This study proposes a statistical model to estimate the productivity (kg/ha) of castor beans in the state of Ceará, as a function of rainfall throughout their vegetative and reproductive cycle. Seven municipalities located in the region known as “Sertão Central” were selected; this choice is justified by the fact that this is the most traditional region for castor bean cultivation in the state of Ceará. Correlation coefficients were calculated between productivity and various parameters related to precipitation (total rainfall, rainfall at the beginning and end of the castor bean cycle, duration of the rainy season, etc.). To minimize the effect of local factors, such as management and soil type, the precipitation and productivity variables were normalized. Next, to eliminate the redundancy in the original variables, principal component analysis (PCA) was used, which reduced the number of independent variables from six to two. By performing a multiple regression of productivity with these two new variables, a model was obtained that allowed the estimation of the harvest for the region studied.
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Paperback. Etat : new. Paperback. This study proposes a statistical model to estimate the productivity (kg/ha) of castor beans in the state of Ceara, as a function of rainfall throughout their vegetative and reproductive cycle. Seven municipalities located in the region known as "Sertao Central" were selected; this choice is justified by the fact that this is the most traditional region for castor bean cultivation in the state of Ceara. Correlation coefficients were calculated between productivity and various parameters related to precipitation (total rainfall, rainfall at the beginning and end of the castor bean cycle, duration of the rainy season, etc.). To minimize the effect of local factors, such as management and soil type, the precipitation and productivity variables were normalized. Next, to eliminate the redundancy in the original variables, principal component analysis (PCA) was used, which reduced the number of independent variables from six to two. By performing a multiple regression of productivity with these two new variables, a model was obtained that allowed the estimation of the harvest for the region studied. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9786209449574
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This study proposes a statistical model to estimate the productivity (kg/ha) of castor beans in the state of Ceará, as a function of rainfall throughout their vegetative and reproductive cycle. Seven municipalities located in the region known as 'Sertão Central' were selected; this choice is justified by the fact that this is the most traditional region for castor bean cultivation in the state of Ceará. Correlation coefficients were calculated between productivity and various parameters related to precipitation (total rainfall, rainfall at the beginning and end of the castor bean cycle, duration of the rainy season, etc.). To minimize the effect of local factors, such as management and soil type, the precipitation and productivity variables were normalized. Next, to eliminate the redundancy in the original variables, principal component analysis (PCA) was used, which reduced the number of independent variables from six to two. By performing a multiple regression of productivity with these two new variables, a model was obtained that allowed the estimation of the harvest for the region studied.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch. N° de réf. du vendeur 9786209449574
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