Determination of Soil and Landscape Requirements of Pistachio for Use in Land Suitability Evaluation

Document Type : Original Article


1 Soil and Water Research Institute, Agricultural Research Education and Extension Organization (AREEO),

2 Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.

3 تحقیقات آموزش و ترویج کشاورزی اصفهان، سازمان تحقیقات، آموزش و ترویج کشاورزی

4 استادیار پژوهش، پژوهشکده پسته، مؤسسه تحقیقات علوم باغبانی، سازمان تحقیقات، آموزش و ترویج کشاورزی، رفسنجان، ایران

5 East Azarbaijan Agricultural and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization

6 Khorasan Razavi Agricultural and Natural Resources, Research and Education Center, Agricultural Research Education and Extension Organization (AREEO


Pistachio is one of the most important and valuable orchard products in Iran, and its compatibility with unfavorable growth conditions, especially drought and salinity, causes its high production in the country. The study aim was to investigate the effect of soil characteristics on pistachio yield and their rating for applying in land suitability assessment studies. So, 124 pistachio orchards were selected in Kerman, Fars, Khorasan-Razavi, Isfahan and East-Azarbaijan provinces. In each orchard, a soil profile was studied and a land use questionnaire completed. After the necessary physical and chemical analyzes, multivariate regression was performed by the stepwise method between yield (dependent variable) and different soil characteristics (independent variables). By creating simple regression relations between effective soil characteristics on yield, the characteristics rating was determined for different land suitability classes. The results showed available potassium, salinity, ESP, sand and CaCO3 had the highest variation, and pH, organic carbon and available phosphorus had the lowest one. The results of stepwise regression showed the input of salinity, ESP, gypsum, CaCO3, gravel, available phosphorus and potassium to the equation were significant (p < 0.01). The variables entered into the regression model with NRMSE=0.280 determined 75% of the variance related to the dependent variable (yield). In simple regression relations, salinity, ESP, gypsum, CaCO3 and gravel had negative influence and organic carbon, available phosphorus and potassium had positive influence on yield. The validation of soil variables ratings with R2=0.82 and NRMSE=0.224 distinguished acceptable accuracy of the proposed table which can be confidently applied for use in land suitability assessment.


Volume 5, Issue 9
September 2020
Pages 70-88
  • Receive Date: 12 May 2020
  • Revise Date: 29 July 2020
  • Accept Date: 29 July 2020
  • First Publish Date: 22 August 2020