Document Type : Research Paper
Authors
1
Assistance professor of Soil and Water Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center, AEEO, Iran
2
Assistance professor of Soil and Water Research Institute, AEEO, Iran.
3
Scientific Staff of Soil and Water Research Department, Kermanshah Agricultural and Natural Resources Research and Education Center, AEEO, Iran.
4
MSc of soil pedology, Agricultural Jihad Organization of Kermanshah Province.
10.22092/ijsr.2023.359848.678
Abstract
Tissue analysis is a useful tool for evaluation and optimizing nutrients for sugar beet using Deviation from Optimum Percentage (DOP) and Compositional Nutrient Diagnosis (CND) methods. In order to evaluate the nutritional status of sugar beet farms in Kermanshah Province, this project was conducted in two cropping seasons (2018-21). In each year, 30 different farms with different ranges of soil properties were selected in each region. The project database for the first and second seasons was completed and analyzed and DOP and CND indices were calculated for each nutrient element. Compared with the critical nutrient concentration in Kermanshah Province, the results showed that 85%, 10%, 97.5%, 67%, 93%, 100%, and 5% of farms were deficient in phosphorus, potassium, iron, manganese, zinc, boron and copper, respectively. The average sugar beet yield in this region was about 67.6 t/ha. Selected sugar beet farms were divided into two groups of high and low yields. The results of CND and DOP indices in the Kermanshah province showed that Mg, P, N and K deficiencies were more prevalent among macro-elements and Fe, Mn and Zn deficiencies were observed among micro-elements. However, there was a difference between the two methods in terms of the content of N, Mn, and Fe among the deficient elements. There was a significant correlation (0.48) between nutritional balance index and yield at 1% probability level. The results obtained in this study can be used to increase the yield and improve the quality of sugar beet in each of the regions.
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