Posted on :
4 Nov, 2021
4 Nov, 2021
Sub-Saharan Africa experiences poor soil fertility that suppresses crop yields. The use of fertilizers has therefore been recommended as one of the ways to address this problem of low yield and poor agricultural productivity. Maize fertilizer use in Ghana, for example, is low in general but highly variable with yield responses varying across agroecological zones. Therefore, soil fertility may not be the only culprit for low yields and variability, as climate could be a contributing factor as has been identified in recent studies for Ghana. FERARI is undertaking trials on fertilizer yield response for Maize, Rice and Soybean across agroecological zones in Ghana, which have varying climatic conditions. We, therefore, seek to explore the influence of weather on the potential and water-limited yields of crops by simulating the daily growth and yields using soil and climatic variables.
Job Title: Internship – Crop Growth and Yield Modeling
This student will assess the influence of climate on Maize, Rice and Soybean using the Light Interception and Utilization (LINTUL) crop model to estimate crop growth, potential and water-limited yields. The study area would be FERARI field trial locations for the above listed crops, and the student shall be required to produce a clear methodology for achieving the objectives. In the course of the internship, the student would receive assistance and supervision from the FERARI team.
At the end of the research, the student shall produce a report to FERARI on this research and extract the most important findings in a policy brief. The student would also be assisted to produce a research article that can be published in a scientific journal for our wider international audience.
An MPhil/MSc student in agronomy, plant physiology or related studies. Applicant must have completed his/her course work and ready to start the research component. The applicant must demonstrate high analytical capabilities, be creative, pragmatic and flexible in finding solutions to problem. Preferably, applicant should be knowledgeable in software packages such as (R, STATA and Microsoft Excel) and preferably have command over crop models.
The duration for this assignment shall be seven (7) months. The student is expected to deliver specific activities within the following timeline (student can propose a revision to the timeline).