DRIS formulas and PCA approach for evaluation of the nutritional status of walnut trees in the Hawraman area

It is essential to understand the proper nutrient levels for obtaining the highest yield when analyzing the foliar composition of walnut leaves using DRIS techniques that take into account the interaction between nutrients. The study's objective is to identify the nutritional deficiency in walnut orchards that is responsible for low production by analyzing the data using DRIS and PCA methods. Nine elements were measured in leaf parts of the walnut tree including N, P, K, Ca, Mg, and microelements Fe, Zn, Cu, and Mn. The Diagnosis and Recommendation Integrated System (DRIS) was used in order to assess nutrient status in the leaf, detecting deficits or imbalances and making specific recommendations for optimal growth. Along with Principal component analysis diagnose deficient nutrients and deal with problems. In the present work, 42 samples of walnut leaves from the Hawraman walnut orchard were analyzed. A high-yielding population of walnut trees forms up 71.4% of the total, while a low-yielding population makes up the remaining 28.6%. Results showed that the most deficient nutrients ascendingly were: Fe>Cu> Zn>Mn>N=Ca>K>P>Mg. The PCA results show that 78.8%, 87.2%, and 93.5% respectively, of the DRIS index and the low- and high-yield subgroups' nutrient concentrations were explained. From previous results and field observation, the walnut orchards need more attention and studies in other aspects to fulfill knowledge about soil quality index, climatic changes, and diseases related to these precious trees in order to make decisions for best monitoring and management.