Metasurface shows selective solar–thermal energy conversion with high‐activity solar/laser‐driven chemistry. The breakthrough is co‐designing broadband FP‐cavity + plasmonic LSPR/SLR resonances in an ultra‐thin metamaterial so that it not only harvests the most efficient proportion of solar radiation but also suppresses mid and IR emissivity. Moreover,
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Effects of environmental factors on arsenic accumulation in rice under field conditions using a Bayesian state space model. [PDF]
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Non-maize hosts outperform maize in sustaining fall armyworm population during off-season irrigation in the tropics. [PDF]
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Harnessing discrete choice experiments to elicit preferred configurations of trustworthy AI augmented decision support systems for certified crop advisors. [PDF]
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Data-driven climate-smart strategies for boosting crop yield and minimizing greenhouse gas emissions by optimizing cropping systems and fertilization practices. [PDF]
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Design of a modular solver - Excel spreadsheet decision-support tool for calibrated nonlinear farm optimization in small holder farm systems. [PDF]
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Monitoring phosphorus content in winter wheat using feature fusion and feature selection from UAV remote sensing imagery. [PDF]
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Correcting Midseason Crop Coefficients for Climate
Journal of Irrigation and Drainage Engineering - ASCE, 2015AbstractIt is well known that crop coefficients are not necessarily transferrable from one location to another, for a variety of reasons.
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Crop coefficients of major crops in South India
Agricultural Water Management, 1994Abstract Crop coefficients (Kc) were estimated for cotton, sorghum and millet for tropical South India based on lysimeter measured actual evapotranspiration (ET) and reference crop ET computed by the modified Penman method. The estimated crop coefficients were 0.46, 0.70, 1.01, and 0.39 in the four crop stages for cotton.
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Irrigation crop coefficients for lowland rice
Irrigation and Drainage Systems, 1994Meteorological and lysimetric data for a period of nine years were used to develop crop coefficients for rice grown under lowland conditions in a sub-humid tropical climate in India. The estimated crop coefficients were found to be higher than those values recommended by FAO.
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