Genotypic Differences in Current Peanut (Arachis hypogaea L.) Cultivars in Phenology and Stability of These Traits under Different Irrigation Scheduling Methods

Abstract

Understanding differences among peanut (Arachis hypogaea L.) cultivars in growth and phenology and the interactions with environment (G X E interactions) for these traits allows predictions for yield potential or performance in variable environments. Despite the importance of this information, very little quantitative data exists on the differences in aboveground growth, canopy architecture, and reproductive phenology for currently grown peanut cultivars. This study quantified differences in these traits among eight peanut cultivars and explored whether irrigation scheduling method (a factor of environment) affected the development in these traits through the season in 2004 and 2005. As expected, year to year variability in environmental conditions (most likely timing of rainfall events during the growing season) significantly affected growth habit across cultivars. However, the irrigation scheduling method, despite differences in total water applied among methods during the season, had no effect on any of the measured traits. This result is likely due to the fact that all methods were adequately supplying crop water demand. Genetic variability in all of the measured growth and phonological traits was strong despite the expectation that cultivars were genetically similar. Further, the lack of significant interactions between year and cultivar for most of the plant growth and reproductive characteristics also indicated a strong genetic component to these traits. One overall trend noted was that late-maturing cultivars had, on average, higher maximum values of LAI, stem mass, and leaf mass measured in the late growth period. Differences in isotopic composition were also strong among cultivars; the cultivars Georgia-02C and Tifrunner had significantly higher isotopic levels (and thus water-use efficiency) than Georgia-01R, Georgia Green, and AP3 across years. Aside from the obvious relationships between pod number and weight, the strongest predictors of reproductive output were late-season traits including leaf weight and LAI. This study successfully documented variability among peanut cultivars in many important traits linked to overall production.

Crop performance, water use, economics and energy indices in rabi groundnut (Arachis hypogaea L.) under micro irrigation methods

“…3). Previosuly, Rowland et al (2010) also observed linear response of kernel weight with pod yield in regression analysis, however, noticed non-significant effect of irrigation scheduling method on any measured trait in groundnut. Further, the current study successfully demonstrated that selection based on 100-kernel weight will result in the improvement of dry pod yield of groundnut.…”

Influence of planting pattern on peanut ecosystem daytime net carbon uptake, evapotranspiration, and water-use efficiency using the eddy-covariance method

“…Alabama, US by Davis and Mack (1991), 5.0-7.0 in Texas, US by Kiniry et al (2005), about 4.5-6.8 in Georgia, US by Rowland et al (2010), 5.1-5.3 in South China by Qi et al (2020), and 4.9-6.5 in Georgia, US by Zhang et al (2022). The observed higher CO 2 flux can be attributed to lower intra-row competition for space, light, water and nutrients in twin-row as compared to single-row peanut (Hauser and Buchanan, 1981;Wehtje et al, 1984).…”

Establishing Irrigation Thresholds for Furrow-Irrigated Peanuts

“…A water balance method utilizes known environmental parameters and crop growth stage to estimate soil water content. The primary water balance methods used across the USA and other international peanut‐growing regions include evaporation pans (Khan and Datta, 1982; Pahalwan and Tripathi, 1984; Rowland et al, 2010; Wright et al, 1986), Irrigator Pro (Lamb et al, 2007; Rowland et al, 2010), the University of Georgia Extension checkbook method (UGA‐EXT) (Rowland et al, 2010), MOISNUT (Davidson et al, 1998a), EXNUT (Davidson et al, 1998a,b), and AQUAMAN (Chauhan et al, 2013). Relative to producer‐derived methods or rainfed environments, water balance scheduling methods are purported to improve yield, net returns, and/or irrigation water use efficiency (IWUE) up to 50% in overhead‐irrigated environments (Chauhan et al, 2013; Davidson et al, 1998a,b).…”