MULTIVARIATE NUTRIENT DIAGNOSIS OF THE CARROT CROP

Compositional nutrient diagnosis (CND) provides undistorted (linearize d) variates amenable to principal component analysis (PCA) using a row -centered logratio transformation of foliar nutrient data. Our objecti ves were to carry PCA on raw or transformed nutrient data for carrot ( Daucus carota L.) crops and to compare the critical value approach (CV A), diagnosis and recommendation integrated system (DRIS), and CND dia gnoses using independent data. PCA conducted on percentage or log-tran sformed data produced similar multivariate structures difficult to int erpret. PCA conducted on DRIS indexes and on row-centered logratios pr oduced PCs (K-Ca+), (N+K-Ca-Mg+), and (P-Mg+) and PCs (K-Mg+), (N-Ca+) , and (P-), respectively. Nutrient contrasts were easiest to interpret with CND and reflected either K-Mg antagonism or N dilution and Ca ac cumulation over time. CVA diagnosis of independent samples was general ly not in line with DRIS or CND. DRIS and CND diagnostic indexes were highly correlated (r = 0.98 to 0.99). By summing bivariate DRIS functi ons, the DRIS index calculation procedure effectively row-centered the nutrient values for carrots. DRIS and CND index diagnosis indicated t reatment-dependent Ca shortage. In contrast, CND PC diagnosis indicate d overall stationary values for PC (N-Ca+) whatever treatment was appl ied. CND PC diagnosis is a multivariate (PCA) approach providing simpl ified computational effort and a theoretical basis for further improve ments in foliar diagnosis.