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        <dc:title>Exploring aflatoxin contamination and household-level exposure risk in diverse Indian food systems</dc:title>
        <dc:creator>Audenaert, K</dc:creator>
        <dc:creator>Wenndt, A</dc:creator>
        <dc:creator>Sudini, H K</dc:creator>
        <dc:creator>Pingali, P</dc:creator>
        <dc:creator>Nelson, R</dc:creator>
        <dc:subject>Aflatoxins</dc:subject>
        <dc:description>The present study sought to identify household risk factors associated with aflatoxin contamination&#13;
within and across diverse Indian food systems and to evaluate their utility in risk&#13;
modeling. Samples (n = 595) of cereals, pulses, and oil seeds were collected from 160&#13;
households across four diverse districts of India and analyzed for aflatoxin B1 using&#13;
enzyme-linked immunosorbent assay (ELISA). Demographic information, food and cropping&#13;
systems, food management behaviors, and storage environments were profiled for&#13;
each household. An aflatoxin detection risk index was developed based on household-level&#13;
features and validated using a repeated 5-fold cross-validation approach. Across districts,&#13;
between 30–80% of households yielded at least one contaminated sample. Aflatoxin B1&#13;
detection rates and mean contamination levels were highest in groundnut and maize,&#13;
respectively, and lower in other crops. Landholding had a positive univariate effect on&#13;
household aflatoxin detection, while storage conditions, product source, and the number of&#13;
protective behaviors used by households did not show significant effects. Presence of&#13;
groundnut, post-harvest grain washing, use of sack-based storage systems, and cultivation&#13;
status (farming or non-farming) were identified as the most contributive variables in stepwise&#13;
logistic regression and were used to generate a household-level risk index. The index had&#13;
moderate classification accuracy (68% sensitivity and 62% specificity) and significantly correlated&#13;
with village-wise aflatoxin detection rates. Spatial analysis revealed utility of the&#13;
index for identifying at-risk localities and households. This study identified several key features&#13;
associated with aflatoxin contamination in Indian food systems and demonstrated that&#13;
household characteristics are substantially predictive of aflatoxin risk.</dc:description>
        <dc:publisher>Public Library of Science</dc:publisher>
        <dc:date>2020-10</dc:date>
        <dc:type>Article</dc:type>
        <dc:type>PeerReviewed</dc:type>
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        <dc:language>en</dc:language>
        <dc:identifier>http://oar.icrisat.org/11681/1/pone.0240565.pdf</dc:identifier>
        <dc:identifier>  Audenaert, K and Wenndt, A and Sudini, H K and Pingali, P and Nelson, R  (2020) Exploring aflatoxin contamination and household-level exposure risk in diverse Indian food systems.  PLOS ONE (TSI), 15 (10).  pp. 1-29.  ISSN 1932-6203     </dc:identifier>
        <dc:relation>https://doi.org/10.1371/journal.pone.0240565</dc:relation>
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