Intensive systems with two or three rice (Oryza sativa L.) crops per year account for about 50% of the harvested area for irrigated rice in Asia. Any reduction in productivity or sustainability of these systems has serious implications for global food security. Rice yield trends in the world’s longest-running long-term continuous cropping experiment (LTCCE) were evaluated to investigate consequences of intensive cropping and to draw lessons for sustaining production in Asia. Annual production was sustained at a steady level over the 50-y period in the LTCCE through continuous adjustment of management practices and regular cultivar replacement. Within each of the three annual cropping seasons (dry, early wet, and late wet), yield decline was observed during the first phase, from 1968 to 1990. Agronomic improvements in 1991 to 1995 helped to reverse this yield decline, but yield increases did not continue thereafter from 1996 to 2017. Regular genetic and agronomic improvements were sufficient to maintain yields at steady levels in dry and early wet seasons despite a reduction in the yield potential due to changing climate. Yield declines resumed in the late wet season. Slower growth in genetic gain after the first 20 y was associated with slower breeding cycle advancement as indicated by pedigree depth. Our findings demonstrate that through adjustment of management practices and regular cultivar replacement, it is possible to sustain a high level of annual production in irrigated systems under a changing climate. However, the system was unable to achieve further increases in yield required to keep pace with the growing global rice demand.

Modern cotton (Gossypium hirsutum L.) cultivars are more productive and have unique growth and fruiting characteristics due to optimization of genetics and management practices in the past 30 yr. The most recent work evaluating nutrient uptake and partitioning by cotton was conducted in the early 1990s, necessitating a re-evaluation of nutrient accumulation and requirements in modern high productivity cultivars. Modern cultivar (FiberMax [FM] 958 and Deltapine [DP] 1646) resource allocation, including dry matter production, yields, and accumulation and partitioning of N, P, K, Ca, Mg, and S to different organs, was compared with that of a 1990s cultivar (Paymaster [PM] HS26) in 2018 and 2019. The modern cultivars tested in this study partitioned a greater percentage of dry matter, N, P, K, and S into the fruit than the older cultivar, highlighting the importance of partitioning for increased production potential of these cultivars from the 1990s to the 2010s. Greater efficiencies in partitioning and remobilization of N, P, K, and S resulted in 66, 88, 64, and 30% increase in the amount of lint yield produced for every unit of uptake, respectively, under favorable growing conditions. These findings suggest that existing fertility paradigm in cotton may underestimate the accumulation expectations during the middle and latter part of the growing season. These results can be a basis for optimizing nutrient application to address partitioning changes. Adjusting nutrient recommendations to the shift in cultivar growth characteristics may improve both yield and application efficiency of fertilizers. 1 INTRODUCTION Nutrient uptake and partitioning among plant tissues of cotton (Gossypium hirsutum L.) grown under both dryland and irrigated conditions have been documented in

Recent technological advances in cotton (Gossypium hirsutum L.) phenotyping have offered tools to improve the efficiency of data collection and analysis. High-throughput phenotyping (HTP) is a non-destructive and rapid approach of monitoring and measuring multiple phenotypic traits related to the growth, yield, and adaptation to biotic or abiotic stress. Researchers have conducted extensive experiments on HTP and developed techniques including spectral, fluorescence, thermal, and three-dimensional imaging to measure the morphological, physiological, and pathological resistance traits of cotton. In addition, ground-based and aerial-based platforms were also developed to aid in the implementation of these HTP systems. This review paper highlights the techniques and recent developments for HTP in cotton, reviews the potential applications according to morphological and physiological traits of cotton, and compares the advantages and limitations of these HTP systems when used in cotton cropping systems. Overall, the use of HTP has generated many opportunities to accurately and efficiently measure and analyze diverse traits of cotton. However, because of its relative novelty, HTP has some limitations that constrains the ability to take full advantage of what it can offer. These challenges need to be addressed to increase the accuracy and utility of HTP, which can be done by integrating analytical techniques for big data and continuous advances in imaging.

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The use of high-throughput phenotyping aids breeding programs in making more informed selections and advancements. This study's objectives were to determine which proximal remote sensing parameters (normalized difference red edge [NDRE], normalized difference vegetation index [NDVI], difference between canopy and air temperatures [∆T], and plant height) are robust estimators of cotton lint yield and to use a time-integrated function of one parameter as a single phenotypic measurement for predicting yield. This study evaluated remote sensing parameters (NDRE, NDVI, ∆T, and plant height) measured weekly from squaring through boll production and development. Of these measurements, NDRE was most consistent in terms of r 2 , slope, and normality in predicting yield. From these findings, a temporal analysis was calculated as NDRE integrated over the season, namely NDRE-days. Significant r 2 values were detected for the individual remote sensing measurements, with the largest r 2 occurring around peak bloom (80 d after planting). An r 2 of 0.81 was identified between ∆T and lint yield in 2015, whereas in 2017 the largest r 2 value with lint yield was with NDRE (r 2 = .71). The temporal analysis showed a significant relationship between NDRE-days and lint yield (P < .0001; r 2 = .58 in 2015 and r 2 = .68 in 2017) that was not cultivar specific. This study presents a suitable method that breeders could use to efficiently evaluate plant growth and estimate yield for variety selections while cutting resource requirements.Abbreviations: ∆T, difference between canopy temperature and air temperature; ET, evapotranspiration; FM, FiberMax; GDD 15.6 , 15.6 • C growing degree days; GPS, global positioning system; NDRE, normalized difference red edge; NDVI, normalized difference vegetation index; SDI, subsurface drip irrigation; ST, Stoneville.

Combining production of low‐input alternative crops together with cotton (Gossypium hirsutum L.) under deficit irrigation (DI) has gained attention for purposes of rotation, diversification, and saving water resources in West Texas. The objective of this study was to determine a relationship between water extraction patterns and water use efficiency (WUE) of crops tolerant of the semiarid conditions in West Texas. Irrigation responses of cotton, sesame (Sesamum indicum L.), and grain sorghum [Sorghum bicolor (L.) Moench] were compared in 2017 and 2018 at irrigation levels ranging from extreme DI to mild DI based on crop yield, aboveground biomass, water extraction patterns, and WUE. Cotton and sorghum biomass production and yield increased with irrigation rate, whereas sesame productivity was not significantly increased in either year. The water extraction patterns suggested that the rooting system of sesame was not as extensive compared with cotton and sorghum and did not change substantially among irrigation treatments, and sesame yields did not significantly vary among DI treatments. The implication is that the biomass production and yield of sesame, even under low irrigation management, was not water limited, even in irrigation treatments that resulted in 25% yield losses in sorghum and 40% yield losses in cotton. As a result, the WUE of sesame was dramatically decreased with additional irrigation, whereas cotton and sorghum maintained similar WUE under all irrigation treatments. Therefore, water‐limiting environments may not actually be water limiting to sesame, and the bigger limitation is the yield potential associated with a baseline irrigation level far below that of cotton or sorghum.

Boll distribution provides an important assessment of the response and adaptation of upland cotton (Gossypium hirsutum L.) to its environment and is strongly linked to yield and fiber quality and consequently to economic value. Several studies have measured boll distribution through end-of-season field or box mapping to study the spatiotemporal characteristics of bolls at both the plant and field levels, to quantify the effects of stress on cotton maturity and fiber quality, and to estimate yield as a function of the relative partitioning of resources to competing sinks. This paper discusses the environmental factors affecting boll production and distribution, reviews methods of measuring and analyzing boll distribution, and discusses the comparative advantages and drawbacks of these methods. With the advent of advanced imaging technologies, this paper also discusses the potential transition from traditional methods to machine-based boll distribution measurements, the challenges associated with these technologies, and how continuous improvements in the baseline technologies being used in the different methods will translate to improved measurement capacities. Overall, major strides can still be made in the area of boll distribution measurement by combining the positive elements in the different studies described in this review to circumvent each of their respective limitations.

Non-optimal application of nitrogen (N) fertilizer in cotton (Gossypium hirsutum L.) production systems often results from a producer’s uncertainty in predicting the N rate that ensures maximum economic return. Residual soil nitrate-N (NO3-N) is also often unaccounted for in fertilizer management decisions. In this study, the lint yield and profitability of two cotton cultivars (FiberMax FM 958 and Deltapine DP 1646 B2XF) were compared across five N fertilizer treatments [0 kg ha−1 (control), 45 kg ha−1 (N-45), 90 kg ha−1 (N-90), 135 kg ha−1 (N-135), 180 kg ha−1 (N-180)] from 2018 to 2020. For both cultivars, additional N fertilizer on top of the control treatment did not increase the lint yield of cotton. For each year, both control and N-45 treatments resulted in the greatest revenue above variable costs (RAVC) values for all cultivars. The improved N partitioning efficiency in newer cultivars and the high levels of residual soil NO3-N allowed sustained plant growth and yield even with reduced N application. Overall, the results show the advantage of reducing N inputs in residual N-rich soils to maintain yield and increase profits. These findings are important in promoting more sustainable agricultural systems through reduced chemical inputs and maintained soil health.