Modulation of Wheat Yield Components in Response to Management Intensification to Reduce Yield Gaps

Abstract

Appropriate genotype selection and management can impact wheat (Triticum aestivum L.) yield in dryland environments, but their impact on yield components and their role in yield modulation are not well understood. Our objectives were to evaluate the yield response of commercial winter wheat genotypes to different management practices reflecting a stepwise increase in management intensity (including a reduction in crop density under high input), and to quantify how the different yield components modulate wheat yield. A factorial experiment evaluated six management (M) intensities [“farmer practice” (FP), “enhanced fertility” (EF), “ecological intensification” (EI), “increased foliar protection” (IFP), “water-limited yield” (Yw), and “increased plant productivity” (IPP)] and four winter wheat genotypes (G) in four Kansas environments (E). Average grain yield was 4.9 Mg ha–1 and ranged from 2.0 to 7.4 Mg ha–1, with significant two-way interactions (E × M and E × G). The EF usually maximized yields in dry environments, while EI, which consisted of EF plus one fungicide application, maximized yields in environments with greater water availability. Across all sources of variation, kernels m–2 and aboveground biomass were the strongest modulators of yield as compared to kernel weight and harvest index, while spikes m–2 and kernels spike–1 modulated yields at a similar magnitude. Foliar fungicides improved yield through increased green canopy cover duration and greater radiation intercepted during grain filling. When crop density was reduced from 2.7 to 1.1 million plants per hectare in an otherwise high-input system, plants produced more productive tillers (with genotype-specific response); however, reduced green canopy cover at anthesis and reduced cumulative solar radiation intercepted during grain filling limited wheat yield—although large differences in canopy cover or intercepted radiation were needed to cause modest changes in yield. Treatments more intensive than EI were not warranted as EF or EI maximized yields at all environments, and practices that promote biomass and kernels m–2 are to be targeted for future increases in wheat yield.

Intensive management simultaneously reduces yield gaps and improves milling and baking properties of bread wheat

“…Grain yield gaps averaged 859 kg ha −1 , which is similar to previous reports for this region (de Oliveira Silva et al., 2020, 2021; Jaenisch et al., 2019, 2021, 2022). While the current study considered a general improvement in management through a high‐input practice and a couple of alternative practices restricting either foliar fungicides or nitrogen rates, at the farmer level such a high input may not be justifiable due to economic constraints, and therefore, the refinement of the recommendations should be specific to each production system (Andrade et al., 2022; Jaenisch et al., 2021).…”

“…Despite its importance within the United States and the global scenarios, Kansas still has wheat yields (∼3 Mg ha −1 ) that are well below their potential, that is, 5.0-5.5 Mg ha −1 (Lollato et al, 2017), resulting in a large yield gap (i.e., the difference between actual and potential yields). These large yield gaps were confirmed at the experimental (de Oliveira Jaenisch et al, 2019Jaenisch et al, , 2022Lollato & Edwards, 2015) and field levels (Jaenisch et al, 2021;Lollato et al, 2019a) and can be narrowed by management (Munaro et al, 2020). However, there have been no attempts to understand whether narrowing yield gaps through improved management impacts the end use quality of the wheat grain.…”

“…However, this increase in kernel number naturally originates smaller kernels as more kernels are developed in distal spikelets within the spike and in distal florets within the spikelet-which are naturally smaller than central spikelets and florets (Slafer et al, 2014(Slafer et al, , 2022. Thus, yield does not always associate with kernel weight either at the regional level (de Oliveira Silva et al, 2020;Jaenisch et al, 2022) or across large global datasets (Slafer et al, 2014(Slafer et al, , 2022. The weather during the critical period seems to also determine grain quality traits in oats (Avena sativa L.) (Sadras et al, 2019) and grain protein response to late-season N (Giordano et al, 2023).…”

Revisiting source versus sink limitations of wheat yield during grain filling

“…In fact, most photoperiod effects on the number of fertile florets and grains appear to be mediated by assimilate supply to the growing spike (Gonzales et al., 2005). Improving agronomic practices increases yield (Jaenisch et al., 2022) including maintaining leaf function (i.e., source) with fungicides under disease‐prone conditions (Cruppe et al., 2021; Jaenisch et al., 2022).…”

Monitoring Winter Wheat Crop Traits Change During Crop Development Using Sentinel-1 Backscatters

“…Timely and accurate estimation of AGDB is another crucial component of crop health assessment, decision-making on optimal crop management strategies, and grain yield forecasts (Jaenisch et al, 2022). (Fig.…”