Biochar (B) has shown promise in improving crop productivity. However, its interaction with inorganic nitrogen (N) in temperate soils is not well-studied. The objective of this paper was to compare the effect of fertilizer N-biochar-combinations (NBC) and N fertilizer (NF) on maize (Zea mays L.) grain yield, N uptake, and N use efficiency (NUE). Trials were conducted in 2018 and 2019 at Efaw and Lake Carl Blackwell (LCB) in Oklahoma, USA. A randomized complete block design with three replications and ten treatments consisting of 50, 100, and 150 kg N ha⁻¹ and 5, 10, and 15 Mg B ha⁻¹ was used. At LCB, yield, N uptake, and NUE under NBC increased by 25%, 28%, and 46%, respectively compared to NF. At Efaw, yield, N uptake, and NUE decreased under NBC by 5%, 7%, and 19%, respectively, compared to NF. Generally, results showed a significant response to NBC at ≥10 Mg B ha⁻¹. While results were inconsistent across locations, the significant response to NBC was evident at LCB with sandy loam soil but not Efaw with silty clay loam. Biochar application with inorganic N could improve N use and the yield of maize cultivated on sandy soils with poor physical and chemical properties.

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.

Accurate winter wheat (Triticum aestivum L.) grain yield prediction is vital for improving N management decisions. Currently, most N optimization algorithms use in‐season estimated yield (INSEY) as a sole variable for predicting grain yield potential (YP). Although evidence suggests that this works, the yield prediction accuracy could be further improved by including other predictors in the model. The objective of this work was to evaluate INSEY, pre‐plant N rate, total rainfall, and average air temperature from September to December as predictors of winter wheat YP. An 8‐yr (2012–2019) data set for grain yield was obtained from Experiment 502, Lahoma, OK. The experiment was designed as a randomized complete block with four replications and N applied at 0, 45, 67, 90, and 112 kg ha^–1. Weather data was obtained from the Oklahoma Mesonet (http://mesonet.org). The data were analyzed using R statistical computing platform. The best model was selected using least absolute shrinkage and selection operator. Root mean square error (RMSE) was obtained using k‐fold cross‐validation. The model selection algorithm produced the full model as the best model for yield prediction with an R² of .79 and RMSE of 0.54 Mg ha^–1. The best one‐variable model – as expected – used INSEY as the predictor and had the highest RMSE of 0.72 Mg ha^–1 and an R² of .62. Mid‐season YP prediction accuracy could be improved by including pre‐plant N rate, mean air temperature, and total rainfall from September to December in a model already containing INSEY.

Crop nitrogen (N) use is always affected by the variability in production environment. Dataset (2001 to 2014) from long-term winter wheat (Triticum aestivum L.) experiments at Lahoma and Stillwater, Oklahoma was used. Both experiments have a randomized complete block design with four replications, and fertilizer N was applied as urea pre-plant. Responsiveness of grain yield to maximum fertilizer N rate (112 kg ha⁻¹ – Lahoma; 135 kg ha⁻¹ – Stillwater) was compared with that from check plot (0 kg ha⁻¹). The objective was to determine the relative influence of environment, management, and variety on winter wheat grain yield. The combined analysis of variance indicated that the main effect of year, treatment, location, and variety accounted for 29.3%, 21.2%, 3.1%, and 22.6%, respectively of the variance terms. Over the study period, the non-responsiveness of winter wheat to fertilizer N accounted for 29% and 23% of grain yield at Lahoma and Stillwater, respectively where yield at maximum N rate did not significantly differ from check plot. This highlights the importance of random changes in a crop production environment and its influence in dictating the response to applied N fertilizer. Nitrogen fertilizer losses could be reduced by adopting in-season variable N application techniques.

In the developing world, fertilizer application is commonly achieved by broadcasting nutrients to the soil surface without incorporation. A commonly used nitrogen (N) source is urea and if not incorporated, can sustain N losses via ammonia volatilization and lower crop yields. This study evaluated the effect of planting, N rate and application methods on maize (Zea mays L.) grain yield. An experiment with a randomized complete block design (nine treatments and three replications) was established in 2013 and 2018 in Oklahoma. The planting methods included; farmer practice (FP), Oklahoma State University hand planter (OSU-HP), and John Deere (JD) mechanical planter. Side-dress N application methods included; dribble surface band (DSB), broadcast (BR), and OSU-HP. Nitrogen was applied at the rate of 30 and 60 kg ha⁻¹ as urea and UAN at V8 growth stage. On average, planting and applying N at 60 kg ha⁻¹ using OSU-HP resulted in the highest yield (11.4 Mg ha⁻¹). This exceeded check plot yield (5.59 Mg ha⁻¹) by 104%. Nitrogen application improved grain yield by over 57% when compared to the 0-N check (8.77 Mg ha⁻¹). Mid-season N placement below the soil surface using OSU-HP makes it a suitable alternative to improve grain yield.

In many developing countries, crop production is achieved with little or no application of fertilizer N. Understanding grain yield trends as new winter wheat cultivars (Triticum aestivum L.) are released and grown under different N management is important for crop yield improvement. This study evaluated grain yield trends of winter wheat cultivars over time in a crop production system with and without N application. Yield data was obtained from two long‐term experiments; 502 (E502) and 222 (E222) between 1969 and 2018. Results showed a mean annual grain yield increase of 12 and 30 kg ha^–1 yr^–1 as new cultivars were released and grown under adequate N management in E222 and E502, respectively. However, without N application, yield declined annually by 2.4 kg ha^–1 yr^–1 in E222 and increased marginally by 0.6 kg ha^–1 yr^–1 in E502. Nonetheless, the yield increase or decrease was only significant for E502 at 112 kg N ha^–1 (r² = .145; p = .01) and its slope was significantly different from that of control treatment (p = .02). In both experiments, yield was significantly influenced by cultivar and N interaction (p < .01), an indication that yield changed according to the level of N applied. In general, when N was applied, grain yields were high as well. New cultivars released over time improved grain yield with adequate N management.