Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = -0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d-¹ for 12 fields analyzed and NSE values 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and -0.0013, respectively. SAFER performed well for ET estimation after calibration, with r² and NSE values equal to 0.91 and RMSD = 0.469 mm d-¹. SAFER also showed good performance (r² = 0.86) after validation, with the lowest RMSD (0.58 mm d-¹) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.(AU)

Evapotranspiration mapping of commercial corn fields in Brazil using SAFER algorithm

SAFER (Simple Algorithm for Evapotranspiration Retrieving) is a relatively new algorithm applied successfully to estimate actual crop evapotranspiration (ET) at different spatial scales of different crops in Brazil. However, its use for monitoring irrigated crops is scarce and needs further investigation. This study assessed the performance of SAFER to estimate ET of irrigated corn in a Brazilian semiarid region. The study was conducted in São Desidério, Bahia State, Brazil, in corn-cropped areas in no-tillage systems and irrigated by central pivots. SAFER algorithm with original regression coefficients (a = 1.8 and b = -0.008) was initially tested during the growing seasons of 2014, 2015, and 2016. SAFER performed very poorly for estimating corn ET, with RMSD values greater than 1.18 mm d-¹ for 12 fields analyzed and NSE values 0 in most fields. To improve estimates, SAFER regression coefficients were calibrated (using 2014 and 2015 data) and validated with 2016 data, with the resulting coefficients a and b equal to 0.32 and -0.0013, respectively. SAFER performed well for ET estimation after calibration, with r² and NSE values equal to 0.91 and RMSD = 0.469 mm d-¹. SAFER also showed good performance (r² = 0.86) after validation, with the lowest RMSD (0.58 mm d-¹) values for the set of 14 center pivots in this growing season. The results support the use of calibrated SAFER algorithm as a tool for estimating water consumption in irrigated corn fields in semiarid conditions.

Leaf development stages and ontogenetic changes in passionfruit (Passiflora edulis Sims.) are detected by narrowband spectral signal.

During shoot development, leaves undergo various ontogenetic changes, including variation in size, shape, and geometry. Passiflora edulis (passionfruit) is a heteroblastic species, which means that it experiences conspicuous changes throughout development, enabling a morphological distinction between the juvenile and adult vegetative phases. Quantification of heteroblasty requires a practical, inexpensive, reliable, and non-destructive method, such as remote sensing. Moreover, relationships among ontogenetic changes and spectral signal at leaf level can be scaled up to support precision agriculture in passion fruit crops. In the present study, we used laboratory spectroscopic measurements (400-2500 nm) and narrowband vegetation indexes (or hyperspectral vegetation indexes - HVIs) to evaluate ontogenetic changes related to development and aging in P. edulis leaves. We also assessed leaf pigment concentration to further support the application of biochemical-related narrowband indexes. We report that 30-d-old leaves can be discriminated into developmental stages through their spectral signals. MSI (Moisture Stress Index) and NDVI750 (Normalized Difference Vegetation Index ρ750) contribute most to the variation of age (15 to 30-d-old leaves) and developmental stage (phytomer positions along the plant axis) in passionfruit leaves. PRI (Photochemical Reflectance Index) played an important role in detecting age and development alterations, including heteroblasty. A biochemical and spectral comparison of pigments revealed that spectroscopy offered potential for diagnosing phenology in P. edulis, as some narrowband indexes correlated strongly with chlorophylls and carotenoids content. Narrowband vegetation indexes are found to be a suitable tool for monitoring passionfruit crops.