Density Dependence Rather Than Maturity Determines Hybrid Selection in Dryland Maize Production

Abstract

For dryland maize (Zea mays L.) production, it is believed that optimal hybrid choice pertains to time required to reach maturity. In our study, the main hypothesis was that density independence (ability of the hybrid to yield highly under both low and high density) is another key factor that deserves special consideration. To address the issue, fi eld experimentation was conducted under rainfed conditions at Martonvásár, Hungary for 11 yr. Treatments consisted of four N fertilizer rates (0, 100, 200, and 300 kg ha -1 ), four plant population densities (3, 5, 7, and 9 plants m -2 ), and four hybrids (Mara, Norma, Gazda, and Maraton). Variation in precipitation contributed to considerable variability in grain yield, which ranged from 1.46 to 7.67 T ha -1 . A positive relationship between optimum density and mean experimental yield indicated suitability of low and high plant populations for unfavorable and favorable seasons, respectively. Among hybrids, the mid-season Norma and full-season Maraton and Gazda hybrids were superior over the short-season Mara. However, Maraton hybrid exhibited a wide range of optimum densities, and performed as a density-independent hybrid. Th is characteristic enables hybrid planting at low density to meet requirements of the dry season and good utilization of occasional high rainfalls with less yield potential loss. Th is research indicated that breeding density-independent hybrids help in maize production under dryland conditions.

Adapting maize crop to climate change

“…Across 11 consecutive growing seasons (from 1989 through 1999) at the same location (Martonvásár, Hungary), total precipitation ranged between 68 % above and 55 % below the 30-year average (Berzsenyi and Tokatlidis 2012). Over four N-fertilizer treatments at 3, 5, 7, and 9 plants/m 2 , rain-fed maize crop averaged a grain yield from 1,460 to 7,670 kg/ha, showing an EYI gap of up to 425 % across seasons (Fig.…”

“…4 The degree of variability in environmental yield index, (EYI) and crop yield potential (CYP), are indicative of the across-season at a single-location environmental diversity in dryland maize production. Data over four hybrids and four N-fertilizer treatments at four densities from Berzsenyi and Tokatlidis (2012) treatment of 0 Nkg/ha. For the similarly yielding treatments of 165 and 330 Nkg/ha, OP(D) values were 7.4 and 7.9 plants/m 2 , respectively.…”

“…Numerous studies demonstrated the use of the quadratic model (y0a+bx−cx 2 ) to best describe the grain yield response to population changes (Echarte et al 2000;Sangoi et al 2002;Blumenthal et al 2003;Shanahan et al 2004;Hashemi et al 2005;Stanger and Lauer 2006;Sarlangue et al 2007;Berzsenyi and Tokatlidis 2012). Consequently, the per unit ground area maximum yield and the required number of plants were computed from the quadratic equation, corresponding to the CYP and optimum population (OP(q)), respectively.…”

“…Duncan's (1958) method was used to calculate optimum population (OP(D)) when the quadratic model did not fit or the range of plant densities included fewer than four treatments. According to this method, optimum density equals 1/b, where b is the slope of the linear regression of natural logarithm of yield per plant over density (Tollenaar 1992;Tokatlidis 2001;Tokatlidis et al 2011;Berzsenyi and Tokatlidis 2012). Although Duncan's (1958) method is, in part, an artifact of the estimation of OP, it approaches the differences among estimated values fiducially (Tollenaar 1992;Tokatlidis and Tsialtas 2008;Berzsenyi and Tokatlidis 2012).…”

“…According to this method, optimum density equals 1/b, where b is the slope of the linear regression of natural logarithm of yield per plant over density (Tollenaar 1992;Tokatlidis 2001;Tokatlidis et al 2011;Berzsenyi and Tokatlidis 2012). Although Duncan's (1958) method is, in part, an artifact of the estimation of OP, it approaches the differences among estimated values fiducially (Tollenaar 1992;Tokatlidis and Tsialtas 2008;Berzsenyi and Tokatlidis 2012). Indeed, strong positive correlation (P<0.001) between OP(q) and OP(D) values is drawn from the data of Berzsenyi and Lap (2005) and Luque et al (2006), as shown in Fig.…”