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Enhancing resource use efficiency in agricultural field management and breeding high-performance crop varieties are crucial approaches for securing crop yield and mitigating negative environmental impact of crop production. Crop stress sensing and plant phenotyping systems are integral to variable-rate (VR) field management and high-throughput plant phenotyping (HTPP), with both sharing similarities in hardware and data processing techniques. Crop stress sensing systems for VR field management have been studied for decades, aiming to establish more sustainable management practices. Concurrently, significant advancements in HTPP system development have provided a technological foundation for reducing conventional phenotyping costs. In this paper, we present a systematic review of crop stress sensing systems employed in VR field management, followed by an introduction to the sensors and data pipelines commonly used in field HTPP systems. State-of-the-art sensing and decision-making methodologies for irrigation scheduling, nitrogen application, and pesticide spraying are categorized based on the degree of modern sensor and model integration. We highlight the data processing pipelines of three ground-based field HTPP systems developed at the University of Nebraska-Lincoln. Furthermore, we discuss current challenges and propose potential solutions for field HTPP research. Recent progress in artificial intelligence, robotic platforms, and innovative instruments is expected to significantly enhance system performance, encouraging broader adoption by breeders. Direct quantification of major plant physiological processes may represent one of next research frontiers in field HTPP, offering valuable phenotypic data for crop breeding under increasingly unpredictable weather conditions. This review can offer a distinct perspective, benefiting both research communities in a novel manner.

Water supply limitations will likely impose increasing restrictions on future crop production, underlining a need for crops that use less water per mass of yield. Water use efficiency (WUE) therefore becomes a key consideration in developing resilient and productive crops. In this study, we hypothesized that it is possible to improve WUE under drought conditions via modulation of chloroplast signals for stomatal opening by up-regulation of non-photochemical quenching (NPQ). Nicotiana tabacum plants with strong overexpression of the PsbS gene encoding PHOTOSYSTEM II SUBUNIT S, a key protein in NPQ, were grown under differing levels of drought. The PsbS -overexpressing lines lost 11% less water per unit CO2 fixed under drought and this did not have a significant effect on plant size. Depending on growth conditions, the PsbS -overexpressing lines consumed from 4–30% less water at the whole-plant level than the corresponding wild type. Leaf water and chlorophyll contents showed a positive relation with the level of NPQ. This study therefore provides proof of concept that up-regulation of NPQ can increase WUE, and as such is an important step towards future engineering of crops with improved performance under drought. [ABSTRACT FROM AUTHOR]

With the CMOS technology downscaling to the deep nanoscale, the aging effects of devices degrade circuit performance and even lead to functional failure. The stress analysis is critical to evaluate the influence of aging effects on digital circuits. Some related analytical work has recently focused on reliability-aware circuit analysis. Nevertheless, the aging dependence among different devices is not considered, which will induce errors of degradation evaluation in the digital circuit. In order to improve the accuracy of reliability-aware static timing analysis, an improved analytical method is proposed by employing logical resolving. Experimental results show that the proposed method has a better evaluation accuracy of aging path delay than traditional strategies. For aging timing evaluation on aging paths, excessive pessimism can be reduced by employing the proposed method. And, a 378× speedup is achieved while having a 0.56% relative error compared with precise SPICE simulation. Moreover, the circuit performance sacrifice of an aging-aware synthesis flow with the proposed method can be decreased. Due to the high efficiency and high accuracy, the proposed method can meet the speed demands of large-scale digital circuit reliability analysis while achieving transistor simulation accuracy. [ABSTRACT FROM AUTHOR]