Modeling of specific energy consumption within technology cycles of pig breeding

Artykuł dotyczy określenia energochłonności czterech podstawowych grup w chowie trzody chlewnej. W wyniku pomiarów eksploatacyjnych oraz analiz teoretycznych uzyskano jednostkowe zużycie energii w odniesieniu do poszczególnych czynności wykonywanych w ramach produkcyjnego cyklu technologicznego. Opracowano proste zależności matematyczne, określające zależność jednostkowego zużycia energii od normatywnych bądź zalecanych wartości eksploatacyjnych dla danej grupy trzody chlewnej. Dokonano również oceny wzajemnych zależności jednostkowego zużycia energii w poszczególnych grupach zabiegów roboczych.The article presents results of modeling and operational evaluation of specific energy consumption in four pig breeding categories, which have been realized under the project QF 3200 „Expert System for Determination Support and Optimization of Technology Processes Control in Agricultural Production“ supported by Czech Ministry of Agriculture. The first step of solution brought mathematical equations that describe physical relation of specific energy consumption to machine input, technology cycle duration, total efficiency and day time operation. As example of energy requirements of material manipulation during feeding operation, mulch treatment are presented in equations 1 to 4. Following performed analysis based on calculated and operationally proved energy consumptions were created simple mathematical equations (tab. I) that qualify relation of specific energy consumption Q [Wh.d-1.ks-1] to recommended or standardized values of dry pasture mkr [kg.d-1.ks-1], wet pasture mkr,v [kg.d-1.ks-1], specific mulch production mmr [kg.d-1.ks-1], liquid manure mk [kg.d-1.ks-1], stable area S1,u [m2.ks-1], disinfected area S1,z [m2.ks-1], technology cycle duration τTC [d] and average animal weight mz [kg.ks-1]. The elementary mathematical models come out from hypothesis that individual operation and technology cycles of agricultural production is possible to optimize on the base of theoretical knowledge adjusted by real conditions. The results in the tab. I show notably high energy consumption for indoor environment conditions maintenance. The most significant is category P2, pregnant, parturient and nursing sows. This category has 50 times higher specific energy consumption for maintenance of required quality of “System environment” operation than total specific energy consumption for “Stable preparation”, “Feeding” and “Mulch manipulation”. In the article presented partial results prove the influence of specific energy consumption to spent direct costs and production effectiveness. The specific energy consumption is one of major criteria to production optimization such as work productivity and unitary direct costs. The analysis significance is during decision process