TY  - JOUR
AV  - public
A1  - Hendrix, M C
A1  - Obed, I L
A1  - Alice, M M
A1  - Elijah, P
A1  - Jones, Y
A1  - Njoroge, S M C
A1  - Rick, L B
A1  - David, J
TI  - Predicting aflatoxin content in peanuts using ambient temperature, soil temperature and soil moisture content during pod development
UR  - https://doi.org/10.5897/AJPS2018.1742
JF  - African Journal of Plant Science
SN  - 1996-0824
PB  - Academic Journals
N1  - This study was mainly funded by the Peanut and
Mycotoxin Innovation Laboratory under the Southern
African Value Chain Project through the U.S. Agency for
International Development, under the terms of Award No.
AID-ECG-A-00-07-0001 to The University of Georgia as
the management entity for the U.S. Feed the Future
Innovation Lab on Peanut Productivity and Mycotoxin
Control. Partial funding from the University of Zambia,
Directorate of Research and Graduate Studies under the
2017/18 Research Seed Money Award to Mr. Hendrix
Chalwe facilitated field experiments conducted in the
2017/2018 cropping season.
N2  - Higher than acceptable aflatoxin levels in peanut kernels (Arachis hypogaea L.) and related products is
a worldwide food safety concern. Strict regulatory standards by major importers of peanuts limit the
marketability of peanuts for many developing tropical countries including Zambia. The incidence of preharvest
aflatoxins is strongly linked to soil and weather conditions during pod-development. This study
aimed to formulate statistical models to predict total aflatoxin content in peanut kernels using selected
environmental factors during pod development. Field experiments were conducted for two years during
which the peanut crop was exposed to 84 combinations of ambient temperature, soil temperature and
soil moisture content measured during the last 30 days of pod development. These data were used to
formulate regression models to predict total aflatoxin content in peanut kernels. Simple linear
regression models had R2 values of 0.30 for maximum ambient temperature, 0.24 for soil temperature
and 0.38 for soil moisture content. Combining soil moisture content and soil temperature in a
multivariate regression model could explain 54% of the variation in total aflatoxin content while a
combination of soil moisture content and maximum ambient temperature could only explain 46% of the
variation in total aflatoxin content.
KW  - Aflatoxin
KW  -  Groundnut
KW  -  Linear regression
KW  -  Statistical model
KW  -  Zambia
Y1  - 2019/03//
SP  - 59
ID  - icrisat11390
EP  - 69
VL  - 13
IS  - 3
ER  -