An evaluation of uptake and developmental impact in the semi-arid tropics of four crop production models

Citation
E. Kebreab et al., An evaluation of uptake and developmental impact in the semi-arid tropics of four crop production models, J AGR SCI, 134, 2000, pp. 173-180
Citations number
26
Categorie Soggetti
Agriculture/Agronomy
Journal title
JOURNAL OF AGRICULTURAL SCIENCE
ISSN journal
00218596 → ACNP
Volume
134
Year of publication
2000
Part
2
Pages
173 - 180
Database
ISI
SICI code
0021-8596(200003)134:<173:AEOUAD>2.0.ZU;2-N
Abstract
In the last two decades, crop production models have been developed or modi fied for use in the semiarid tropics. Although potential uses of crop model s have been discussed in detail in the literature, examples of successful u ptake and impact of those models is lacking. Four models developed specific ally for the semi-arid tropics were used as a basis for evaluating uptake a nd impact of models in the semi-arid tropics. PARCH accounts for difference s in water availability when predicting yield. PARCHED-THIRST covers water- harvesting, run-off and run-on. EMERGE identifies opportunities for success ful crop establishment, and SWEAT calculates evapo-transpiration and estima tes temperature and moisture throughout the soil profile. The models are dy namic, deterministic and mechanistic in nature. The equations and notations comprising them are generally well structured, meaningful and concise. The uptake and impact of these models on crop production in the semi-arid trop ics was assessed using questionnaires and semi-structured interviews with t he model developers. There was limited uptake. Low uptake resulted from lac k of efficient dissemination and discontinuity in information transfer: fro m model developers to scientists in the national research institutions; and thereon to extension agents and so to farmers. Although this paper is base d on a study of only four models, there are important lessons to be drawn i n order to avoid similar mistakes being repeated. Guidelines for improving impact for future crop production modelling projects are proposed.