Determining a precise nitrogen fertilizer requirement for maize in a particular field and year has proven to be a challenge due to the complexity of the nitrogen inputs, transformations and outputs in the nitrogen cycle. Remote sensing of maize nitrogen deficiency may be one way to move nitrogen fertilizer applications closer to the specific nitrogen requirement. Six vegetation indices [normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), red-edge normalized difference vegetation index (RENDVI), triangle greenness index (TGI), normalized area vegetation index (NAVI) and chlorophyll index-green (CI_green)] were evaluated for their ability to detect nitrogen deficiency and predict grain maize grain yield. Strip trials were established at two locations in Arkansas, USA, with nitrogen rate as the primary treatment. Remote sensing data was collected weekly with an unmanned aerial system (UAS) equipped with a multispectral and thermal sensor. Relationships among index value, nitrogen fertilizer rate and maize growth stage were evaluated. Green NDVI, RENDVI and CI_green had the strongest relationship with nitrogen fertilizer treatment. Chlorophyll Index-green and GNDVI were the best predictors of maize grain yield early in the growing season when the application of additional nitrogen was still agronomically feasible. However, the logistics of late season nitrogen application must be considered.

The Lower Mississippi River Basin (LMRB) is an internationally‐important region of intensive agricultural crop production that relies heavily on the underlying Mississippi River Valley Alluvial Aquifer (MRVAA) for irrigation. Extensive irrigation coupled with the region’s geology have led to significant aquifer decline. The response to the decline has been multi‐faceted. Research related to three responses are highlighted: innovation in rice irrigation, on‐farm reservoirs, and managed aquifer recharge. Irrigated rice grown in Arkansas, which is nearly 50% of annual U.S. rice production, accounts for a significant portion of aquifer withdrawal. As a result, strategies for using less water while maintaining rice yields are being developed. The Rice Stewardship Partnership (RSP) began in 2015 and aims to improve irrigation management in rice lands of the LMRB. Early results from the RSP are presented. Secondly, on‐farm reservoir‐tailwater recovery systems (R‐TWRS) are increasingly used to store abundant surface water in the LMRB. Over 700 R‐TWRS are currently used in rice producing areas of Arkansas. The confining clay layer that overlies the MRVAA in many locations limits rates of aquifer recharge. Locations where the confining layer is thin or non‐existent may provide opportunities for artificial (i.e., managed) recharge. A 10‐m deep excavation pit from a highway project provided an opportunity to measure infiltration rates of the uppermost section of the alluvial aquifer. Findings from this and other studies are used to demonstrate how conservation, off‐season rainfall capture and storage, and managed recharge are being investigated as means to reduce the on‐going decline of the alluvial aquifer that is both economically and ecologically important to the LMRB.

Improved irrigation management is identified as a potential mitigation option for methane (CH₄) emissions from rice (Oryza sativa). Furrow-irrigated rice (FR), an alternative method to grow rice, is increasingly adopted in the Mid-South U.S. However, FR may provide a potential risk to yield performance and higher emissions of nitrous oxide (N₂O). This study quantified the grain yields, CH₄ and N₂O emissions from three different water management practices in rice: multiple-inlet rice irrigation (MIRI), FR, and FR with cereal rye (Secale cereale) and barley (Hordeum vulgare) as preceding winter cover crops (FRCC). CH₄ and N₂O fluxes were measured from May to September 2019 using a static chamber technique. Grain yield from FR (11.8 Mg ha⁻¹) and MIRI (12.0 Mg ha⁻¹) was similar, and significantly higher than FRCC (8.5 Mg ha⁻¹). FR and FRCC drastically reduced CH₄ emissions compared to MIRI. Total seasonal CH₄ emissions decreased in the order of 44 > 11 > 3 kg CH₄-C ha⁻¹ from MIRI, FR, and FRCC, respectively. Cumulative seasonal N₂O emissions were low from MIRI (0.1 kg N₂O-N ha⁻¹) but significantly higher from FR (4.4 kg N₂O-N ha⁻¹) and FRCC (3.0 kg N₂O-N ha⁻¹). However, there was no net difference in global warming potential among FR, FRCC and MIRI. These results suggest that the increased N₂O flux from furrow-irrigated rice may not greatly detract from the potential benefits that furrow-irrigation offers rice producers.

Global nighttime temperatures are rising at twice the rate of daytime temperatures and pose a challenge for rice (Oryza sativa) production. High nighttime temperature (HNT) stress affects rice yield by reducing grain weight, size, and fertility. Although the genes associated with these yield parameters have been identified and characterized under normal temperatures, the genetic basis of grain weight regulation under HNT stress remains less explored. We examined the natural variation for rice single grain weight (SGW) under HNT stress imposed during grain development. A genome-wide association analysis identified several loci associated with grain weight under HNT stress. A locus, single grain weight 1 (SGW1), specific to HNT conditions resolved to LONELY GUY-Like 1 (LOGL1), which encodes a putative cytokinin activation enzyme. We demonstrated that LOGL1 contributes to allelic variation at SGW1. Accessions with lower LOGL1 transcript abundance had higher grain weight under HNT. This was supported by higher grain weight of logl1 mutants relative to the wild type under HNT. Compared to logl1 mutants, LOGL1 over-expressers showed increased sensitivity to HNT. We showed that LOGL1 regulates the thiamine biosynthesis pathway, which is under circadian regulation, which in turn is likely perturbed by HNT stress. These findings provide a genetic source to enhance rice adaptation to warming night temperatures and improve our mechanistic understanding of HNT stress tolerance pathways.