Soft winter wheat outyields hard winter wheat in a subhumid environment: Weather drivers, yield plasticity, and rates of yield gain

Abstract

Despite the proximity in zones of adaptation for soft and hard winter wheat (SWW and HWW; Triticum aestivum L.), agronomic evaluations have been confined to market class. Our objectives were to compare SWW and HWW regarding yield and agronomic attributes; genotype, environment, and their interaction; and rates of yield gain. Yield, grain volume weight, heading date, and plant height were collected from 40 adjacent studies evaluating HWW and SWW cultivars in 20 Kansas environments (n = 2,885). Growing season weather partially explained the variability in yield (47-51%), heading date (58-92%), and plant height (67-80%). Yield was greater in SWW than in HWW (3.73 vs. 3.48 Mg ha −1 ), and a quadratic relationship between the 10th, mean, and 90th percentile yields suggested that SWW has a greater yield potential than HWW, although grain volume weight was greater in HWW (743 vs. 733 kg m −3 ). An asymmetric yield response for both classes was associated with greater phenotypic plasticity, which portrayed a more positive response for SWW. We performed a literature review that suggested a greater genetic gain for SWW than for HWW (33 vs. 17 kg ha −1 yr −1 ). This gain, however, represented a smaller portion of the regional yield gain (considering both genetic gain and adoption of agronomic practices) of each class (72 vs. 81%). We concluded that SWW outyields HWW due to greater rates of genetic gain, partially due to breeding in higher yield environments, and more positive phenotypic plasticity of yield in high-yielding environments coupled to yield stability in excessively moist environments.Abbreviations: DOY, day of year; HWW, hard winter wheat; SWW, soft winter wheat.

Wheat grain and straw yield, grain quality, and disease benefits associated with increased management intensity

“…Since 2015, the United States has produced an average of 2.75 t ha −1 of wheat (40.89 bushels acre −1 ) across all wheat acreage (Supplemental Table S1). Midwest states expect and obtain higher yields than other winter wheat–producing regions in the Great Plains due to wheat class as well as increased moisture and lower temperatures that allow wheat to thrive (Lollato et al., 2020; Vocke & Ali, 2013). Therefore, Midwest wheat farmers, including Wisconsin farmers, should consider adopting some of the practices used in the mid‐ and high‐level management strategies in this study because they had even higher yields and profits than the current strategy widely used in Midwestern states.…”

“…A Swiss study examining 20 yr of winter wheat data shows that genetics explains more variation under a high‐input management approach than a low‐input or organic approach (Herrera et al., 2020), suggesting that high‐input management can optimize yields across varieties and enhance knowledge about variety yield potential. In Midwest states like Wisconsin, soft red winter wheat is commonly grown, which has higher yield potential than hard red winter wheat (Lollato, Roozeboom, Lingenfelser, Lemes da Silva, & Sassenrath, 2020), so additional inputs may be worthwhile if they lead to higher yields. However, additional inputs require additional expenditures, and the economic value of wheat grain has decreased in recent years (data not shown).…”

Genotype‐specific nitrogen uptake dynamics and fertilizer management explain contrasting wheat protein concentration

“…Split N applications have been associated with reduced risk of plant lodging and increased wheat yield and GPC (Schulz et al., 2015; Walsh, Shafian, & Christiaens, 2018; Wu et al., 2019). Improvements in NUE through genotype selection can arise from different commercial wheat classes (Bicego, Sapkota, & Torrion, 2019; Lollato, Roozeboom, Lingenfelser, da Silva, & Sassenrath, 2020a; Marti & Slafer, 2014) or hybrid wheat (Prey, Kipp, Hu, & Schmidhalter, 2019a), though commercially these options are restricted to few growing regions. Within a wheat class, there is large genetic variation in NUE but this usually reflects differences in yield (Hawkesford, 2014), and the opportunities to break the negative yield‐GPC relationship through genotypes combining good yield and GPC are restricted (Cox, Qualset, & Rains, 1985; Latshaw, Vigil, & Haley, 2016; Monaghan, Snape, Chojecki, & Kettlewell, 2001).…”

Toward a Better Understanding of Genotype × Environment × Management Interactions—A Global Wheat Initiative Agronomic Research Strategy

“…Historically, concomitant advancements in breeding and agronomy translated into yield improvements for wheat at the farm level, though the individual contribution of each varied by region (Bell et al, 1995;Nalley et al, 2008;Lollato et al, 2020). Technologies developed to support efforts related to plant breeding more consistently resulted in deployment of tools when compared to agronomy, perhaps because the end user of the tool is the breeder rather than the producer.…”