بررسی ارتباط بین گوارش‌پذیری منابع نشاسته‌ای با شاخص‌های تولید و سلامت در گاوداری‌های شیری استان آذربایجان غربی

Introduction:
Starch stands as one of the most critical nutritional components in dairy cattle diets, serving as a primary energy source that directly influences metabolic functions, milk synthesis, and overall herd health. In typical feeding systems, common starch sources such as corn silage, corn grain, barley, and wheat are incorporated; however, these ingredients differ considerably in terms of their chemical structure, ruminal degradation kinetics, and total-tract digestibility. Such variations lead to marked differences in their effects on milk production, reproductive efficiency, and the prevalence of health disorders including dystocia, mastitis, and lameness. West Azerbaijan Province, a leading region in Iran’s dairy sector, relies heavily on locally produced starch sources like barley and corn. Despite this, there remains a notable lack of scientific data regarding the efficiency and suitability of these feedstuffs across different farm scales—small, medium, and large. This gap is particularly relevant given that farm size often correlates with differences in management capacity, feeding infrastructure, and access to technical support. Accordingly, this study was conceived to systematically evaluate the relationships between starch source utilization and key performance metrics across a range of dairy operations in West Azerbaijan. The specific objectives were threefold: (1) to analyze and compare the chemical composition and in vivo digestibility of the most commonly used starch sources—corn silage, corn grain, barley, and wheat; (2) to examine how each source relates to milk production traits, reproductive indices, and metabolic health parameters; and (3) to formulate herd-size–specific nutritional guidelines that can support enhanced productivity, welfare, and economic sustainability in the region’s diverse dairy farming systems.

Materials and Methods:
A total of 31 industrial dairy farms located throughout West Azerbaijan Province were enrolled in this study. These were strategically classified according to herd size into three distinct categories: small (maintaining 15–30 milking cows, n=5), medium (31–60 cows, n=20), and large (61–150 cows, n=6). A comprehensive, multi-method data collection protocol was implemented over three consecutive months (June, July, and August) to capture seasonal variations. This included: (i) the administration of detailed, pre-tested questionnaires designed to record farm management practices, precise feed ingredient profiles, health event logs (e.g., dystocia, clinical mastitis, lameness, and metabolic issues), and reproductive performance indicators; (ii) systematic monthly sampling of all major starch-based feeds—corn silage, corn grain, barley, and wheat—as well as representative bulk-tank milk samples from each farm; and (iii) extensive laboratory analyses conducted on collected samples. Feed analyses determined dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), acid detergent fiber (ADF), and ether extract (EE) following established procedures outlined by the AOAC (2003). To estimate total-tract digestibility coefficients for DM, organic matter (OM), and CP, acid-insoluble ash was employed as a reliable internal marker. Milk composition parameters—specifically fat, protein, and lactose percentages—were accurately measured using a Fourier-transform infrared spectroscopy-based Milkoscan instrument. All statistical evaluations were carried out with SAS software (version 9.4). Continuous response variables (such as milk yield, composition, and digestibility values) were analyzed using mixed-effect models that accounted for repeated measures, while health incidence data (binomial outcomes) were assessed via logistic regression procedures. A probability level of P<0.05 was considered statistically significant for all tests.

Results and Discussion:
The analysis revealed pronounced differences in starch source selection patterns across the three farm size categories. Smaller-scale farms demonstrated a heavy reliance on commercially formulated concentrates, which constituted approximately 75% of the starch input. In contrast, larger farms utilized significantly higher proportions of barley (55.6% of dietary starch) and corn grain (75%), reflecting greater on-farm mixing capacity and procurement flexibility. Use of wheat declined progressively as herd size increased, from 50% in small herds to 33.3% in large herds. Corn silage was a dietary staple across all systems, present in 75–88.9% of rations, though its dry matter content varied, with medium farms recording significantly higher DM (32.3%) compared to large farms (26.0%, P<0.05). Production outcomes indicated that larger farms achieved higher overall milk yields (P<0.05), although milk components—specifically fat (ranging 3.50–3.63%) and protein (3.13–3.19%)—remained statistically similar across groups. A notable temporal effect was observed in lactose content, which peaked significantly in small herds during August (4.72%, P<0.05), potentially indicating less effective heat-abatement strategies and subsequent shifts in rumen fermentation patterns during hot weather. Health monitoring data highlighted a higher incidence of dystocia in smaller herds (4.43% of calvings), possibly linked to suboptimal pre-partum nutrition. Meanwhile, larger herds reported elevated rates of metabolic disturbances, specifically acidosis (1.20%) and clinical mastitis (1.60%), likely resulting from high-concentrate feeding regimes. Reproductive performance was generally subpar across all farm types, with an average interval to first observed estrus of 68.95 days and 1.65 artificial insemination services required per conception. Most importantly, apparent total-tract digestibility estimates were consistently and significantly superior in larger herds across multiple metrics: DM (56.02% in large vs. 46.98% in small), OM (57.58% vs. 51.01%), and CP (61.60% vs. 53.47%) (P<0.05 for all). This digestibility advantage underscores the role of advanced ration balancing, consistent feed delivery, and professional nutritional oversight commonly available in larger, more resource-endowed operations.

Conclusion:
This study underscores the profound influence of farm scale and associated management factors on starch utilization efficiency, milk output, and herd health under practical conditions in West Azerbaijan. Smaller farms, often constrained by limited technical expertise and feeding infrastructure, exhibited clear nutritional imbalances—including overreliance on commercial concentrates—and elevated perinatal challenges such as dystocia. Larger farms, while achieving higher milk yields and superior starch digestibility (reinforcing the nutritional superiority of corn over barley in high-yielding cows), simultaneously faced greater risks of diet-related metabolic disorders due to intensive concentrate inclusion. Seasonal fluctuations in milk lactose percentage highlighted critical gaps in environmental management, particularly heat stress mitigation, among smallholder producers. These findings collectively suggest that future feeding strategies must be tailored to herd capacity and available resources. For smaller farms, practical recommendations include dietary diversification, reduced dependence on purchased concentrates, and basic training in ration formulation. In larger, more intensive systems, focus should shift toward optimizing dietary starch-to-fiber ratios, adopting precision feeding technologies, and implementing more robust metabolic health screening protocols. At a broader level, policy interventions—such as the creation of open-access regional feed composition databases, financial incentives for high-quality forage production, and subsidized extension services—could significantly improve sustainability and animal welfare across the dairy sector. By aligning nutritional management with operational scale, producers can simultaneously enhance productivity, reduce veterinary costs, and improve overall farm resilience, thereby contributing to a more competitive and evidence-based dairy industry in Iran.