Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions
The dataset contains six datasheets with different types of data i.e., cropping system physiological characteristics, gross margins, soil nutrient characterization, seasonal physical conditions of the soil, soil water infiltration and seasonal weather conditions. The data will be helpful in assessin...
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| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
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Bioversity International and the International Center for Tropical Agriculture
2021
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| Acceso en línea: | https://hdl.handle.net/10568/116633 |
| _version_ | 1855529877538603008 |
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| author | Alliance of Bioversity International and CIAT |
| author_browse | Alliance of Bioversity International and CIAT |
| author_facet | Alliance of Bioversity International and CIAT |
| author_sort | Alliance of Bioversity International and CIAT |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | The dataset contains six datasheets with different types of data i.e., cropping system physiological characteristics, gross margins, soil nutrient characterization, seasonal physical conditions of the soil, soil water infiltration and seasonal weather conditions. The data will be helpful in assessing how the different Climate Smart Agricultural practices (CSA) affect crop physiological characteristics, yield, and soil physical attributes.
The cropping system physiological characteristic datasheet contains data on maize leaf chlorophyll measurements using SPAD and soil moisture and temperature reading using time domain reflectometry.
The gross margin datasheet contains data on yields of the different plant (maize, beans and pigeon pea) components (grain, stover, maize toppings, haulms, stalks and husks). The different components were converted into gross revenue using the farm gate prices of each parameter.
The soil nutrient characterization datasheet contains data on soil nutrient content at 0-20 cm depth which was sampled at block level during planting.
The seasonal physical conditions of soil datasheet has data on daily soil physical conditions i.e., soil moisture, temperatures and bulk electrical conductivity during the cropping season. This data was measured at a meteorological station located in the low altitude-low rainfall eco-zone of Babati.
The soil water infiltration datasheet indicates the rate of water infiltrating under two suctions i.e., -2 cm sec2 and -6 cm sec2 using mini-disc infiltrometer at field level.
The seasonal weather condition indicates daily weather data collected in three agro-ecological conditions of Babati during the 2019 long rain season. |
| format | Conjunto de datos |
| id | CGSpace116633 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | Bioversity International and the International Center for Tropical Agriculture |
| publisherStr | Bioversity International and the International Center for Tropical Agriculture |
| record_format | dspace |
| spelling | CGSpace1166332025-12-08T10:29:22Z Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions Alliance of Bioversity International and CIAT climate-smart agriculture farming systems cropping systems soil water movement soil fertility agricultural productivity crop yield weather agricultura climáticamente inteligente sistemas de explotación sistemas de cultivo movimiento del agua en el suelo fertilidad del suelo productividad agrícola The dataset contains six datasheets with different types of data i.e., cropping system physiological characteristics, gross margins, soil nutrient characterization, seasonal physical conditions of the soil, soil water infiltration and seasonal weather conditions. The data will be helpful in assessing how the different Climate Smart Agricultural practices (CSA) affect crop physiological characteristics, yield, and soil physical attributes. The cropping system physiological characteristic datasheet contains data on maize leaf chlorophyll measurements using SPAD and soil moisture and temperature reading using time domain reflectometry. The gross margin datasheet contains data on yields of the different plant (maize, beans and pigeon pea) components (grain, stover, maize toppings, haulms, stalks and husks). The different components were converted into gross revenue using the farm gate prices of each parameter. The soil nutrient characterization datasheet contains data on soil nutrient content at 0-20 cm depth which was sampled at block level during planting. The seasonal physical conditions of soil datasheet has data on daily soil physical conditions i.e., soil moisture, temperatures and bulk electrical conductivity during the cropping season. This data was measured at a meteorological station located in the low altitude-low rainfall eco-zone of Babati. The soil water infiltration datasheet indicates the rate of water infiltrating under two suctions i.e., -2 cm sec2 and -6 cm sec2 using mini-disc infiltrometer at field level. The seasonal weather condition indicates daily weather data collected in three agro-ecological conditions of Babati during the 2019 long rain season. 2021-11 2021-12-09T15:49:58Z 2021-12-09T15:49:58Z Dataset https://hdl.handle.net/10568/116633 en Open Access image/jpeg Bioversity International and the International Center for Tropical Agriculture Alliance of Bioversity and International Center for Tropical Agriculture (2021) Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions. https://doi.org/10.7910/DVN/M0XCES, Harvard Dataverse, V1, UNF:6:C1fr736AnTRJyUW6zMKGsQ== [fileUNF] |
| spellingShingle | climate-smart agriculture farming systems cropping systems soil water movement soil fertility agricultural productivity crop yield weather agricultura climáticamente inteligente sistemas de explotación sistemas de cultivo movimiento del agua en el suelo fertilidad del suelo productividad agrícola Alliance of Bioversity International and CIAT Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title | Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title_full | Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title_fullStr | Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title_full_unstemmed | Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title_short | Test climate-smart farming practices for increasing productivity of maize-legume system under variable weather conditions |
| title_sort | test climate smart farming practices for increasing productivity of maize legume system under variable weather conditions |
| topic | climate-smart agriculture farming systems cropping systems soil water movement soil fertility agricultural productivity crop yield weather agricultura climáticamente inteligente sistemas de explotación sistemas de cultivo movimiento del agua en el suelo fertilidad del suelo productividad agrícola |
| url | https://hdl.handle.net/10568/116633 |
| work_keys_str_mv | AT allianceofbioversityinternationalandciat testclimatesmartfarmingpracticesforincreasingproductivityofmaizelegumesystemundervariableweatherconditions |