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.

Accurate sensor-based prediction of crop yield and grain quality in-season would enable growers to adjust nitrogen (N) fertilizer management for optimized production. This study assessed the feasibility (and compared the accuracy) of wheat (Triticum aestivum L.) yield, grain N uptake, and protein content prediction with in-season crop spectral reflectance measurements (Normalized Difference Vegetative Index, NDVI) obtained with a handheld GreenSeeker (GS) sensor and an Unmanned Aerial Vehicle (UAV)-mounted sensor. A strong positive correlation was observed between GS NDVI and UAV NDVI at Feekes 5 (R² = 0.78) and Feekes 10 (R² = 0.70). At Feekes 5, GS NDVI and UAV NDVI explained 42% and 43% of wheat yield, respectively. The correlation was weaker at Feekes 10 (R² of 0.34 and 0.25 for GS NDVI and UAV NDVI, respectively). The accuracy of wheat grain N uptake prediction was comparable to that of yield: the R² values for GS NDVI and UAV NDVI were 0.53 and 0.37 at Feekes 5 and 0.13 and 0.20 at Feekes 10. We found that neither GS NDVI nor UAV NDVI in-season data were useful in prediction of wheat grain protein content. In conclusion, wheat yield and grain N uptake can be estimated at Feekes 5 using either handheld or aerial based NDVI with comparable accuracy.

Improvement of nitrogen use efficiency (NUE) via active optical sensors has gained attention in recent decades, with the focus of optimizing nitrogen (N) input while simultaneously sustaining crop yields. To the authors’ knowledge, a comprehensive review of the literature on how optical sensors have impacted winter wheat (Triticum aestivum L.) NUE and grain yield has not yet been performed. This work reviewed and documented the extent to which the use of optical sensors has impacted winter wheat NUE and yield. Two N management approaches were evaluated; optical sensor and conventional methods. The study included 26 peer-reviewed articles with data on NUE and grain yield. In articles without NUE values but in which grain N was included, the difference method was employed to compute NUE based on grain N uptake. Using optical sensors resulted in an average NUE of 42% (±2.8% standard error). This approach improved NUE by approximately 10.4% (±2.3%) when compared to the conventional method. Grain yield was similar for both approaches of N management. Optical sensors could save as much as 53 (±16) kg N ha⁻¹. This gain alone may not be adequate for increased adoption, and further refinement of the optical sensor robustness, possibly by including weather variables alongside sound agronomic management practices, may be necessary.

The accuracy of the traditional soil and plant‐based techniques for assessing sugarbeet demand for nitrogen (N) and yield prediction is generally low. Refining N and irrigation water management is a key to maximizing return for sugarbeet (Beta vulgaris L.) growers from agronomic, economic, and environmental perspective. The use of Normalized Difference Vegetative Index (NDVI) in combination with the unmanned aerial vehicle (UAV)‐based data collection for in‐season estimation of sugarbeet root yield and sugar concentration has potential for precision N management. Sugarbeet field trials were conducted in Idaho in 2019 and 2020 to assess (1) effects of water and N fertilizer rates on yield and estimated recoverable sugar (ERS) and (2) feasibility of predicting root yield and ERS using UAV NDVI. At the lowest N rate, application of water at 100% level resulted in greater yield, compared to 50%, in both years. At higher N rates, 50% level produced higher yields. At each N level, application of water at 100% level resulted in lower ERS, compared to 50%. The UAV NDVI was strongly correlated with root yield and ERS. The relationship between UAV NDVI and root yield and ERS was stronger in July (60 days after planting) compared to June (40 days after planting). Estimating the yield and ERS potential in late June/early July and topdressing the crop before the end of July may help to improve N use efficiency while optimizing sugarbeet production.

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.

Plant spacing and density are important metrics in crop production because they impact the plant’s ability to utilize resources and attain full yield potential. Planting sorghum (Sorghum bicolor (L.) Moench) in a more narrow spacing brings about phytochrome-mediated responses, where plants develop narrow leaves, long stems, fewer roots, and this is linked to competition that plants develop for nutrients like nitrogen (N). The Oklahoma State University hand planter (OSU-HP) can improve plant homogeneity and midseason placement of N. However, this crop production tool alongside other agronomic practices have not been adequately evaluated for improving sorghum grain yields. The objective of this work was to evaluate the response of sorghum to planting methods, the number of seeds per hole, within row spacing, and N rate. A randomized complete block design with 13 treatments replicated 3 times was used in this study. The treatments included different combinations of 3 planting methods (John Deere [JD], OSU-HP, and stick planter [check]), 3 within-row spacings (10, 30, and 60 cm), 3 different number of seeds per hole (1, 3, and 6) and 3 N rates (0, 30 and 60 kg ha⁻¹). Average grain yield with 3 seeds per hole was at least 18% higher than the yield range of 0.7 to 4.6 Mg ha⁻¹ achieved with 1 or 6 seeds per hole. This study demonstrated that the production of sorghum using sound agronomic practices could improve yield.