Publications by authors named "Everardo Chartuni Mantovani"

4 Publications

  • Page 1 of 1

Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing.

PLoS One 2021 9;16(2):e0245834. Epub 2021 Feb 9.

Agricultural Engineering Department, Federal University of Viçosa (UFV), Viçosa, Minas Gerais, Brazil.

Reference evapotranspiration (ETo) is a fundamental parameter for hydrological studies and irrigation management. The Penman-Monteith method is the standard to estimate ETo and requires several meteorological elements. In developing countries, the number of weather stations is insufficient. Thus, free products of remote sensing with evapotranspiration information must be used for this purpose. In this context, the objective of this study was to estimate monthly ETo from potential evapotranspiration (PET) made available by MOD16 product. In this study, the monthly ETo estimated by Penman-Monteith method was considered as the standard. For this, data from 265 weather station of the National Institute of Meteorology (INMET), spread all over the Brazilian territory, were acquired for the period from 2000 to 2014 (15 years). For these months, monthly PET values from MOD16 product for all Brazil were also downloaded. By using machine learning algorithms and information from WorldClim as covariates, ETo was estimated through images from the MOD16 product. To perform the modeling of ETo, eight regression algorithms were tested: multiple linear regression; random forest; cubist; partial least squares; principal components regression; adaptive forward-backward greedy; generalized boosted regression and generalized linear model by likelihood-based boosting. Data from 2000 to 2012 (13 years) were used for training and data of 2013 and 2014 (2 years) were used to test the models. The PET made available by the MOD16 product showed higher values than those of ETo for different periods and climatic regions of Brazil. However, the MOD16 product showed good correlation with ETo, indicating that it can be used in ETo estimation. All models of machine learning were effective in improving the performance of the metrics evaluated. Cubist was the model that presented the best metrics for r2 (0.91), NSE (0.90) and nRMSE (8.54%) and should be preferred for ETo prediction. MOD16 product is recommended to be used to predict monthly ETo, which opens possibilities for its use in several other studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0245834PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7872264PMC
July 2021

Impact of drought associated with high temperatures on Coffea canephora plantations: a case study in Espírito Santo State, Brazil.

Sci Rep 2020 11 12;10(1):19719. Epub 2020 Nov 12.

Biology Department, Federal University of Espírito Santo (UFES), Alegre, 29500-000, Brazil.

Droughts are major natural disasters that affect many parts of the world all years and recently affected one of the major conilon coffee-producing regions of the world in state of Espírito Santo, which caused a huge crisis in the sector. Therefore, the objective of this study was to conduct an analysis with technical-scientific basis of the real impact of drought associated with high temperatures and irradiances on the conilon coffee (Coffea canephora Pierre ex Froehner) plantations located in the north, northwest, and northeast regions of the state of Espírito Santo, Brazil. Data from 2010 to 2016 of rainfall, air temperature, production, yield, planted area and surface remote sensing were obtained from different sources, statistically analyzed, and correlated. The 2015/2016 season was the most affected by the drought and high temperatures (mean annual above 26 °C) because, in addition to the adverse weather conditions, coffee plants were already damaged by the climatic conditions of the previous season. The increase in air temperature has higher impact (negative) on production than the decrease in annual precipitation. The average annual air temperatures in the two harvest seasons that stood out for the lowest yields (i.e. 2012/2013 and 2015/2016) were approximately 1 °C higher than in the previous seasons. In addition, in the 2015/2016 season, the average annual air temperature was the highest in the entire series. The spatial and temporal distribution of Enhanced Vegetation Index values enabled the detection and perception of droughts in the conilon coffee-producing regions of Espírito Santo. The rainfall volume accumulated in the periods from September to December and from April to August are the ones that most affect coffee yield. The conilon coffee plantations in these regions are susceptible to new climate extremes, as they continue to be managed under irrigation and full sun. The adoption of agroforestry systems and construction of small reservoirs can be useful to alleviate these climate effects, reducing the risk of coffee production losses and contributing to the sustainability of crops in Espírito Santo.
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http://dx.doi.org/10.1038/s41598-020-76713-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665182PMC
November 2020

Mapping within‑field variability of soybean evapotranspiration and crop coefficient using the Earth Engine Evaporation Flux (EEFlux) application.

PLoS One 2020 9;15(7):e0235620. Epub 2020 Jul 9.

Department of Agricultural Engineering, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.

Accurate information about the spatiotemporal variability of actual crop evapotranspiration (ETa), crop coefficient (Kc) and water productivity (WP) is crucial for water efficient management in the agriculture. The Earth Engine Evapotranspiration Flux (EEFlux) application has become a popular approach for providing spatiotemporal information on ETa and Kc worldwide. The aim of this study was to quantify the variability of water consumption (ETa) and the Kc for an irrigated commercial planting of soybeans based on the EEFlux application in the western region of the state of Bahia, Brazil. The water productivity (WP) for the fields was also obtained. Six cloud-free images from Landsat 7 and 8 satellites, acquired during the 2016/17 soybean growing season were used and processed on the EEFlux platform. The ETa from EEFlux was compared to that of the modified FAO (MFAO) approach using the following statistical metrics: Willmot's index of agreement (d-index), root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE). The Kc from EEFlux was compared to the Kc used in the soybean field (Kc FAO-based) and to the Kc values obtained in different scientific studies using the d-index. A similar procedure was performed for WP. Our results reveal that EEFlux is able to provide accurate information about the variability of ETa and the Kc of soybean fields. The comparison between ETa EEFlux and ETa MFAO showed good agreement based on the d-index, with values of 0.85, 0.83 and 0.89 for central pivots 1, 2 and 3, respectively. However, EEFlux tends to slightly underestimate ETa. The Kc EEFlux showed good accordance with the Kc values considered in this study, except in phase II, where a larger difference was observed; the average WP of the three fields (1.14 kg m-3) was higher than that in the majority of the previous studies, which is a strong indicator of the efficient use of water in the studied soybean fields. The study showed that EEFlux, an innovative and free tool for access spatiotemporal variability of ETa and Kc at global scale is very efficient to estimate the ETa and Kc on different growth stages of soybean crop.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0235620PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7347170PMC
September 2020

Agronomic performance of lettuce cultivars submitted to different irrigation depths.

PLoS One 2019 11;14(12):e0224264. Epub 2019 Dec 11.

Department of Phytotechnics, Center of Agricultural Sciences, Federal University of Viçosa, Viçosa-MG, Brazil.

The use of cultivars adapted to the climate and soil conditions associated with adequate irrigation supply maximizes lettuce agronomic performance. The aim of this work was to evaluate the agronomic performance of four lettuce cultivars submitted to five different drip irrigation depths under a protected environment in Viçosa-MG, Brazil. A randomized block design was applied in a split plot scheme with four replications, and several agronomic characteristics were evaluated by analysis of variance, Tukey range tests, regression and principal component analysis. A higher chlorophyll concentration in the Raider Plus cultivar promoted the production of more leaves, leading to a higher phytomass. The Luara cultivar presented a higher number of commercial leaves per plant than the other cultivars, regardless of the irrigation depth, reflected in a larger diameter and volume of the aerial part of the plants. The Raider Plus and Luara cultivars presented better root development than that of the other cultivars, reducing the effect of plant water stress even under lower irrigation depth conditions. Although higher water productivity (WP) was observed for the lowest irrigation depth (50% of ETc), important variables reached the maximum values at depths higher than 100% water replenishment. Therefore, Raider Plus and Luara cultivars with an irrigation depth of 110% of crop evapotranspiration provided better commercial lettuce quality and are recommended for lettuce cultivation in the research region and under conditions similar to those of the present study.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0224264PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6905512PMC
March 2020
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