Modeling and Optimization of Maize Yield and Water Use Efficiency under Biochar, Inorganic Fertilizer and Irrigation Using Principal Component Analysis

Abstract

This study was conducted to predict the grain yield of a maize crop from easy-to-measure growth parameters and select the best treatment combinations of biochar, inorganic fertilizer, and irrigation for the maize grain yield and water use efficiency (WUE) using the Principal Component Analysis (PCA) technique. Two rates of biochar (0 and 20 t ha−1) and fertilizer (0 and 300 kg ha−1) were applied to the soil, with maize crop planted, and subjected to deficit irrigation at 60, 80, and 100% of full irrigation amounts (FIA). Maize growth parameters (number of leaves—NL, leaf area—LA, leaf area index—LAI, and plant height—PH) were measured weekly. The results showed that the developed principal component regression (PCR) from the easy-to-measure growth parameters were strong and moderate in predicting the maize yield and WUE, with coefficient of determination; r2 values of 0.92 and 0.56, respectively. Using the PCA technique, the integration of irrigation with the least amount of water (60% FAI) with biochar (20 t ha−1) and fertilizer (300 kg ha−1) produced the highest ranking on grain yield and water use efficiency. This optimization technique showed that with the adoption of the integrative approach, 40% of irrigation water could be saved for other agricultural purposes

Keywords

• soil amendments
• irrigation
• maize
• leaf area index
• principal component analysis