Cattle Potential

Scientific and technical description of the project. The project is being implemented to disseminate the developed algorithms for determining and quantifying reserves for growth in cattle productivity, taking into account the cost of resources, the genetic potential of animals and the optimal feeding ration. It is presented on the basis of a software and analytical complex (SAC) with a mobile version.

Industrial livestock farming is the main source of agricultural products, the volumes of which allow not only to satisfy domestic needs within the framework of ensuring food security, but also form a significant export potential in livestock farming. Determining the growth reserves of dairy cattle breeding is one of the most important factors in increasing the production and sale of milk. At the same time, the problematic issues remain the imbalance of diets, overconsumption of feed, instability of production of optimal volumes of feed, full use of the genetic potential of animal productivity. As a result, in agricultural organizations, the livestock sector is economically high-cost. Increasing its efficiency is a necessary condition for the further successful development of agriculture. An important role is also played by the introduction of innovative solutions into production processes aimed at reducing specific production costs, maintaining an appropriate level of product quality, and reducing the environmental burden within the framework of economic activity.

In this regard, we have developed an algorithm for determining and quantifying reserves for increasing cattle productivity, based on the cost of resources, genetic potential, and optimal animal feeding rations, which are presented on the basis of the PAC with a mobile version.

Approbation. The foundations for developing the “Cattle Potential” algorithm were laid more than 10 years ago by scientists from the Institute of System Research in the Agro-Industrial Complex of the National Academy of Sciences of Belarus at the intersection of animal husbandry, agricultural economics and business analysis. (Takun A. P., Klimovec E. G., Takun S. P. Economic calculation in dairy cattle breeding: a methodical practical course. – Minsk: Institute of System Research in the Agro-Industrial Complex of the National Academy of Sciences of Belarus, 2011. – 28 p.). The publication presents the main approaches to the definition and economic assessment of reserves for growth in cattle productivity in the context of the following areas: feeding level, feed quality, balanced diet, animal care.

The described approach is constantly being tested in practice and is used to optimize the development of dairy cattle breeding in a number of agricultural organizations, including: CPMS «Rus-Agro» (Dyatlovsky district, Grodno region), CPMS «Berezovets» (Gantsevichi district, Brest region), UP «Polymir-agro» (Polotsk district, Vitebsk region), etc.

Advantages. Unlike existing analogues on the market, the Potential Cattle PAC is focused on the potential productivity of animals, allows you to quantitatively assess the reserves for increasing productivity, determine its economically justified level, and can be used as a stand-alone application or integrated into other digital solutions for herd management. Allows users to correctly determine priorities in strategic and tactical planning for the development of the livestock industry, as well as promptly eliminate imbalances in animal feeding to achieve maximum economic effect (profit) in milk production.

Thus, the PAC allows solving the following tasks:

To determine the reserves for increasing the productivity of dairy cattle herds;
Optimize and balance feeding rations for animal groups;
Conduct calculations, accounting for losses and reserves caused by imbalances;
Reduce the burden on animal technicians;
Control feed consumption based on economic assessment;
Plan production and feed requirements;
Improve the efficiency of cattle breeding.

At present, the results of the algorithms (reserves), feeding rations are visualized through the developed mobile application «Mobile Farm» (integrated as a separate unit).