Abstract

World climate is projected to be more harmful and unforeseeable. A threefold combination of temperature, precipitation and potential evapotranspiration leads to climate change with a negative effect on staple food crop production. To understand the sensitivity of staple food crop yield to future change in climate, this paper uses the feasible generalized least square (FGLS) and heteroskedasticity and autocorrelation (HAC) consistent standard error techniques function to quantify the effects of climate variables on the mean and variance of crop yields. Data from FAOSTAT website and national institutions such as temperature, precipitation and crop areas cultivated for period 1961-2015 for Benin country are used. Climate variables are computed according to each crop growing season. The results showed that climate change could significantly influence the mean crop yields and could significantly affect the crop yield variability. The contribution of climate variables to crop yield varies across staple crop yields and they were predicted to decrease about 2025. In order to ensure food availability in the context of climate change, support to agricultural sector and especially to staple food crops production should be focused on seeds improvement by generating, developing and extending drought and flood-tolerant varieties. The results also implicate the promoting of irrigated agriculture.

Highlights

  • Crop production and crop yield in particular are controlled by the combination of climate factors, soil fertility, land use decisions, agricultural practices through innovative use of tools, and access and utilization of high yielding varieties among other factors (Kulcharik & Serbin, 2008; Epule & Bryant, 2015)

  • Apart from non-climate factors such as demographic pressure, fertility degree, technological progress, plant management, and insect, disease and weeds management that affect crop yields, there is no ambiguity that temperature and precipitation constitute the important climate factors which determine crop yields, in agricultural rain-fed system

  • This study develops the feasible generalized least square (FGLS) and heteroskedasticity and autocorrelation (HAC) model to estimate stochastic production functions and determine the effects of temperature and precipitation on mean and variability of maize, rice, cowpea, sorghum, cassava, and yam yields in Benin

Read more

Summary

Introduction

Crop production and crop yield in particular are controlled by the combination of climate factors, soil fertility, land use decisions, agricultural practices through innovative use of tools, and access and utilization of high yielding varieties among other factors (Kulcharik & Serbin, 2008; Epule & Bryant, 2015). Everywhere in the world, plants, animals, and ecosystems are adapted to the prevailing climate conditions (FAO, 2008) For these reasons, it does not matter whether climate conditions change, even slightly, even in favor of life growing, plants and animals are impacted, some of them become less productive, or even disappear. Considering Emaziye’s (2015) point of view, crop production requires optimum conditions during crop growing for maximum yields, where an excess or a deficit in temperature and/or precipitation results in poor harvests and even total losses. This exactly applies in Benin according to Hounnou and Dedehouanou (2018). Climate change is considered to have direct jas.ccsenet.org

Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call