Tiller presence never reduced yield in evaluated environments and plant densities. In favorable scenarios, corn tillers have plant density compensation potential. Plant density adjustment was necessary to maximize yield for all environments. Corn tillers have plasticity potential to optimize defensive management strategies.
Tillers (commonly termed "suckers") have lower overall yield contributions in corn (Zea mays L.) than in other Poaceae species. Current research evaluating the value of tillers in corn is scarce, particularly under water-limited conditions. This study aims to quantify relationships between tiller, main plant, and full (considering both tiller and main plant fractions) plant aboveground biomass and yields of corn under low plant density scenarios. Experiments were conducted in the 2019 growing season at three sites across Kansas (Garden City, Goodland, and Manhattan) evaluating two tiller-prone corn hybrids common in this region (P0805AM and P0657AM) at two plant densities (10,000 and 17,000 plants/a) with tiller maintenance (YT) or tiller removal (NT) at the V10 growth stage (tenth leaf). Treatments were set in a split-split-plot under a randomized complete block design (RCBD) with three replications. Results showed that full shoot dry biomass at maturity was neutrally or positively influenced by both tiller presence and an increase in plant density. Although yield from ears on the main plant (herein termed as "main plant yields") can be negatively impacted by tillers, full yield of all portions of the plant (herein "full plant yields") were neutrally or positively influenced by tiller contributions. Tiller yield variation in this study was influenced by tiller reproductive development, specifically tassel and lateral ear types. Responsible mechanisms and environmental factors influencing these development processes remain largely unknown, and this will be the focus of continuing studies.
IntroductionCrop plasticity is fundamental to sustainability discussions in production agriculture. Modern corn (Zea mays L.) genetics can compensate yield determinants to a small degree, but plasticity mechanisms have been masked by breeder selection and plant density management preferences. While tillers are a well-known source of plasticity in cereal crops, the functional trade-offs of tiller expression to the hierarchical yield formation process in corn are unknown. This investigation aimed to further dissect the consequences of tiller expression on corn yield component determination and plasticity in a range of environments from two plant fraction perspectives – i) main stalks only, considering potential functional trade-offs due to tiller expression; and ii) comprehensive (main stalk plus tillers). MethodsThis multi-seasonal study considered a dataset of 17 site-years across Kansas, United States. Replicated field trials evaluated tiller presence (removed or intact) in two hybrids (P0657AM and P0805AM) at three target plant densities (25000, 42000, and 60000 plants ha-1). Record of ears and kernels per unit area and kernel weight were collected separately for both main stalks and tillers in each plot. ResultsIndicated tiller contributions impacted the plasticity of yield components in evaluated genotypes. Ear number and kernel number per area were less dependent on plant density, but kernel number remained key to yield stability. Although ear number was less related to yield stability, ear source and type were significant yield predictors, with tiller axillary ears as stronger contributors than main stalk secondary ears in high-yielding environments. DiscussionsCertainly, managing for the most main stalk primary ears possible – that is, optimizing the plant density (which consequently reduces tiller expression), is desirable to maximize yields. However, the demonstrated escape from the deterministic hierarchy of corn yield formation may offer avenues to reduce corn management dependence on a seasonally variable optimum plant density, which cannot be remediated mid-season.
IntroductionWhile globally appreciated for reliable, intensification-friendly phenotypes, modern corn (Zea mays L.) genotypes retain crop plasticity potential. For example, weather and heterogeneous field conditions can overcome phenotype uniformity and facilitate tiller expression. Such plasticity may be of interest in restrictive or otherwise variable environments around the world, where corn production is steadily expanding. No substantial effort has been made in available literature to predict tiller development in field scenarios, which could provide insight on corn plasticity capabilities and drivers. Therefore, the objectives of this investigation are as follows: 1) identify environment, management, or combinations of these factors key to accurately predict tiller density dynamics in corn; and 2) test outof-season prediction accuracy for identified factors.MethodsReplicated field trials were conducted in 17 diverse site-years in Kansas (United States) during the 2019, 2020, and 2021 seasons. Two modern corn genotypes were evaluated with target plant densities of 25000, 42000, and 60000 plants ha -1. Environmental, phenological, and morphological data were recorded and evaluated with generalized additive models.ResultsPlant density interactions with cumulative growing degree days, photothermal quotient, mean minimum and maximum daily temperatures, cumulative vapor pressure deficit, soil nitrate, and soil phosphorus were identified as important predictive factors of tiller density. Many of these factors had stark non-limiting thresholds. Factors impacting growth rates and photosynthesis (specifically vapor pressure deficit and maximum temperatures) were most sensitive to changes in plant density. Out-of-season prediction errors were seasonally variable, highlighting model limitations due to training datasets.DiscussionThis study demonstrates that tillering is a predictable plasticity mechanism in corn, and therefore could be incorporated into decision tools for restrictive growing regions. While useful for diagnostics, these models are limited in forecast utility and should be coupled with appropriate decision theory and risk assessments for producers in climatically and socioeconomically vulnerable environments.
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