Theme 5-1: Drought Management and Climate Change--Oral Sessions

Description

Plant growth modeling has been shown an increasing strategy to cope with the high demand for food supply, mainly in climate vulnerable areas, providing them to be used in agriculture worldwide. Concerning semiarid regions, the PHYGROW software has been promising to model plant growth, as cactus forage (‘Opuntia stricta’ cv. “Mexican elephant ear”) which was used in this study. Production data from 2017 and 2018 in Petrolina, Permambuco state, Brazil, with 12 replicates each year were considered. This region shows a very hot and dry climate and has an erratic and seasonal rainfall, which varies a lot in quantity, frequency and intensity from one year to another. After the PHYGROW software parameterization, we performed the generation of the synthetic series and, afterwards, we add the field data to calibration and validation. The results showed a high prediction capacity of PHYGROW software, even in such an erratic climate as Brazilian Semiarid, considering the model performed as calibrated. In 2017 and 2018, the observed cactus forage biomass were 1745 ± 505.83 and 2016 ± 584.58 kg DM ha-1 and the estimated data were 1795 and 2314 kg DM ha-1, respectively. This relatively high deviation suggests an opportunity to add more data, in order to get the model more accurate. Although there was a high difference in precipitation from 2017 to 2018 (166 and 301 mm, respectively), cactus forage was capable to offset this fluctuation, which makes it a strategic resource to reduces the biomass variation and stockpiling necessity on the farm level. This study also demonstrated the importance of modelling to help the farmer to cope with the weather and feed variation in climate vulnerable areas, allowing them to anticipate and adopt strategies to cope with drought more efficiently.

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Cactus Forage Productivity Modelling Using PHYGROW Software in a Semiarid Environment

Plant growth modeling has been shown an increasing strategy to cope with the high demand for food supply, mainly in climate vulnerable areas, providing them to be used in agriculture worldwide. Concerning semiarid regions, the PHYGROW software has been promising to model plant growth, as cactus forage (‘Opuntia stricta’ cv. “Mexican elephant ear”) which was used in this study. Production data from 2017 and 2018 in Petrolina, Permambuco state, Brazil, with 12 replicates each year were considered. This region shows a very hot and dry climate and has an erratic and seasonal rainfall, which varies a lot in quantity, frequency and intensity from one year to another. After the PHYGROW software parameterization, we performed the generation of the synthetic series and, afterwards, we add the field data to calibration and validation. The results showed a high prediction capacity of PHYGROW software, even in such an erratic climate as Brazilian Semiarid, considering the model performed as calibrated. In 2017 and 2018, the observed cactus forage biomass were 1745 ± 505.83 and 2016 ± 584.58 kg DM ha-1 and the estimated data were 1795 and 2314 kg DM ha-1, respectively. This relatively high deviation suggests an opportunity to add more data, in order to get the model more accurate. Although there was a high difference in precipitation from 2017 to 2018 (166 and 301 mm, respectively), cactus forage was capable to offset this fluctuation, which makes it a strategic resource to reduces the biomass variation and stockpiling necessity on the farm level. This study also demonstrated the importance of modelling to help the farmer to cope with the weather and feed variation in climate vulnerable areas, allowing them to anticipate and adopt strategies to cope with drought more efficiently.