Quadratic Regression of Grain Protein, Oil and Starch Contents and Yields of Different Maize (Zea mays L.) Genotypes on Elevated Plant Density

Abstract

The main objective of the present investigation was to identify the optimum plant density for the best performance of grain protein, oil and starch contents and yields of different maize genotypes via quadratic regression functions. Diallel crosses among diverse maize inbreds were evaluated in the field for grain protein (GPC), oil (GOC) and starch (GSC) contents, grain (GYPH), protein (PYPH), oil (OYPH), and starch (SYPH) yield per hectare under three plant densities, i.e.47,600, 71,400 and 95,200 plants/ha, using a split plot design with 3 replications in two growing seasons. Results combined across seasons revealed that elevated density from 47,600 to 95,200 plants/ha caused a significant reduction in GYPP, GPC and a significant increase in GYPH, PYPH, OYPH, SYPH and GOC. Regression functions revealed that for GYPH, PYPH, OYPH and SYPH, the response of the four groups of genotypes (tolerant and sensitive inbreds and hybrids) to the elevated plant density showed a quadratic response of increase in hybrids and near-linear response of increase in inbreds, but the response of increase was stronger for tolerant than sensitive groups. A quadratic response of increase was observed for GPC of sensitive hybrids, GOC of sensitive and tolerant hybrids and GSC of tolerant inbreds and hybrids. On the contrary, a quadratic response of decrease was observed for GPC of tolerant inbreds and hybrids, GOC of tolerant and sensitive inbreds, GSC of sensitive hybrids and GYPP of the four groups.