On-farm data-rich analysis explains yield and quantifies yield gaps of winter wheat in the U.S. central Great Plains

Jaenisch, B. R.; Munaro, Lucas Berger; Bastos, Leonardo M.; Moraes, M. T. C. de; Lin, Xiaomao; Lollato, Romulo P.

doi:10.1016/j.fcr.2021.108287

Cited by 24 publications

(20 citation statements)

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“…The average grain yield in the FP was 4.01 Mg ha –1 , which resulted in a yield gap of 1.37 Mg ha –1 when compared to the highest yielding treatment (Yw). Similar yield levels and yield gaps have been reported for the area under intensified management ( Jaenisch et al, 2019 , 2021 ; de Oliveira Silva et al, 2020b ), confirming the opportunity to increase current yields through management intensification.…”

Section: Discussionsupporting

confidence: 78%

“…The crop is grown predominantly under dryland conditions (∼94%, USDA-NASS, 2018 ), with a 10-year average yield of 2.8 Mg ha –1 , which corresponds to only 50–55% of the dryland yield potential (∼5.2 Mg ha –1 ; Patrignani et al, 2014 ; Lollato et al, 2017 ). A range of genotypic traits and agronomic management practices is proposed to modulate wheat yield in this region ( Lollato et al, 2020b ; Munaro et al, 2020 ; Jaenisch et al, 2021 ). For instance, improved fertility management, including the adoption of in-furrow starter fertilizer ( McConnell et al, 1986 ; Lollato et al, 2013 ; Maeoka et al, 2020 ), increased nitrogen rates ( Thomason et al, 2002 ; Walsh et al, 2018 ; Lollato et al, 2019a , 2021 ), and use micronutrients ( Zain et al, 2015 ), has been associated positively with yields.…”

Section: Introductionmentioning

confidence: 99%

“…The content of this manuscript first appeared in BJ’s Ph.D. dissertation according to Kansas State University policy and is available online ( Jaenisch, 2021 ). This is research contribution No.…”

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confidence: 99%

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

et al. 2022

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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.

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Section: Discussionsupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

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

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“…Proper wheat management strategies to match environmental conditions can enhance the yield and end‐use quality of wheat grains. Common practices that are manageable with these objectives include genotype selection, crop fertilization, foliar protection, and seeding rates and dates, among others 42 5 …”

Section: Introductionmentioning

confidence: 99%

“…A wheat management program includes the integration of several in‐season decisions, including, but not limited to, genotype selection, plant population, application of foliar fungicides, fertility levels, including the application of micronutrients, and use of in‐furrow starter fertilizer 17 . Even though producers always integrate management strategies in their commercial operations,42 15,18 the effects of integrated management practices instead of a single treatment such as fertilizer usage on wheat phenolics have not been reported. Furthermore, management strategies interact with environmental conditions and thus need to be investigated across a range of environments so that producers can adjust management strategies properly based on weather conditions and market preference.…”

Section: Introductionmentioning

confidence: 99%

Effect of environment and field management strategies on phenolic acid profiles of hard red winter wheat genotypes

et al. 2021

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BACKGROUND: Integrated wheat management strategies can affect grain yield and flour end-use properties. However, the effect of integrated management and its interaction with environmental factors on the phenolic acid profiles of wheat has not been reported. The phenolic acid profile has become another parameter for the evaluation of wheat quality due to its potential health benefits.RESULTS: Year × location × management and year × management × genotype interactions were significant for the total phenolic content (TPC) of wheat samples. The year × location × management × genotype interaction was significant for the concentration of trans-ferulic acid and several other phenolic acids. Field management practices with no fungicide application (e.g., farmer's practice, enhanced fertility) may lead to increased accumulation of phenolic compounds, especially for WB4458, which is more susceptible to fungi infection. However, this effect was also related to growing year and location. Higher soil nitrogen content at sowing also seems to affect the TPC and phenolic acid concentration positively.CONCLUSION: Wheat phenolic acid profiles are affected by genotype, field management, environment, and their interactions. Intensified field management, in particular, may lead to decreased concentration of wheat phytochemicals. The level of naturally occurring nitrogen in the soil may also affect the accumulation of wheat phytochemicals.

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Winter wheat light interception measured with a quantum sensor and images

2022

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Light interception (LI) measurements are essential for modeling crop biomass and grain yield. Canopy LI is often measured with linear quantum sensors, but the need for unobstructed sunlight near solar noon can make field measurements impractical.We aimed to evaluate the use of the fraction of green canopy cover (FGCC) as a surrogate for LI in winter wheat (Triticum aestivum L.) canopies. A linear quantum sensor and a camera were used to collect 930 observations during the 2021 growing season across three locations in Kansas. Images were analyzed with the Canopeo application. The quantum sensor was also used to estimate the LI and leaf area index (LAI) in different canopy strata. Growing season shoot dry biomass was modeled with LI values from images and the quantum sensor. The LI estimated by the quantum sensor and images resulted in a strong positive linear correlation (r = 0.97). During the vegetative stages, LI values from images were generally greater than the LI values from the quantum sensor. During the reproductive stages, LI values from images were generally lower than those obtained by the quantum sensor, which was partly attributed to the better discrimination of FGCC for senescing vegetation. Using images to measure LI was easier and faster in prostrate canopies, and less sensitive to soil microrelief and changing sky conditions. The quantum sensor was useful for quantifying LI and LAI nondestructively in different canopy layers. Final growing season shoot dry biomass determined by either method was within 5% of the observed biomass.

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On-farm data-rich analysis explains yield and quantifies yield gaps of winter wheat in the U.S. central Great Plains

Cited by 24 publications

References 69 publications

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

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

Effect of environment and field management strategies on phenolic acid profiles of hard red winter wheat genotypes

Winter wheat light interception measured with a quantum sensor and images

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