Development of the precision feeding system for sows via a rule-based expert system

Chong Chen, Xingqiao Liu, Chaoji Liu, Qin Pan

Abstract


To precisely meet the nutritional requirements of sows during the stages of pregnancy and lactation, a precision feeding system was developed by using the intelligent sow feeder combined with a rule-based expert system and the Internet of Things (IoTs). The model of uncertain knowledge representation was established for inference by using the certainty factor. The daily feeding amount of each sow was calculated by the expert system. An improved pattern matching algorithm Reused Degree Model-RETE (RDM-RETE) was proposed for the decision of daily feeding amount, which sped up inference by optimizing the RETE network topology. A prediction model of daily feeding amount was established by a rule-based expert system and the precision feeding was achieved by an accurate control technology of variable volume. The experimental results demonstrated that the HASH-RDM-RETE algorithm could effectively reduce the network complexity and improve the inference efficiency. The feeding amount decided by the expert system was a logarithmic model, which was consistent with the feeding law of lactating sows. The inferential feeding amount was adopted as the predicted feed intake and the coefficient of correlation between predicted feed intake and actual feed intake was greater than or equal to 0.99. Each sow was fed at different feeding intervals and different feed amounts for each meal in a day. The feed intake was 26.84% higher than that of artificial feeding during lactation days (p<0.05). The piglets weaned per sow per year (PSY) can be increased by 1.51 compared with that of relatively high levels in domestic pig farms. This system is stable in feeding and lowers the breeding cost that can be applied in precision feeding in swine production.
Keywords: precision feeding, expert system, pattern matching, lactating sows, intelligent sow feeder, feed intake
DOI: 10.25165/j.ijabe.20231602.7427

Citation: Chen C, Liu X Q, Liu C J, Pan Q. Development of the precision feeding system for sows via a rule-based expert system. Int J Agric & Biol Eng, 2023; 16(2): 187-198.

Keywords


precision feeding, expert system, pattern matching, lactating sows, intelligent sow feeder, feed intake

Full Text:

PDF

References


Strathe A V, Bruun T S, Geertsen N, Zerrahn J E, Hansen C F. Increased dietary protein levels during lactation improved sow and litter performance. Animal Feed Science & Technology, 2017; 232: 169-181.

Hermesch S. First analysis of factors influencing feed intake of sows during lactation. In: AGBU Pig Genetics Workshop, 2006; pp.44-49.

Wähner M, Scholz H, Kämmerer B. Relationship between side fat thickness, feed intake in last days of pregnancy and during lactation and rearing performance in sows. Biotechnology in Animal Husbandry, 2000; 17(5-6): 3-16.

Mellagi A P G, Panzardi A, Bierhals T, Gheller N B, Bernardi M L, Wentz I, et al. The effect of parity order and lactation weight loss on subsequent reproductive performance of sows. Arquivo Brasileiro de Medicina Veterinária e Zootecnia, 2013; 65(3): 819-825.

Jin S S, Jin Y H, Jang J C, Hong J S, Jung S W, Kim Y Y. Effects of dietary energy levels on physiological parameters and reproductive performance in gestating sows over three consecutive parities. Asian-Australasian Journal of Animal Sciences, 2018; 31(3): 410-420.

Elsley F W H, Bannerman M, Bathurst E V J, Bracewell A G, Cunningham J M M, Dodsworth T L, et al. The effect of level of feed intake in pregnancy and in lactation upon the productivity of sows. Animal Production, 1969; 11(2): 225-241.

Kim S W, Easter R A. Nutrient mobilization from body tissues as influenced by litter size in lactating sows. Journal of Animal Science, 2001; 79(8): 2179-2186.

Gomes B C K, Andretta I, Valk M, Pomar C, Hauschild L, Fraga A Z, et al. Prandial correlations and structure of the ingestive behavior of pigs in precision feeding programs. Animals, 2021; 11(10): 2998. doi: 10.3390/ani11102998.

Lei X J, Lee S I, Kim I H. Evaluation of three different patterns of feed intake during early lactation in lactating sows. Animal Science Journal, 2018; 89(8): 1129-1133.

Marcon M, Brossard L, Quiniou N. Precision feeding based on individual daily body weight of group-housed pigs with an automatic feeder developed to allow for restricting feed allowance. Precision Livestock Farming, 2015; 15: 592-601.

Manteuffel C, Schon P C, Manteuffel G. Beyond electronic feeding: The implementation of call feeding for pregnant sows. Computers and Electronics in Agriculture, 2011, 79: 36-41.

Xiong B H, Yang L, Cao P, Pan X H, Wang M L. Optimal design and test of electromechanical control system of automatic feeder for nursing sow. Transactions of the CSAE, 2014; 30(20): 28-33. (in Chinese)

Xiong B H, Yang L, Zheng S S, Cao P, Pan X H, Wu G T. Design and test of precise blanking control system for lactating sows. CSAE, 2017; 33(20): 177-182.

Wang M Z, An T, Liu J J, Zhang J R, Wang W F, Yi L, et al. Effect of intelligent feeder on feed intake, body condition and production performance of lactating sows. Transactions of the CSAE, 2019; 35(6): 190-197. (in Chinese)

Geng L Q, Chen Z, Chen C W, Huang G H. An intelligent decision support system for management of petroleum-contaminated sites. Expert Systems with Applications, 2001; 20(3): 251-260.

Chakrabarty B K. Expert System: A Tool for Expert Decision. Transactions of the Indian Ceramic Society, 2002; 61(3): 118-121.

Guo C, Xiong W, Hao L Y. An improved RETE algorithm with branch filtration. Procedia Engineering, 2017; 174: 767-772.

Xiao D, Zhong X A. Improving RETE algorithm to enhance performance of rule engine systems. In: 2010 International Conference on Computer Design and Applications, Qinhuangdao, China: IEEE, 2010; pp.V3-572−V3-575. doi: 10.1109/ICCDA.2010.5541368.

Yay E, Madrid N M, Ramírez J A O. Using an improved rule match algorithm in an expert system to detect broken driving rules for an energy-efficiency and safety relevant driving system. Procedia Computer Science, 2014; 35: 127-136.

Karmakar S, Nketia M, Lague C, Agnew J. Development of expert system modeling based decision support system for swine manure management. Computers and Electronics in Agriculture, 2010; 71(1): 88-95.

Banhazi T M, Babinszky L, Halas V, Tscharke M. Precision livestock farming: Precision feeding technologies and sustainable livestock production. Int J Agric & Biol Eng, 2012; 5(4): 54-61.

Pomar J, Pomar C. A knowledge-based decision support system to improve sow farm productivity. Expert Systems with Applications, 2005; 29(1): 33-40.

Vásquez R P, Aguilar-Lasserre A A, López-Segura M V, Rivero L C, Rodríguez-Duran A A, Rojas-Luna M A. Expert system based on a fuzzy logic model for the analysis of the sustainable livestock production dynamic system. Computers and Electronics in Agriculture, 2018; 161: 104-120.

Xu X J, Yan X P, Sheng C X, Yuan C Q, Xu D L, Yang J B. A belief rule-based expert system for fault diagnosis of marine diesel engines. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017; 50(2): 656-672.

Forgy C L. RETE: A fast algorithm for the many pattern/many object pattern match problem. Artificial Intelligence, 1982; 19: 17-37.

Sun X, Yan X M, Shang Y M, Ouyang T, Dong K. An improved RETE algorithm using shared degree model. Acta Automatica Sinica, 2019; 43(9): 1571-1579. (in Chinese)

Cabezón F A, Schinckel PAS A P, Richert B T, Stewart K R, Gandarillas M, Peralta W A. Analysis of lactation feed intakes for sows including data on environmental temperatures and humidity. The Professional Animal Scientist, 2016; 32:333–345.

Chen C, Liu X Q, Duan W Y, Liu C J. Assessment of the environmental comfort of lactating sows via improved analytic hierarchy process and fuzzy comprehensive evaluation. Int J Agric & Biol Eng, 2022; 15(2): 58-67.




Copyright (c) 2023 International Journal of Agricultural and Biological Engineering

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

2023-2026 Copyright IJABE Editing and Publishing Office