Compositional Nutrient Diagnosis Norms (CND) for Guava (Psidium guajava L.)
Multivariate nutrient diagnostic norms were developed for guava using compositional nutrient diagnosis (CND) through leaf nutrient concentration vs. yield data bank. CND norms for N (VN), P (VP) and K (VK) were 2.48, 0.23 and 2.13, respectively. Norms for N and K were much higher compared to P, indi...
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| Autores principales: | , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Society for Promotion of Horticulture - Indian Institute of Horticultural Research
2008
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/00213fde2a954f8187b3373356dfcac6 |
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| Sumario: | Multivariate nutrient diagnostic norms were developed for guava using compositional nutrient diagnosis (CND) through leaf nutrient concentration vs. yield data bank. CND norms for N (VN), P (VP) and K (VK) were 2.48, 0.23 and 2.13, respectively. Norms for N and K were much higher compared to P, indicating higher requirement of these two nutrients. CND norms are multivariate norms that consider all elements, including unmeasured factors and, therefore, has higher diagnostic sensitivity. Among micronutrients, Fe requirement was much higher than all other nutrients. Interaction among different nutrients was explained by principal component analysis conducted on log-transformed data which produced four significant PCs, explaining about 73.66% of the variance. The four Eigen values added up to 8.1 denoting the four significant PCs. The first PC was positively correlated with P, Zn and R (residue, which is a reflection of dry matter accumulation in the plant) and negatively correlated with Ca, Mg, S and Fe, indicating that P and Zn behaved in one direction and the other elements in opposite direction. In the second PC, antagonistic effect of N, Fe with P and Cu was evident. In PC3, P and Mg were negatively correlated with Mn and Cu. In PC4, N and S showed their behaviour in the same direction. Diagnostic norms developed were used for identification of yield-limiting nutrients in low-yielding orchards. Thus, diagnostic norms and nutrient interactions help evolve nutrient management strategies for guava to realize higher yields and better quality. |
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