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Browsing by Author "Jackson, Chad"

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    Spring wheat yield and grain quality response to nitrogen rate
    Walsh, Olga S.; Marshall, Juliet; Nambi, Eva; Shafian, Sanaz; Jayawardena, Dileepa; Jackson, Chad; Lamichhane, Ritika; Owusu Ansah, Emmanuella; McClintick-Chess, Jordan (Wiley, 2022-07-01)
    Nitrogen (N) is the most limiting nutrient in cereal production, yet its use efficiency remains very low at only 35%. Nutrient use efficiency (NUE) is crucial for increasing crop yield and quality while reducing fertilizer inputs and minimizing environmental damage. Optimum N rates that maximize yield without reducing NUE have been found to vary from location to location. This field study assessed the effect of N rates on the yield and quality of spring wheat (Triticum aestivum L.) at five locations in southern Idaho in 2015–2017. Nitrogen was applied as urea (46–0–0) immediately after planting at five rates: 0, 84, 168, 252, and 336 kg ha–1. Nitrogen application improved grain quality (increased protein) even when no increase in yield was noted. Nitrogen use efficiency and N uptake were affected by N rate at only 2 and 4 of 14 site-years, respectively. These observations highlight the challenging task of pinpointing the appropriate N rates for optimizing wheat yield, grain protein, N uptake and NUE; and the importance of adjusting N rates based on location, year, and prevalent environmental conditions.
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    Wheat yield and protein estimation with handheld- and UAV-based reflectance measurements
    Walsh, Olga S.; Marshall, Juliet; Jackson, Chad; Nambi, Eva; Shafian, Sanaz; Jayawardena, Dileepa M.; Lamichhane, Ritika; Owusu Ansah, Emmanuella; McClintick-Chess, Jordan R. (Wiley, 2022-09-27)
    Precision agriculture provides efficient means of obtaining real-time data to guide nitrogen (N) management based on predicted crop profitability. This study was conducted to assess the efficacy of using in-season measurements (plant height, biomass weight, biomass N, soil plant analysis development [SPAD], GreenSeeker [GS] normalized difference vegetative index [NDVI], and unmanned aerial vehicle [UAV] NDVI) at Feekes 5 (tillering) and Feekes 10 (anthesis) to estimate wheat (Triticum aestivum L.) yield and protein. The secondary aim was to determine whether the accuracy of yield and protein prediction varies by wheat class and cultivar. Six cultivars—hard red spring (HRS) wheat ‘Jefferson’ and ‘SY Basalt’, hard white spring (HWS) wheat ‘Dayn’ and ‘UI Platinum’, and soft white spring (SWS) wheat ‘Seahawk’ and ‘UI Stone’—were planted at two locations in Idaho in 2018–2020. Plots were arranged in a randomized complete block design with four replications with each cultivar evaluated at seven N rates (0, 50, 100, 150, 200, 250, and 300 kg N ha–1). The determination of the Pearson correlation coefficients revealed that all parameters were linearly correlated with yield except for SPAD at Feekes 5 and biomass weight at Feekes 10. Although estimation of in-season grain protein remains a challenge, NDVI was strongly correlated with yield especially at Feekes 5. The accuracy of yield prediction was similar for all wheat classes. Comparable accuracy of yield estimation was achieved with GS NDVI and UAV NDVI. Both hand-held and aerial-based spectral measurements could be used to prescribe N rates to be applied during tiller formation when wheat yield can be optimized.