Newcastle viral disease causation web correlations with laying hen productivity.

Environmental conditions profoundly impact the health, welfare, and productivity of laying hens in commercial poultry farming. We investigated the association between microclimate variations, production indices, and histopathological responses to accidental Newcastle disease virus (NDV) infection within a controlled closed-house system. The study was conducted over seven months in a laying hen facility in Cairo, Egypt. Microclimate measurements included temperature, relative humidity (RH%), air velocity (AV), and the temperature humidity index (THI) that were obtained from specific locations on the front and back sides of the facility. Productivity indices, including the egg production percentage (EPP), egg weight (EW), average daily feed intake, and feed conversion ratio, were assessed monthly. During an NDV outbreak, humoral immune responses, gross pathology, and histopathological changes were evaluated. The results demonstrated significant (p < 0.05) variations in EPP and EW between the front and back sides except in April and May. AV had a significant (p = 0.006) positive effect (Beta = 0.346) on EW on the front side. On the back side, AV had a significant (p = 0.001) positive effect (Beta = 0.474) on EW, while it negatively influenced (p = 0.027) EPP (Beta = - 0.281). However, temperature, RH%, and THI had no impact and could not serve as predictors for EPP or EW on either farm side. The humoral immune response to NDV was consistent across microclimates, highlighting the resilience of hens. Histopathological examination revealed characteristic NDV-associated lesions, with no significant differences between the microclimates. This study underscores the significance of optimizing microclimate conditions to enhance laying performance by providing tailored environmental management strategies based on seasonal variations, ensuring consistent airflow, particularly near cooling pads and exhaust fans, and reinforcing the importance of biosecurity measures under field challenges with continuous monitoring and adjustment.

From source to house: unraveling the seasonal effect of water distribution system on drinking water quality of poultry farms under Egyptian environmental condition.

Improvements in drinking water quality (DWQ) can lead, according to some estimates, to a 10% reduction of the world's disease load. The drinking water distribution system (DWDS) plays a crucial role in influencing DWQ and can contribute to the emergence of poultry-related epidemics. This study aims to monitor the variations in DWQ throughout the seasons within the DWDS of Egyptian poultry farms experiencing epidemics. The study assessed DWQ at four different points along the DWDS, including the water source (WS), water tank (WT), broiler drinker (BD), and layer drinker (LD), across 86 farms. Statistical analysis was employed to establish correlations between DWQ and the sampling points within the DWDS, as well as between water temperature (Tw.C°), ambient temperature (Ta.C°), and microbial DWQ. The survey revealed significant differences between Tw.C° and Ta.C°, with notable effect sizes (d = 0.89-1). Additionally, the results revealed significant differences in physicochemical DWQ between WS and house drinkers (HD), with medium to large effect sizes (d = 0.56-0.85). Furthermore, significant differences were identified in microbial DWQ between winter and summer, with a small to large effect size (d = 0.40-0.87). Notably, we recorded significant differences in microbial DWQ between WS and WT, with a small to medium effect size (d = 0.40-0.61), and between WT and BD, with a small to medium effect size (d = 0.48-0.53). Additionally, we found significant differences in microbial DWQ between WS and LD, with a medium effect size (d = 0.59-0.68). In conclusion, Tw.C° is influenced by seasonal variations in Ta.C°. While the physicochemical DWQ was unaffected by seasonal temperature variations, it was significantly impacted by the DWDS from WS to HD. In contrast, the microbial DWQ was strongly influenced by both seasonal temperature changes and DWDS.