Experimental and producer-reported data quantify the value of foliar fungicide to winter wheat and its dependency on genotype and environment in the U.S. central Great Plains

Cruppe, Giovana; DeWolf, Erick; Jaenisch, B. R.; Andersen, Kelsey F.; Valent, Barbara; Fritz, Allan K.; Lollato, Romulo P.

doi:10.1016/j.fcr.2021.108300

Cited by 15 publications

(17 citation statements)

References 107 publications

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“…We note, however, that increases in kernel weight through management associated positively with increases in yield (insert, Figure 4E ), in particular through the application of foliar fungicides ( Figure 6 ). These findings agree with previous reports of highly managed wheat in the U.S. Great Plains ( Lollato and Edwards, 2015 ; Jaenisch et al, 2019 ; Cruppe et al, 2021 ) suggesting that kernel weight might, in some conditions, partially explain increases in yield for wheat.…”

Section: Discussionsupporting

confidence: 92%

“…Wheat genotypes responded differently to increased yielding conditions but similarly to management ( Figure 2 and Table 3 ), suggesting that selecting wheat genotypes either with performance specific to the most reoccurring environment in a given region or with broad adaptability seems more promising than genotype-specific management. We note, however, that the lack of significant G × M interaction in this research might be due to a small sample size, as previous research with larger sample size showed significant G × M ( Thompson et al, 2014 ; Cruppe et al, 2021 ).…”

Section: Discussioncontrasting

confidence: 79%

“…However, we note that large reductions in the green leaf area or radiation intercepted were needed to cause modest reductions in yield ( Figure 7 ), likely because wheat is mostly sink-limited and very efficient in translocating stem reserves to the developing kernels ( Borrás et al, 2004 ). Even though foliar fungicides applied around anthesis have increased wheat yield and reduced the yield gap in the region ( Thompson et al, 2014 ; Jaenisch et al, 2019 ), producers may be reluctant to apply it consistently due to high environmental unpredictability ( Couëdel et al, 2021 ) and inconsistencies in yield response ( Cruppe et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…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. Likewise, genetic resistance to major diseases and its interaction with foliar fungicides are management variables of interest ( Lollato et al, 2019b ; de Oliveira Silva et al, 2020b ; Cruppe et al, 2021 ). The role of crop density seems a variable and dependent resource availability ( Fischer et al, 2019 ; Lollato et al, 2019b ; Bastos et al, 2020 ); thus, its potential to interact with other practices (e.g., Jaenisch et al, 2019 ) deserves further exploration.…”

Section: Introductionmentioning

confidence: 99%

“…Thus, management practices that affect kernels m –2 would expectedly have a greater impact on yield. Still, some management practices that mostly modulate kernel weight might also relate positively to yield in some environments ( Cruppe et al, 2021 ). To our knowledge, there have been no attempts to explicitly manipulate management practices that match important stages of crop development when different organs are produced and quantify their relationship to yield within a context of management intensification, which is crucial for food security ( Cassman and Grassini, 2020 ).…”

Section: Introductionmentioning

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: 92%

Section: Discussioncontrasting

confidence: 79%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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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Effect of traditional and intensive management on soft red winter wheat yield and profitability

2023

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Some farmers regard wheat (Triticum aestivum L.) as a low-input crop, whereas other farmers intensively manage wheat with many inputs, such as multiple foliar fungicide applications, S fertilizer, and split applications of N. This research aimed to identify the management practices that improve the yield and profitability of wheat grain and straw. An incomplete factorial omission trial was established at two locations in Ohio [the Western Agricultural Research Station (WARS) and Northwest Agricultural Research Station (NWARS)] during the 2020 and 2021 growing seasons. The tested management practices included a high seeding rate, a high N rate, a split application of N, a spring S application, a fungicide application at Feekes 9, and a fungicide application at Feekes 10.5.1. The treatments were intensive management (IM) (all tested management practices), traditional management (TM) (none of the tested management practices), and treatments consisting of the individual addition of each practice to TM or removal from the IM system. The IM increased grain yield at three of the four site-years by an average of 0.83 Mg ha −1 but did not increase the partial economic return at any site-year during this study. Individual treatment effects were rare and inconsistent. These results suggest that although IM can improve grain yield, it failed to do so economically at the grain prices and input costs used in this study. Farmers should use crop scouting techniques and disease forecasting tools to identify wheat fields that are likely to benefit from additional inputs such as fertilizer or foliar fungicide. INTRODUCTIONIn Ohio, winter wheat (Triticum aestivum L.) is the third most planted annual row crop by area after soybean [Glycine max (L.) Merrill] and corn (Zea mays L.

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Experimental and producer-reported data quantify the value of foliar fungicide to winter wheat and its dependency on genotype and environment in the U.S. central Great Plains

Cited by 15 publications

References 107 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

Winter wheat light interception measured with a quantum sensor and images

Effect of traditional and intensive management on soft red winter wheat yield and profitability

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