Multi-attribute decision-making: Use of scoring methods to choose the best form of dietary fat supplement in pregnant Saanen goats.

Background: Nutritional manipulation with functional nutrients like polyunsaturated fatty acids can boost milk production efficiency in dairy farming. It is important to consider the animal's physiological periods, especially the second half of the first pregnancy for mammary gland development.

Objectives: By considering multiple factors and comparing them, multi-attribute decision-making (MADM) can be utilized to conduct further assessments and select the best diet for the animals.

Methods: Forty primiparous Saanen does, from the last 2 months of pregnancy up to 4 months of lactation, have been assigned to four iso-energetic and iso-nitrogenous diets. Four dietary groups included: no external sources of fat (negative control, CT), saturated palm oil (positive control), roasted soybeans (omega-6, SB) and extruded flaxseed (omega-3, FS). Twenty-two performance criteria such as feed intake, milk yield and composition, body weight, blood metabolites and hormones, the milk fatty acid profile, as well as morphological and histological measurements of the mammary gland, in the form of least-square means, were considered.

Results: A decision-making tool was used to select the best form of fat supplements in late pregnancy and early lactation diets, to improve lactation performance in Saanen goats. For this purpose, a MADM method was applied to determine the order of preference similarity to the ideal solution. According to the score of this method, the FS group had the highest coefficients (0.689), and the CT group had the lowest coefficients (0.281).

Conclusions: Incorporating flaxseed into the diets of Saanen goats during late pregnancy and early lactation is a valuable strategy for enhancing milk performance. This supplement is recommended as a source of fat. Additionally, the implementation of decision-making tools, such as the MADM method in animal science, can significantly improve management decision-making processes by reducing both time and cost. This presents a new avenue for making well-informed decisions.