Articles
Modelling the productivity of underutilised crops for climate resilience
Article number
1101_17
Pages
113 – 118
Language
English
Abstract
Current agriculture depends on a few LSQUOmajorRSQUO species grown as monocultures that are supported by global research and development systems underpinning the current productivity with quantitative evidences.
Whereas many hundreds of LSQUOunderutilisedRSQUO crops have no such support systems but knowledge about them is fragmentary and based on the qualitative local evidences of the growers themselves rather than multi-locational research.
Farmers in developing parts of the world have traditionally used indigenous knowledge to cope with climate hazards based upon observations and interpretation of natural phenomena.
Crop choices, crop mixes and seasonal cropping calendars are largely based on farmer-level local forecasts.
Since climate change is characterized mainly by uncertainty, it is vital to assess the crops and system resilience by means of underutilised crops.
These neglected crops have the potential to meet real world challenges by means of sustaining humanity, diversifying the agricultural systems and especially responding to climate change with climate-resilient characters.The main analysis engine of the present study involves crop-climate modelling that introduces specific underutilised crops into recognised crop models (APSIM, DSSAT, AquaCrop) and links available climate databases within a geospatial information system framework.
The preliminary use-cases on bambara groundnut (an African legume) evaluated the yield, total biomass and water productivity under the following scenarios: (i) Baseline, (ii) 5 Global Climate Models (CCSM4, GFDLESM2M, HadGEM2-ES, MIROC5, MPI-ESM-MR) with high emission scenario for mid-century, and (iii) for 99 climate sensitivities (C3MP). Productivity simulations for contrasting African locations demonstrated that interrogation methods can be devised for genetically distinct materials from matched climatic conditions to predict optimal selections of parental germplasm suited to different geographical locations for climate resilience.
Whereas many hundreds of LSQUOunderutilisedRSQUO crops have no such support systems but knowledge about them is fragmentary and based on the qualitative local evidences of the growers themselves rather than multi-locational research.
Farmers in developing parts of the world have traditionally used indigenous knowledge to cope with climate hazards based upon observations and interpretation of natural phenomena.
Crop choices, crop mixes and seasonal cropping calendars are largely based on farmer-level local forecasts.
Since climate change is characterized mainly by uncertainty, it is vital to assess the crops and system resilience by means of underutilised crops.
These neglected crops have the potential to meet real world challenges by means of sustaining humanity, diversifying the agricultural systems and especially responding to climate change with climate-resilient characters.The main analysis engine of the present study involves crop-climate modelling that introduces specific underutilised crops into recognised crop models (APSIM, DSSAT, AquaCrop) and links available climate databases within a geospatial information system framework.
The preliminary use-cases on bambara groundnut (an African legume) evaluated the yield, total biomass and water productivity under the following scenarios: (i) Baseline, (ii) 5 Global Climate Models (CCSM4, GFDLESM2M, HadGEM2-ES, MIROC5, MPI-ESM-MR) with high emission scenario for mid-century, and (iii) for 99 climate sensitivities (C3MP). Productivity simulations for contrasting African locations demonstrated that interrogation methods can be devised for genetically distinct materials from matched climatic conditions to predict optimal selections of parental germplasm suited to different geographical locations for climate resilience.
Authors
A.S. Karunaratne, S.N. Azam-Ali, S. Walker, A. Ruane
Keywords
crop model, sensitivity, yield, landraces
Online Articles (31)