapid and nondestructive prediction of chlorophyll content and response to the growth of various crops using remote sensing technology is a prominent topic in agricultural remote sensing research. Bordeaux mixture has been extensively employed for managing citrus diseases, such as black star and ulcer disease. However, the presence of pesticide residues in Bordeaux mixture can significantly modify the spectral response of the citrus canopy, thereby exerting a substantial influence on the accurate prediction of agronomic indices in fruit trees. In this study, we used unmanned aerial vehicle (UAV) multispectral imaging technology to obtain remote sensing imagery of Bordeaux-covered citrus canopies during the months of July, September, and November. We integrated spectral and texture information to construct a high-dimensional feature dataset and performed data downscaling and feature optimization. Furthermore, we established four machine learning models, namely, partial least squares regression (PLS), ridge regression (RR), ridge, random forest (RF), and support vector regression (SVR). Our objectives were to identify the most effective prediction model for estimating the SPAD (soil plant analysis development) value of Bordeaux-covered citrus canopies, assess the variation in prediction accuracy between fused features and individual features, and investigate the impact of Bordeaux solution on the spectral reflectance of the citrus canopy. The results showed that (1) the impact of Bordeaux mixture on citrus canopy reflectance bands ranked from the highest to the lowest as follows: near-infrared band at 840 nm, red-edge band at 730 nm, blue band at 450 nm, green band at 560 nm, and red band at 650 nm. (2) Fused feature models had better prediction ability than single-feature modeling, with an average R2 value of 0.641 for the four model test sets, improving by 0.117 and 0.039, respectively, compared with single-TF (texture feature) and -VI (vegetation index) modeling, and the test-set root-mean-square error (RMSE) was 2.594 on average, which was 0.533 and 0.264 lower than single-TF and -VI modeling, respectively. (3) Multiperiod data fusion effectively enhanced the correlation between features and SPAD values and consequently improved model prediction accuracy. Compared with accuracy based on individual months, R improved by 0.013 and 0.011, while RMSE decreased by 0.112 and 0.305. (4) The SVR model demonstrated the best performance in predicting citrus canopy SPAD under Bordeaux solution coverage, with R2 values of 0.629 and 0.658, and RMSE values of 2.722 and 2.752 for the training and test sets, respectively.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"12 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88014503","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 : 2023-08-29DOI: 10.3390/agriculture13091703
Yifeng Xie, Haitao Wu, Rui Yao
Based on the annual average climate data and economic and social data from 262 prefecture-level cities in China from 2001 to 2019, this paper explores the impact of climate change on urban–rural income inequality and its mechanisms using fixed-effects (FEs) and mediated-effects (MEs) models. This study finds that (1) climate change has an inverted U-shaped relationship with the urban–rural income disparity; (2) climate change can affect the urban–rural income disparity by influencing urban and rural income levels, the regional degree of urbanization, and the labor force employment structure; (3) the impact of climate change on the urban–rural income gap is heterogeneous in East, Center, and West China; and (4) extreme heat can widen the urban–rural income gap, and extreme drought can narrow the urban–rural income gap. Climate change has a significant impact on the urban–rural income gap, and there is a need to continue to promote urbanization and the optimization of the employment structure of the workforce, reduce the vulnerability of rural residents to climate change, and narrow the urban–rural income gap.
{"title":"The Impact of Climate Change on the Urban–Rural Income Gap in China","authors":"Yifeng Xie, Haitao Wu, Rui Yao","doi":"10.3390/agriculture13091703","DOIUrl":"https://doi.org/10.3390/agriculture13091703","url":null,"abstract":"Based on the annual average climate data and economic and social data from 262 prefecture-level cities in China from 2001 to 2019, this paper explores the impact of climate change on urban–rural income inequality and its mechanisms using fixed-effects (FEs) and mediated-effects (MEs) models. This study finds that (1) climate change has an inverted U-shaped relationship with the urban–rural income disparity; (2) climate change can affect the urban–rural income disparity by influencing urban and rural income levels, the regional degree of urbanization, and the labor force employment structure; (3) the impact of climate change on the urban–rural income gap is heterogeneous in East, Center, and West China; and (4) extreme heat can widen the urban–rural income gap, and extreme drought can narrow the urban–rural income gap. Climate change has a significant impact on the urban–rural income gap, and there is a need to continue to promote urbanization and the optimization of the employment structure of the workforce, reduce the vulnerability of rural residents to climate change, and narrow the urban–rural income gap.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"5 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82293457","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 : 2023-08-28DOI: 10.3390/agriculture13091691
Mohammad Reza Fayezizadeh, N. Ansari, M. M. Sourestani, M. Hasanuzzaman
The appropriate concentration of the nutrient solution (NS) plays an important role in the yield, antioxidant capacity, and biochemical compounds of basil microgreens in the floating system. This study examined the impact of five different concentrations of Hoagland’s NS (25%, 50%, 75%, 100%, and 125%) on the antioxidant capacity, biochemical compounds, and yield of four basil cultivars and genotypes (Persian Ablagh, Violeto, Kapoor and Red Rubin) in a floating system, utilizing a split plots designs. Results revealed that the highest yield was achieved with a 50% NS concentration. The Persian Ablagh genotype, under a 125% NS concentration, exhibited the highest content of carotenoids, flavonoids, phenolic compounds, and antioxidant potential index (APCI). The Violeto cultivar at a 100% NS concentration produced the highest amounts of vitamin C and anthocyanin. The Kapoor cultivar, when grown with a 100% NS concentration, demonstrated the greatest antioxidant capacity. The nutrient solution with 125% concentration compared to 50% concentration reduced the yield by 23.29%. Also, the performance of the Violeto cultivar increased by 36.24% compared to the red variety of Robin. According to the APCI index, the genotype of Iranian Ablaq basil increased by 152.79% in the treatment of nutrient solution with a concentration of 125% compared to 50%. In this study, yield and total chlorophyll showed a significant negative correlation. A significant positive correlation was observed between vitamin C content and flavonoids, anthocyanin, phenolic compounds, and antioxidant capacity. Anthocyanin content exhibited a positive and significant correlation with the APCI. Based on these findings, we recommend a 50% NS concentration of Hoagland’s NS for optimal yield, a 125% NS concentration for the production of secondary metabolites with enhanced antioxidant capacity, and a 100% NS concentration as a balance between antioxidant properties and yield for basil microgreens production in a floating system.
{"title":"Balancing Yield and Antioxidant Capacity in Basil Microgreens: An Exploration of Nutrient Solution Concentrations in a Floating System","authors":"Mohammad Reza Fayezizadeh, N. Ansari, M. M. Sourestani, M. Hasanuzzaman","doi":"10.3390/agriculture13091691","DOIUrl":"https://doi.org/10.3390/agriculture13091691","url":null,"abstract":"The appropriate concentration of the nutrient solution (NS) plays an important role in the yield, antioxidant capacity, and biochemical compounds of basil microgreens in the floating system. This study examined the impact of five different concentrations of Hoagland’s NS (25%, 50%, 75%, 100%, and 125%) on the antioxidant capacity, biochemical compounds, and yield of four basil cultivars and genotypes (Persian Ablagh, Violeto, Kapoor and Red Rubin) in a floating system, utilizing a split plots designs. Results revealed that the highest yield was achieved with a 50% NS concentration. The Persian Ablagh genotype, under a 125% NS concentration, exhibited the highest content of carotenoids, flavonoids, phenolic compounds, and antioxidant potential index (APCI). The Violeto cultivar at a 100% NS concentration produced the highest amounts of vitamin C and anthocyanin. The Kapoor cultivar, when grown with a 100% NS concentration, demonstrated the greatest antioxidant capacity. The nutrient solution with 125% concentration compared to 50% concentration reduced the yield by 23.29%. Also, the performance of the Violeto cultivar increased by 36.24% compared to the red variety of Robin. According to the APCI index, the genotype of Iranian Ablaq basil increased by 152.79% in the treatment of nutrient solution with a concentration of 125% compared to 50%. In this study, yield and total chlorophyll showed a significant negative correlation. A significant positive correlation was observed between vitamin C content and flavonoids, anthocyanin, phenolic compounds, and antioxidant capacity. Anthocyanin content exhibited a positive and significant correlation with the APCI. Based on these findings, we recommend a 50% NS concentration of Hoagland’s NS for optimal yield, a 125% NS concentration for the production of secondary metabolites with enhanced antioxidant capacity, and a 100% NS concentration as a balance between antioxidant properties and yield for basil microgreens production in a floating system.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"104 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76841291","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 : 2023-08-28DOI: 10.3390/agriculture13091695
Wenxin Wang, Yaowen Liang, Zhuo Ru, H. Guo, Bingjie Zhao
Trade market power serves as a significant indicator of pricing power within the trade market. This paper aims to examine the market structure of global forage trade from 1997 to 2020 and assess the market power of forage exporters in major importing countries, namely Japan, China, and South Korea, by utilizing an extended G-K model based on the theory of residual elasticity of demand. The findings of this analysis provide several key insights. Firstly, it is revealed that the United States and Australia hold a monopoly on forage trade, while China has emerged as the most pivotal market for worldwide forage trade. Notably, China’s growing demand for forage imports is profoundly influencing the global forage trade landscape. Secondly, the extent and effectiveness of exporting countries’ market power in forage-importing nations, such as China, varies considerably. Lastly, the market power of forage-exporting countries is determined by various factors, including the demand for forage in importing nations, export monopoly, import structure, demand elasticity, and the level of marketization.
{"title":"World Forage Import Market: Competitive Structure and Market Forces","authors":"Wenxin Wang, Yaowen Liang, Zhuo Ru, H. Guo, Bingjie Zhao","doi":"10.3390/agriculture13091695","DOIUrl":"https://doi.org/10.3390/agriculture13091695","url":null,"abstract":"Trade market power serves as a significant indicator of pricing power within the trade market. This paper aims to examine the market structure of global forage trade from 1997 to 2020 and assess the market power of forage exporters in major importing countries, namely Japan, China, and South Korea, by utilizing an extended G-K model based on the theory of residual elasticity of demand. The findings of this analysis provide several key insights. Firstly, it is revealed that the United States and Australia hold a monopoly on forage trade, while China has emerged as the most pivotal market for worldwide forage trade. Notably, China’s growing demand for forage imports is profoundly influencing the global forage trade landscape. Secondly, the extent and effectiveness of exporting countries’ market power in forage-importing nations, such as China, varies considerably. Lastly, the market power of forage-exporting countries is determined by various factors, including the demand for forage in importing nations, export monopoly, import structure, demand elasticity, and the level of marketization.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"124 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74312549","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 : 2023-08-28DOI: 10.3390/agriculture13091699
M. D. F. Oliveira, Pedro Reis
In the last two decades, Portugal suffered the effects of two global crises, the financial crisis and the COVID-19 pandemic, as well as the Common Agriculture Policy reforms. These crises had a great impact on the Portuguese economy, but it is completely unclear how they affected the dynamics of the Portuguese agrifood sector. This study’s objective is to analyze the resilience of this sector to European and global socks, testing the effects on international trade. Secondary data from the Portuguese Statistics Institute were used for the exports and imports trade series of animal and vegetable products and food industries from 2000 to 2020. The methodology was based on the structural xtbreak model, stability analysis, and tests for structural breaks. Some volatility was observed in the trade series, particularly in imports, without consistency among years, trade sectors, or imports versus exports trade. In the case of exports, one or two structural breaks in the different sectors occurred in different years. The most relevant dynamics occurred after the sovereign debt crisis. It was concluded that CAP reforms and global crises seem to not have caused new relevant dynamics in the Portuguese international agrifood trade. This revealed the resilience of the sector to external shocks.
{"title":"Portuguese Agrifood Sector Resilience: An Analysis Using Structural Breaks Applied to International Trade","authors":"M. D. F. Oliveira, Pedro Reis","doi":"10.3390/agriculture13091699","DOIUrl":"https://doi.org/10.3390/agriculture13091699","url":null,"abstract":"In the last two decades, Portugal suffered the effects of two global crises, the financial crisis and the COVID-19 pandemic, as well as the Common Agriculture Policy reforms. These crises had a great impact on the Portuguese economy, but it is completely unclear how they affected the dynamics of the Portuguese agrifood sector. This study’s objective is to analyze the resilience of this sector to European and global socks, testing the effects on international trade. Secondary data from the Portuguese Statistics Institute were used for the exports and imports trade series of animal and vegetable products and food industries from 2000 to 2020. The methodology was based on the structural xtbreak model, stability analysis, and tests for structural breaks. Some volatility was observed in the trade series, particularly in imports, without consistency among years, trade sectors, or imports versus exports trade. In the case of exports, one or two structural breaks in the different sectors occurred in different years. The most relevant dynamics occurred after the sovereign debt crisis. It was concluded that CAP reforms and global crises seem to not have caused new relevant dynamics in the Portuguese international agrifood trade. This revealed the resilience of the sector to external shocks.","PeriodicalId":48587,"journal":{"name":"Agriculture-Basel","volume":"34 1","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88490560","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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