Dynamic system modeling and decision support for grow-finish swine barn operation

Yang, Shang-Jen

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https://hdl.handle.net/2142/99251 Copy

Description

Title

Dynamic system modeling and decision support for grow-finish swine barn operation

Author(s)

Yang, Shang-Jen

Issue Date

2017-12-08

Director of Research (if dissertation) or Advisor (if thesis)

Wang, Xinlei

Doctoral Committee Chair(s)

Wang, Xinlei

Committee Member(s)

• Gates, Richard S.
• Ellis, Michael
• Hayes, Morgan D

Department of Study

Engineering Administration

Discipline

Agricultural & Biological Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Modeling
• Swine barn
• Decision support
• Grow-finish swine

Abstract

Understanding both swine growth performance and swine barn management under different conditions is essential to evaluate the swine production system. The integrated effect of swine growth and swine barn management is difficult to investigate because of their complex relationships. To estimate the integrated effect between swine growth and swine barn management, a dynamic modeling approach is proposed and applied to simulate swine growth performance under different swine barn management practices. To better simulate the swine growth performance, a modified simple pig growth model (MSPGM) was developed, calibrated, and validated based on two recent separate experiments conducted in 2016 with the same breeding line of swine but different indoor temperatures. The calibration results of the MSPGM demonstrate that swine in the experiment grow leaner, consume more feed, have higher maximum protein deposition rate, and utilize energy more efficiently to deposit body lipid and protein, as compared to data obtained from previous studies. The validation results under lower indoor temperature of the MSPGM showed an underestimation of pig weight, feed intake, and backfat probe thickness with the current modeling scheme. Based on the MSPGM, a process-level integrated swine production system model (ISPSM) was developed by incorporating a grow-finish (33 kg – 130 kg) swine growth simulation with a mechanical-ventilated swine barn management system. A sensitivity analysis on specific ISPSM parameters was then conducted to identify critical swine production practices on different production and performance indicators, including the average daily gain (ADG), feed conversion ratio (FCR), total utility cost (TUC), and marginal utility cost (MUC) for the growing cycle. A case study in Ames, Iowa, was conducted for sensitivity analysis of both heating (Jan - Mar) and cooling seasons (May - Oct) in 2013 to evaluate the potential integrated effect on a virtual 2400-head mechanical-ventilated grow-finish swine barn. Under the ISPSM, the minimum body lipid to protein ratio, building setpoint temperature, and protein level in the diet were shown to be the three most influential parameters on the swine performance indicators. Leaner swine performed better for all performance indicators. A higher setpoint temperature tended to decrease the ADG during both seasons but increased the FCR during the heating season. Both low and high protein levels in feed tended to have a negative impact on the FCR, which implies the existence of an optimum protein level in the diet. During the cooling season, the results indicated that lower protein levels in the diet affected a higher FCR, as compared to the heating season. This modeling result implies the importance of maintaining a sufficient protein level in the diet, especially when swine consume less feed during the cooling season. While seasonality has an important effect on swine growth performance, heat stress in the cooling season can be improved by implementing evaporative cooling as a part of the ventilation system. Although several studies have suggested different evaporative cooling pad (ECP) control approaches based on environmental variables that include temperature, relative humidity, and indices such as thermal humidity index, few studies have been published on the swine barn economic returns of ECP operation strategies. The current research applied the ISPSM to evaluate the economic return for different ECP control offsets for a virtual swine barn. The average daily gain (ADG), daily total utility cost (TUC), marginal utility cost (MUC), evaporative operation cost, and feed conversion ratio (FCR) were used as factors to evaluate the average daily profit (ADP) for the entire growing cycle. A comparison among potential savings due to different ECP control offsets for the cooling season was estimated based on an Iowa virtual swine barn case study using weather data for the past 18 years. Among the different scenarios, no statistically significant differences were found for the FCR. However, statistically significant differences for the AEUC, MUC, ADG, and ADP were found between scenarios with lower and higher ECP operating temperature offsets. This research also found a larger deviation for ADP when ECP operated both at a higher temperature offset and without an ECP operation, which implies the potential benefit of operating an ECP at a lower temperature offset. On the other hand, the simulation result implies that contract growers who focus more on the MUC would likely not choose to operate the cooling pad based on the assumed conditions. Current grow-finish swine producers follow a setpoint temperature by operating under recommendations to reduce the growing period based on the swine live weight without considering the outdoor environment. To meet the difficult-to-achieve setpoint temperature based on those recommendations, the swine house requires extensive energy input. As a result, a more comprehensive setpoint temperature recommendation is required to optimize the economic return of swine housing operation. Based on the ISPSM, the current research developed an economic optimization procedure by recommending daily a setpoint temperature for grow-finish swine production that takes into consideration forecasted outdoor temperature and estimated economic returns. Different economic perspectives were investigated to 1) minimize the FCR for integrated producers, 2) minimize the MUC for contract growers, and 3) optimize the overall economic returns for independent producers. A case study using a virtual swine production system in 2013 located in Ames, Iowa, with different perspectives was conducted to evaluate the optimization procedure. The results showed a higher setpoint temperature in the cooling season and a longer growing period from the contractors’ perspective. In order to produce revenue, integrators and independent producers tend to meet the setpoint with a lower temperature to create the best FCR and ADG. While the optimized setpoint temperature profiles are similar with or without the ECP operation, the setpoint for optimum FCR and ADP tends to be higher for scenarios without ECP, due to the difficulties to achieve LCT.

Graduation Semester

2017-12

Type of Resource

text

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Copyright and License Information

Copyright 2017 Shang-Jen Yang

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