Agriculture
Ali Zeinadini; Mir Naser Navidi; Mahnaz Eskandari; seyed alireza seyedjalali; Javad Seyed Mohammadi; Aboalhasan Moghimi; ءشاشئئشی ganjehie; alireza moghri; mohammadreza pahlavanrad
Abstract
The objective of this study was to investigate the effect of soil and land characteristics on saffron yield, their rating for preparation of a soil requirements table of this plant for land suitability studies by FAO method. First, 124 saffron farms in Khorasan Razavi, South Khorasan, Fars, Golestan, ...
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The objective of this study was to investigate the effect of soil and land characteristics on saffron yield, their rating for preparation of a soil requirements table of this plant for land suitability studies by FAO method. First, 124 saffron farms in Khorasan Razavi, South Khorasan, Fars, Golestan, Markazi and Kerman provinces were selected. In each field, suitable soil samples were taken and a land use questionnaire was completed during three years from 2017 to 2019. Soil samples were tested to determine their physicochemical properties. After preparing the data, they were statistically analyzed. Multivariate regression between yield as a dependent variable and salinity, percentage of exchangeable sodium, soil reaction, gypsum, lime, clay, sand, silt, gravel and available potassium and phosphorus of soil were studied as independent variables by stepwise method. By examining the relationships of simple regression between important and effective land characteristics and yield, land characteristics rating was performed. Then, the saffron soil requirements table prepared. The proposed table was verified with the data of 21 new farms. The results showed that available potassium, sand, soil salinity, percentage of exchangeable sodium and lime had the highest and the reaction of soil and organic carbon had the lowest range of changes. Regression results showed that the independent variables of soil salinity, ESP, lime, gypsum, gravel and available potassium and phosphorus, respectively, affect yield. Coefficient of determination of multivariate regression showed that the variables entered in the model were able to determine 95% of the variance related to the dependent variable. The largest contribution to the reduction of saffron yield is related to soil salinity, gravel, exchangeable sodium percentage and the amount of lime. Validation results showed that the yield correlation coefficient with the soil index of the proposed table for saffron is about 0.92, which indicates the acceptable accuracy of the proposed table.
