Path Analysis of Corn Kernel Physical Properties as Quality Indicators of Poultry Feed Ingredients

This study aimed to identify and analyze the relationships among the physical properties of corn kernels and their impact on quality as a poultry feed ingredient using a Path Analysis approach.Five physical parameters, namely moisture content (MC), damaged kernel (DK), moldy kernel (MK), broken kernel (BK), and foreign material (FM), were evaluated in accordance with the Indonesian National Standard (SNI).Samples were taken directly from each truck that had just been received by the industry, as many as 266 trucks at different times.The sampling technique employed a stratified method based on the position of the sack in the truck, specifically the top, middle, and bottom.Each sampling point produced samples weighing approximately 100g, so the total weight of the sample per sack was approximately 300 grams.Path Analysis results revealed that moldy kernel (MK) and damaged kernel (DK) were the primary factors degrading corn kernel quality, with total effects of =-0.510 and =-0.402,respectively (P<0.001).MK significantly contributed to the risk of mycotoxin contamination, while DK increased susceptibility to physical and nutritional deterioration during storage.The model also uncovered significant indirect effects, where MC and BK mediated the impact of DK on quality, indicating that mechanical damage indirectly accelerates quality degradation through increased moisture retention and kernel breakage.However, the relationship between MC and MK was found to be non-significant (P=0.619),suggesting that factors such as storage temperature and ventilation have a greater influence on fungal growth than moisture content alone.Challenges related to postharvest mechanization, moisture management, and contamination control at the farm level remain critical barriers to maintaining corn quality.Therefore, improving corn quality for poultry feed applications requires an integrated strategy that includes optimizing harvest and postharvest mechanization, enhancing storage environment management, and implementing effective cleaning and sorting processes.