Measuring Maize (Zea mays L.) Genetic Coefficients for Modeling Water-Limited Potential Yield and Yield Gaps in the Wami-Ruvu River Basin, Tanzania: An Overview

Abstract: 
This research establishes observed data for validating an artificial neural network model for estimating the cultivar coefficients for the popular maize varieties in Tanzania. The genetic coefficients are fundamental in calibrating the DSSAT crop system model for estimating potential yield and yield gap under rain fed conditions. Leaf area index, plant height, aboveground biomass and grain growth rate varied significantly among the maize varieties. This paper summarizes the obtained results.
Cette recherche établit les données observées pour valider un modèle de réseau neural artificiel afin d’estimer les coefficients de cultivars pour les variétés de maïs populaires en Tanzanie. Les coefficients génétiques sont fondamentaux pour calibrer le modèle de système cultural DSSAT afin d’estimer le rendement potentiel et l’écart de rendement dans les conditions pluviales. L’indice de la surface foliaire, la hauteur des plantes, la biomasse au-dessus du sol et le taux de croissance des grains ont varié significativement pour les variétés de maïs. Le présent article résume les résultats obtenus.
Language: 
Extended abstracts submitted under Integrated Crop Management
Date of publication: 
2012
Country: 
Region Focus: 
East Africa
Collection: 
RUFORUM Conferences and Workshops
Licence conditions: 
Open Access
Access restriction: 
Form: 
Printed resource
Publisher: 
Notes: 

The 2012 RUFORUM Biennial Conference is the third in the series. The main objective of the Biennial conferences is to provide a platform for agricultural research for development stakeholders in Africa and beyond to actively exchange findings and experiences, while at the same time learning lessons towards improving performance of the agricultural sector and ultimately people’s livelihoods. The biennial conference is RUFORUM’s most comprehensive meeting for the diversity of stakeholers in agriculture. It is especially dedicated to graduate students and their supervisors, grantees in RUFORUM member universities and alumni. It is a platform for peer review, quality control, mentorship, networking and shared learning. The third Biennial Conference was attended by 657 participants.This record contains an extended abstract accepted under the theme of Integrated Crop Management