In the last decades, several methodologies for estimating crop phenology based on remote sensing data have been developed and used to create different algorithms. Although many studies have been conducted to evaluate the different methodologies, a comprehensive understanding of the potential of the different current algorithms to detect changes in the growing season is still lacking, especially in large regions and with more than one crop per season. Therefore, this work aimed to evaluate different phenological metrics extraction methodologies. Using data from over 1500 fields distributed across Brazil’s central area, six algorithms, including CropPhenology, Digital Earth Australia tools package (DEA), greenbrown, phenex, phenofit, and TIMESAT, to extract soybean crop phenology were applied. To understand how robust the algorithms are to different input sources, the NDVI and EVI2 time series derived from MODIS products (MOD13Q1 and MOD09Q1) and from Sentinel-2 satellites were used to estimate the sowing date (SD) and harvest date (HD) in each field. The algorithms produced significantly different phenological date estimates, with Spearman’s R ranging between 0.26 and 0.82 when comparing sowing and harvesting dates. The best estimates were obtained using TIMESAT and phenex for SD and HD, respectively, with R greater than 0.7 and RMSE of 16–17 days. The DEA tools and greenbrown packages showed higher sensitivity when using different data sources. Double cropping is an added challenge, with no method adequately identifying it.

The objective of this work was to calibrate and validate the AquaCrop model for the wheat (Triticum aestivum) crop in the Campos Gerais region, in Southern Brazil. Five cultivars were evaluated in the harvests from 2007 to 2017. The input data for AquaCrop - related to climate, crop, soil, and soil management -, collected in the field, were obtained from the database of Fundação ABC and from the literature. From 35 to 43% of total harvests were selected for calibration, and the remaining, for validation. Calibration was performed for the parameters most sensitive to crop potential yield penalty. The simulated yields were compared with those observed in the field through simple linear regression analysis, root mean square error (RMSE), Pearson’s correlation coefficient (r), the index of agreement (d), and the performance index (c). Calibration showed good results (RMSE ≤ 609.78 kg ha-1; r ≥ 0.72; d ≥ 0.80) for all assessed cultivars and locations, but validation did not have the same performance (c ≤ 0.46). The attempted adjustment, considering the range of calibrated parameters in the harvests, indicated “very good” and “excellent” performances (Supera and Quartzo, respectively) for the cultivars in Castro and “tolerable” to “excellent” in Ponta Grossa.

Crop productivity evaluation with models simulations can help in the prediction of harvests and in the understanding of the interactions resulting from the soil-plant-atmosphere continuum. The aim of this study was to calibrate and validate the AquaCrop model for maize crop in the edaphoclimatic conditions of Campos Gerais region, Paraná State, Brazil. The analyses were carried out for maize crop with model input data (climate, crop, soil and soil management) obtained from the ABC Foundation Experimental Station in Castro, Ponta Grossa and Socavão. The climate in the region is humid subtropical, with rainfall evenly distributed. The relief varies from flat to gently undulating. The period analyzed in the calibration and validation process comprised 2011 to 2016 and 2012 to 2016 harvests, respectively. The data used in the calibration of AquaCrop was different from those used in the validation process. Observed and simulated yields were evaluated by simple linear regression analyses, absolute and relative errors, correlation coefficient (r), concordance (d) and performance (c) indexes. The calibration of AquaCrop was satisfactory in the locations studied for maize crop, obtaining absolute errors varying from 6 to 121 kg ha–1. The highest calibration errors occurred in Castro. However, the errors were not enough to reduce the performance in the validation process for this localitie. The model validation resulted in “excellent” performance in all locations evaluated. The AquaCrop can be used to predict the maize yield with acceptable accuracy in the Campos Gerais Region, Paraná State, Brazil.

RESUMO - O manejo adequado da adubação nitrogenada para atenuar efeitos da perda de área foliar é uma soluçãopouco explorada. Portanto, objetivou-se avaliar, em campo, o efeito da reaplicação de nitrogênio e intensidade dedesfolha em diferentes fases fenológicas sobre a incidência de grãos ardidos e o desempenho produtivo do milho. Odelineamento experimental foi em blocos casualizados, com quatro repetições, em esquema fatorial 2x7x4+2, sendo,a reaplicação de N em cobertura (0 e 40 kg ha-1), os estádios fenológicos de desfolha (V2, V4, V6, V10, R1, R3 e R5),as intensidades de desfolha (25, 50, 75 e 100%) e dois controles adicionais (0% de desfolha com e sem a reaplicaçãode N). As avaliações realizadas foram percentagem de grãos ardidos, massa de 100 grãos e produtividade de grãos. Osdados foram submetidos à análise de variância, testes de Tukey, Dunnett e regressão até 2º grau (p0,05). A reaplicaçãode nitrogênio após a desfolha atenua os efeitos desse estresse na massa e no rendimento total de grãos, com maiorefetividade quando ocorre nos estádios vegetativos. O prejuízo ao desempenho produtivo em razão da desfolha éacentuado quando ocorre no florescimento e enchimento de grãos, pois desequilibra a relação fonte-dreno. A desfolhaem estádios iniciais proporciona maior intensidade de grãos ardidos nas plantas de milho.Palavras-chave: Adubação nitrogenada, Área foliar, Estádios fenológicos, Zea mays L.REAPPLICATION OF NITROGEN AS MITIGATIONTO THE DEFOLIATION EFFECT AT STAGES OF MAIZEABSTRACT - The proper management of nitrogen fertilization to mitigate the effects of the loss of leaf area ispoorly explored. Therefore, the present study evaluated the effect of nitrogen reapplication and defoliation intensity atdifferent phenological stages on the incidence of rot grains and corn production performance. The experimental designwas a randomized complete block with four replications, in a 2x7x4 + 2 factorial scheme, with the reapplication of Ntopdressed (0 and 40 kg ha-1), the defoliation stages (V2, V4, V6, V10, R1, R3 and R5), defoliation intensities (25, 50, 75and 100%) and two additional controls (0% defoliation with and without reapplication of N). Percentage of rot grains,mass of 100 grains and grain yield were evaluated. Data were subjected to analysis of variance, Tukey’s, Dunnett’s testsand regression up to grade 2 (p 0.05). Reapplication of nitrogen after defoliation attenuates the effects of this stress onthe mass and the total yield of grains, with greater effectiveness in the vegetative stages. The damage to the productiveperformance due to defoliation was accentuated when occurred at the flowering and grain filling as it unbalancesthe source-drain relation. Depletion in the early stages caused higher occurrence of grain burned in maize plants.Keywords: Nitrogen fertilization, Leaf area, Phenological stages, Zea mays L.