Journal of Horticultural Sciences

K. Anjaneyulu ¹, H. B. Raghupathi ¹, M. K. Chandraprakash ¹

Affiliations
1 Division of Soil Science and Agricultural Chemistry, Indian Institute of Horticultural Research, Bangalore-560 089, IN

Abstract

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 (V_N), P (V_P) and K (V_K) 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.

Keywords

Nutrients, Diagnosis, Norms, CND, PCA, Guava.

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R. Venugopalan ¹, K. R. M. Swamy ², M. K. Chandraprakash ¹

Affiliations
1 Section of Economics and Statistics, Indian Institute of Horticultural Research, Bangalore-560089, IN
2 Division of Vegetable Crops, Indian Institute of Horticultural Research, Bangalore-560089, IN

Abstract

Randomized Block Design (RBD) is commonly employed to evaluate a set of germplasm accessions (test treatments) along with local checks. In such a trial, if the test treatments under evaluation are more in number and the availability of the seeds is limited, then an alternate experimental design has to be employed. As a remedy, Balanced Incomplete Block Design (BIBD), which estimates treatments contrasts with more precision and the treatments are not repeated in all the blocks, unlike RBD, may be used. Such a constructed layout, not only saves the precious seed material of the test treatments, but also directly reduces the cost of all the related inputs such as labour, water, fertilizers, pesticides etc. Foregoing thoughts were elucidated in the evaluation of 100 accessions of okra along with four check varieties (Arka Anamika, Arka Abhay, Parbhani Kranti and PB-7) evaluated using Augmented BIB Design with six blocks in the Division of Vegetable crops at I.I.H.R., Bangalore during Kharif 2005. Results showed that by adopting BIB experimental design, instead of regular complete block design 60.2% of the land area required for conducting germplasm evaluation in Okra had been reduced.

Keywords

Accessions, Augmented Balanced Incomplete Block Design, Control, Germplasm, Okra, Test Treatments.

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