Peru is the second-largest rice producer in Latin America, with 406166 ha grown annually, predominately on the Peruvian north coast. However, rice is primarily irrigated by flooding (93%), which demands high water use (15000-18000 m3 ha−1) owing to low water-use efficiency. Additionally, the intensification of climate change is of great concern as it causes high variability as well as a decreasing trend in water resource availability. Alternate wetting and drying (AWD) irrigation technique reportedly reduce the irrigation volumes while maintaining conventional yield rates. The AquaCrop model was calibrated and assessed to simulate rice yield response to the AWD technique under water shortage conditions on the Peruvian central coast. The AquaCrop model exhibited a “very good” to “good” performance in predicting canopy cover development, soil water content, aerial biomass, and gr...

Peru is the second-largest rice producer in Latin America, with 406166 ha grown annually, predominately on the Peruvian north coast. However, rice is primarily irrigated by flooding (93%), which demands high water use (15000-18000 m3 ha−1) owing to low water-use efficiency. Additionally, the intensification of climate change is of great concern as it causes high variability as well as a decreasing trend in water resource availability. Alternate wetting and drying (AWD) irrigation technique reportedly reduce the irrigation volumes while maintaining conventional yield rates. The AquaCrop model was calibrated and assessed to simulate rice yield response to the AWD technique under water shortage conditions on the Peruvian central coast. The AquaCrop model exhibited a “very good” to “good” performance in predicting canopy cover development, soil water content, aerial biomass, and gr...

Here, we report the prediction of vegetative stages variables of canary bean crop by means of RGB and multispectral images obtained from UAV during the ripening stage, correlating the vegetation indices with biometric variables measured manually in the field. Results indicated a highly significant correlation of plant height with eight RGB image vegetation indices for the canary bean crop, which were used for predictive models, obtaining a maximum correlation of R2 = 0.79. On the other hand, the estimated indices of multispectral images did not show significant correlations.

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Early assessment of crop development is a key aspect of precision agriculture. Shortening the time of response before a deficit of irrigation, nutrients and damage by diseases is one of the usual concerns in agriculture. Early prediction of crop yields can increase profitability in the farmer's economy. In this study we aimed to predict the yield of four maize commercial hybrids (Dekalb7508, Advanta9313, MH_INIA619 and Exp_05PMLM) using remotely sensed spectral vegetation indices (VI). A total of 10 VI (NDVI, GNDVI, GCI, RVI, NDRE, CIRE, CVI, MCARI, SAVI, and CCCI) were considered for evaluating crop yield and plant cover at 31, 39, 42, 46 and 51 days after sowing (DAS). A multivariate analysis was applied using principal component analysis (PCA), linear regression, and r-Pearson correlation. In the present study, highly significant correlations were found between plant cover with VIs at...