Journal Article

Occurrence and Seasonal Variations of Aflatoxin M1 in Milk from Punjab, Pakistan

Imran, Muhammad, Salehi, Bahare, Iqbal, Sanaullah, Atif, Muhammad, Martorell, Miquel, Cho, William, Ahmad, Mansur-ud-Din, Nasir, Muhammad, Rashid, Anjum, Naeem, Naureen, Sharifi-Rad, Javad, Akbar, Naveed, Aslam Gondal, Tanweer

2019

Overview

The manifestation of aflatoxins in feed and food is a major issue in the world as its presence leads to some health problems. This study investigates the incidence of aflatoxin M1 (AFM1) contamination in raw milk samples which were collected from Punjab, Pakistan. The Cluster Random Sampling technique was used to collect 960 milk samples from five different regions, and samples were collected every month. The AFM1 level in raw milk was analyzed by the ELISA technique. The findings demonstrate that 70% of samples exceeded the United States permissible maximum residue limits (MRL 0.50 µg/L), with an overall AFM1 level that ranged from 0.3 to 1.0 µg/L. AFM1 contamination varied with the season: The highest average contamination was detected in winter (0.875 µg/L), followed by autumn (0.751 µg/L), spring (0.654 µg/L), and summer (0.455 µg/L). The Eastern region exhibited the highest average AFM1 contamination (0.705 µg/L). Milk samples from the Northern region were found to be widely contaminated, as 86.9% samples exceeded the US MRL, followed by the Eastern region, with 72.3% samples being contaminated with >0.5 µg/L AFM1. The study indicated that the raw milk supply chain was heavily contaminated. Recommendations and remedial measures need to be developed by regulatory authorities to improve the raw milk quality.

• Publisher: MDPI AG,MDPI
• Subject: Aflatoxin M1 / Aflatoxins / afm1 / Agricultural commodities / Autumn / Consumption / Contamination / elisa / Feeds / Food contamination / Food contamination & poisoning / Food supply / Health problems / Milk / pakistan / Random sampling / raw milk / Regulatory agencies / Sampling methods / Seasonal variations / Seasons / Statistical sampling / Supply chains / Variance analysis