Multivariate Diagnosis of Nutrient Imbalances in Apple using Compositional Nutrient Diagnosis and Principal Component Analysis

Author: Rakesh Sharma*

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Abstract

In order to improve yields and quality while maintaining tree sustainability, multivariate nutrient diagnostic norms to be derived for proper nutrient and sustainable soil fertility management in apple orchards. Foliar nutrient content vs. yield performance data bank was established for 280 apple (Starking delicious) orchards from seventy locations in Kinnaur region of Himachal Pradesh to diagnose nutrient imbalances in apple using compositional nutrient diagnosis and principal component analysis for efficient nutrient management in orchards. The mean foliar N, P and K concentrations were 2.27, 0.243 and 1.53% respectively. The mean Ca (1.56%) concentration in leaf was quite higher compared to Mg (0.31%) concentration. The diagnostic norms for major nutrients (N, P, K, Ca and Mg) were developed by using compositional nutrient diagnosis (CND) technique. The CND norms for N (VN), P (VP), K (VK), Ca (VCa), and Mg (VMg) for apple were 0.219, -1.998, -0.198, -0.137 and -1.763 r

Keywords

Apple, compositional nutrient diagnosis (CND), nutrient imbalances, principal component analysis (PCA).

Conclusion

Thus, the results of the present study suggested that multi-nutrient diagnosis developed through CND and nutrient interactions elucidated through PCA identified P, Mg and Ca as the most common yield limiting nutrients and indicate the necessity to regulate content of available N and K in apple orchard soils and, are thus instrumental in evolving nutrient management strategies based on soil and plant analysis.

References

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How to cite this article

Rakesh Sharma (2021). Multivariate Diagnosis of Nutrient Imbalances in Apple using Compositional Nutrient Diagnosis and Principal Component Analysis. Biological Forum – An International Journal, 13(1): 776-781.