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| Cova,Alide M. W.; Freitas,Fabio T. O. de; Viana,Paula C.; Rafael,Maria R. S.; Azevedo Neto,André D. de; Soares,Tales M.. |
| ABSTRACT The objective of this study was to evaluate the growth and accumulation of ions in lettuce grown in different hydroponic systems and recirculation frequencies. The experimental design was randomized blocks with 8 treatments and 4 replicates. The evaluated hydroponic systems were Nutrient Flow Technique (NFT) and an adapted Deep Flow Technique (DFT), the latter with recirculation frequencies of 0.25, 2 and 4 h. Both systems used fresh water and brackish water. Plant growth, accumulation of inorganic solutes (Na+, K+, Cl- and NO3-) and the correlation between dry matter production and Na+/K+ and Cl-/NO3- were evaluated. The salinity of the water used to prepare the nutrient solution caused decrease in growth and K+ and NO3- levels, and increased... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Soilless cultivation; Lactuca sativa; Salinity; NFT and DFT systems. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000300150 |
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| Lima,João G. A.; Sánchez,Juan M.; Piqueras,José G.; Espínola Sobrinho,José; Viana,Paula C.; Alves,Aline da S.. |
| ABSTRACT The estimate of the actual surface evapotranspiration (ET) contributes to quantifying the water needs of crops. An alternative to the use of lysimeter for an accurate estimation of water needs, which has proved to be of great value in recent years, is the use of remote sensing combined with models based on surface energy balance. There is wide variety of models that can be classified into two types: one-source models, such as the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC) algorithm, or two-source models, such as the Simplified Two-Source Energy Balance (STSEB). The objective of this study was to analyze how METRIC and STSEB can be used to estimate ET, in comparison with the lysimeter data, for the... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Sorghum bicolor; Irrigation management; Remote sensing; Irrigation. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662020000100024 |
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