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

Abstract

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 consider the interaction between nutrients. The study aims to identify the nutritional deficiencies in walnut orchards responsible for low production by analyzing the data using DRIS and PCA methods. Measured nine elements in the walnut tree leaf: N, P, K, Ca, Mg, and microelements Fe, Zn, Cu, and Mn. Used the Diagnosis and Recommendation Integrated System (DRIS) to assess nutrient status in the leaf, detect deficits or imbalances, and make 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 were analyzed and collected from the walnut orchard at the Balkha/Hawraman, located at 35°11'59.0"N 46°08'59.1"E, altitude 695 m.a.s.l. 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 the DRIS index and the low-and high-yield subgroups' nutrient concentrations were represented by 78.8%, 87.2%, and 93.5%, respectively of the total variance. 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 to make decisions for best monitoring and management.