In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological d...In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.展开更多
Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakista...Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakistan,and climate change is one of the main factors that impact cotton yield.Due to climate change,it becomes very important to understand the change trend and its impact on cotton yield at the regional level.Here,we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window.The piecewise regression was fitted to obtain the trend-shifting point of climate factors.The results show that precipitation has experienced an overall decreasing trend of–0.64 mm/yr during the study period,with opposing trends of–1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point,respectively.We found that cotton yield variability increased at a rate of 0.17%/yr,and this trend was highly correlated with the variability of climate factors.The multiple regression analysis explains that climate variability is a dominant factor and controlled 81%of the cotton production in the study area from 1990 to 2019,while it controlled 73%of the production from 1990 to 2002 and 84%from 2002 to 2019.These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level.展开更多
The family farm of the Upper Solim?es region has maintained the great genetic variability of the pumpkin (Cucurbita maxima Duchesne) by the in situ conservation of the landraces which are widely used as human food. Th...The family farm of the Upper Solim?es region has maintained the great genetic variability of the pumpkin (Cucurbita maxima Duchesne) by the in situ conservation of the landraces which are widely used as human food. The aim of this study was to estimate the current level of genetic variability of pumpkin landraces by means of estimation techniques of genetic parameters. Landraces areas samples were the family farming production units located in floodplains ecosystems of Benjamin Constant (Upper Solim?es River) and Iranduba (Lower Solim?es River), Amazonas. The split-plot designs were adopted at the treatments where the main plots were the five pumpkin landraces and one commercial cultivar. Each landrace was obtained six half sib families distributed in the sub-plots. Among the results of this study, it can be concluded that the genetic variation within the each landrace is greater than the genetic variation among the landraces. The qualitative morphological characteristics bring together half-sib families collected in geographically distant locations. It can be concluded that, through the estimation of genetic parameters, there is genetic variability among local cultivars collected in family farming of Benjamin Constant and Iranduba, Amazonas.展开更多
The Cucurbita maxima Duchesne is a vegetable crop plant cultivated and maintained by traditional Amazon communities, Brazil. The situation is worsened by the possibility of disappearance of local populations and genet...The Cucurbita maxima Duchesne is a vegetable crop plant cultivated and maintained by traditional Amazon communities, Brazil. The situation is worsened by the possibility of disappearance of local populations and genetic variability of this specie, taking into account the today changes promoted in family farming. The aim of this study was to estimate the current levels of genetic variability of local cultivars through the use of molecular markers (Amplified Fragment Length Polymorphism—AFLP). We chose to collect in two distinct micro regions in order to identify possible influences of geographic isolation and different levels of market requirements in the conservation of the genetic variability of the C. maxima. For the molecular analysis, bulk samples of fresh leaves of 15 plants/half-sibling family were collected in paper bags. There were 34 samples from the half-sib families. The analysis of the results half-sib obtained by methods of estimation of genetic variation by molecular markers shows that the forms of cultivation and management adopted by family farmers maintain the identities of the local/landraces (native cultivars) and, at the same time, the levels of diversity for the assurance of adaptability macro-environmental.展开更多
文摘In the past few decades,meteorological datasets from remote sensing techniques in agricultural and water resources management have been used by various researchers and managers.Based on the literature,meteorological datasets are not more accurate than synoptic stations,but their various advantages,such as spatial coverage,time coverage,accessibility,and free use,have made these techniques superior,and sometimes we can use them instead of synoptic stations.In this study,we used four meteorological datasets,including Climatic Research Unit gridded Time Series(CRU TS),Global Precipitation Climatology Centre(GPCC),Agricultural National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications(AgMERRA),Agricultural Climate Forecast System Reanalysis(AgCFSR),to estimate climate variables,i.e.,precipitation,maximum temperature,and minimum temperature,and crop variables,i.e.,reference evapotranspiration,irrigation requirement,biomass,and yield of maize,in Qazvin Province of Iran during 1980-2009.At first,data were gathered from the four meteorological datasets and synoptic station in this province,and climate variables were calculated.Then,after using the AquaCrop model to calculate the crop variables,we compared the results of the synoptic station and meteorological datasets.All the four meteorological datasets showed strong performance for estimating climate variables.AgMERRA and AgCFSR had more accurate estimations for precipitation and maximum temperature.However,their normalized root mean square error was inferior to CRU for minimum temperature.Furthermore,they were all very efficient for estimating the biomass and yield of maize in this province.For reference evapotranspiration and irrigation requirement CRU TS and GPCC were the most efficient rather than AgMERRA and AgCFSR.But for the estimation of biomass and yield,all the four meteorological datasets were reliable.To sum up,GPCC and AgCFSR were the two best datasets in this study.This study suggests the use of meteorological datasets in water resource management and agricultural management to monitor past changes and estimate recent trends.
基金Under the auspices of National Key Research and Development Program of China (No.2017YFA0604403-3,2016YFA0602301)the Joint Fund of National Natural Science Foundation of China (No.U19A2023)。
文摘Cotton is a revenue source for cotton-producing countries;as the second-largest crop in Pakistan,it significantly contributes to its economy.Over the past few decades,cotton productivity has become unstable in Pakistan,and climate change is one of the main factors that impact cotton yield.Due to climate change,it becomes very important to understand the change trend and its impact on cotton yield at the regional level.Here,we investigate the relationship of standardized cotton yield variability with the variability of climate factors using a 15-yr moving window.The piecewise regression was fitted to obtain the trend-shifting point of climate factors.The results show that precipitation has experienced an overall decreasing trend of–0.64 mm/yr during the study period,with opposing trends of–1.39 mm/yr and 1.52 mm/yr before and after the trend-shifting point,respectively.We found that cotton yield variability increased at a rate of 0.17%/yr,and this trend was highly correlated with the variability of climate factors.The multiple regression analysis explains that climate variability is a dominant factor and controlled 81%of the cotton production in the study area from 1990 to 2019,while it controlled 73%of the production from 1990 to 2002 and 84%from 2002 to 2019.These findings reveal that climate factors affact the distinct spatial pattern of changes in cotton yield variability at the tehsil level.
文摘The family farm of the Upper Solim?es region has maintained the great genetic variability of the pumpkin (Cucurbita maxima Duchesne) by the in situ conservation of the landraces which are widely used as human food. The aim of this study was to estimate the current level of genetic variability of pumpkin landraces by means of estimation techniques of genetic parameters. Landraces areas samples were the family farming production units located in floodplains ecosystems of Benjamin Constant (Upper Solim?es River) and Iranduba (Lower Solim?es River), Amazonas. The split-plot designs were adopted at the treatments where the main plots were the five pumpkin landraces and one commercial cultivar. Each landrace was obtained six half sib families distributed in the sub-plots. Among the results of this study, it can be concluded that the genetic variation within the each landrace is greater than the genetic variation among the landraces. The qualitative morphological characteristics bring together half-sib families collected in geographically distant locations. It can be concluded that, through the estimation of genetic parameters, there is genetic variability among local cultivars collected in family farming of Benjamin Constant and Iranduba, Amazonas.
文摘The Cucurbita maxima Duchesne is a vegetable crop plant cultivated and maintained by traditional Amazon communities, Brazil. The situation is worsened by the possibility of disappearance of local populations and genetic variability of this specie, taking into account the today changes promoted in family farming. The aim of this study was to estimate the current levels of genetic variability of local cultivars through the use of molecular markers (Amplified Fragment Length Polymorphism—AFLP). We chose to collect in two distinct micro regions in order to identify possible influences of geographic isolation and different levels of market requirements in the conservation of the genetic variability of the C. maxima. For the molecular analysis, bulk samples of fresh leaves of 15 plants/half-sibling family were collected in paper bags. There were 34 samples from the half-sib families. The analysis of the results half-sib obtained by methods of estimation of genetic variation by molecular markers shows that the forms of cultivation and management adopted by family farmers maintain the identities of the local/landraces (native cultivars) and, at the same time, the levels of diversity for the assurance of adaptability macro-environmental.
