APPLICATION OF FUZZY SYSTEMS ANALYSIS IN BIOLOGICAL SYSTEMS ENGINEERING

• Sponsoring Institution: National Institute of Food and Agriculture
• Project Status: COMPLETE
• Funding Source: HATCH
• Reporting Frequency: Annual
• Accession No.: 0182136
• Project Start Date: Jun 1, 2009
• Project End Date: May 31, 2014
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIVERSITY OF NEBRASKA
(N/A)
LINCOLN,NE 68583

Performing Department
Biological Systems Engineering

Non Technical Summary
The problem of heat stress in cattle is a complex problem in that it combines the character of the animal (e.g., temperament, physiology and genetics), setting of the animal (e.g., type of pen, feed, crowding), environment (e.g., climate, weather patterns) and management goals. The problem and tools associated with systems analysis and mathematical modeling perform very well when the system is defined and delineated. In a system such as heat stress in cattle, traditional modeling strategies and descriptors may not be adequate or satisfactory. As such, fuzzy systems analysis will be used to model and describe the impact of heat stress in cattle.

Animal Health Component

45%

Research Effort Categories

Basic

10%

Applied

45%

Developmental

45%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
306	3310	2020	50%
307	3310	1060	20%
315	3310	2020	30%

Knowledge Area
307 - Animal Management Systems; 306 - Environmental Stress in Animals; 315 - Animal Welfare/Well-Being and Protection;

Subject Of Investigation
3310 - Beef cattle, live animal;

Field Of Science
2020 - Engineering; 1060 - Biology (whole systems);

Keywords

cattle heat stress

fuzzy set theory

systems modeling

animal specific management

Goals / Objectives
The overall goal of this work is to aid in the understanding of heat stress in feedlot cattle and a means to mitigate that stress. Specific objectives are to develop a data representation and transformation strategies for such systems that result in descriptive and explanatory models. These models must address the nature, extent, and character of the ambiguity associated with each aspect of cattle heat stress. This analysis will 1. develop and refine fuzzy rule based models and neural network models to predict heat stress in feedlot cattle; 2. compare the utility of each model and refine the data representation; 3. suggest management, genotype, and health factors impacting heat stress in feedlot cattle; and 4. identify cattle (based on characteristics of health, coat color, genotype, etc) that are anticipated to be impacted by heat stress.

Project Methods
The process of developing a new paradigm for systems analysis is not linear and will likely require several iterations. The following is a review of the necessary steps and inputs. 1. Data, appropriate for analysis, will be collected in cooperation with the Dr. Tami Brown-Brandl (ARS-MARC). The data will be collected from cohorts of animals at MARC. The cohorts will be selected based on animal features (health history, genotype, coat color), subjected to varied confinement strategies, and weather conditions. Heat stress will be measured by monitoring physiological responses such as respiration rate and panting score. 2. Candidate descriptive techniques include fuzzy c-varieties, fuzzy clustering, linguistic representation, forced pair ordering and others. Transformation strategies will be tested using the data characterized in objective 1. 3. The model will be tested, modified, and verified with data from subsequent seasons and animal cohorts. The refinement will be based upon advances our understanding of the factors impacting cattle heat stress. 4. The models (and knowledge revealed in the models) will be challenged to identify cattle that are susceptible to heat stress. Such animals will be candidates for intensive management. Further output will be a methodology to collect, characterize, transform and interpret data regarding modeling of complex biological processes. 5. Validation of the model proposed by Brown-Brandl and Jones (2009) will be executed using data collected from individual animal heat stress observations.

Progress 06/01/09 to 05/31/14

Outputs
OUTPUTS: No progress to report. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.

Impacts
No progress to report.

Publications

• No publications reported this period

Progress 10/01/09 to 09/30/10

Outputs
OUTPUTS: A rule based model to identify specific feedlot animals that are susceptible to heat stress was evaluated. The validation process has been implemented and analysis proceeds. The model allows for animal specific determination of susceptibility to heat stress. The complex nature of the phenomena rendered conventional modeling techniques lacking. The use of a fuzzy-neural approach allowed for collection and expression of processing information and inference. Combined heat and power (CHP) and gas production from byproduct gasification was analyzed in light of economic performance and optimum processing conditions. PARTICIPANTS: Tami Brown-Brandl USDA-ARS MARC; Ajay Kumar BAE Oklahoma State University TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.

Impacts
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, gasification of biomaterials, animal heat stress, machine vision systems, and description of annoyance from odors animal confinements. The animal heat stress model allows for animal specific determination of susceptibility to heat stress. The ability to provide management to the individual animals based on individual need is progressing.

Publications

• Kumar, A., Y. Demirel, D. D. Jones, and M. A. Hanna. 2010. Optimization and economic evaluation of industrial gas production and combined heat and power generation from gasification of corn stover and distillers grains. Bioresource Technology 101(2010):3696-3701.

Progress 10/01/08 to 09/30/09

Outputs
OUTPUTS: A rule based model to identify specific feedlot animals that are susceptible to heat stress was developed. A validation process has been formulated and implementation proceeds. The model allows for animal specific determination of susceptibility to heat stress. Analysis of residence time distribution during the extrusion of starch with nano-composite materials was performed. The complex nature of the phenomena rendered conventional modeling techniques lacking. The use of a fuzzy-neural approach allowed for collection and expression of processing information and inference. PARTICIPANTS: Tami Brown-Brandl USDA-ARS MARC TARGET AUDIENCES: Nothing significant to report during this reporting period. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, gasification of biomaterials, animal heat stress, machine vision systems, and description of annoyance from odors animal confinements. The animal heat stress model allows for animal specific determination of susceptibility to heat stress. The ability to provide management to the individual animals based on individual need is progressing.

Publications

• Lee, S., M.A. Hanna, D.D. Jones. 2009. Residence time distribution and modeling of mechanical properties of extruded nanocomposite foams using adaptive neuro-fuzzy inference system. Starch, 61(6):326-333.

Progress 10/01/07 to 09/30/08

Outputs
OUTPUTS: We developed and refined models to deploy surgical instruments. The techniques have gained attention via publications and presentations. The model to determine the heat stress susceptibility of feedlot cattle was refined. We developed a model to describe the impact of incorporating nano-particles in the extrudates. PARTICIPANTS: Not relevant to this project. TARGET AUDIENCES: Not relevant to this project. PROJECT MODIFICATIONS: Not relevant to this project.

Impacts
We continue to advance the capability of accommodating ambiguity in modeling and describing biological systems. Specific examples include heat stress in feedlot cattle, skin permeability, residence time and expansion in reacting extruders, deploying surgical instruments, and describing livestock odors. The work has matured to the point that other research questions have been redefined.

Publications

• Miller, D., C. Nelson, D. Oleynikov, D. Jones. 2008. Pre-operative ordering of minimally invasive surgical tools: a fuzzy inference system approach. Artificial Intelligence in Medicine (Elsevier), Vol. 43, pp. 35-45.
• Lee, Siew Lee, Hanna, M.A. and David D. Jones. 2008. An adaptive neuro-fuzzy inference system for modeling mechanical properties of tapioca starch-poly (lactic acid) nanocomposite foams. Starch 60:159-164.

Progress 10/01/06 to 09/30/07

Outputs
We have advanced the capability of accommodating ambiguity in modeling and describing biological systems. Specific examples include heat stress in feedlot cattle, skin permeability, residence time and expansion in reacting extruders, deploying surgical instruments, and describing livestock odors.

Impacts
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, gasification of biomaterials, animal heat stress, machine vision systems, skin permeability, and description of annoyance from odors animal confinements. The objective is to model the residence time of material flow within the extruder and investigating strategies to scale-up extrusion processes. Further, the modeling reveals collaborative effects of processing parameters. Models were posed to describe the degree of annoyance associated with odors emanating from animal confinements.

Publications

• Kumar, A., G.M. Ganjyal, D.D. Jones, and M.A. Hanna. 2008. Modeling residence time distribution in a twin-screw extruder as a series of ideal steady-state flow reactors. Journal of Food Engineering, Vol. 84, pp. 441-448.
• Keshwani, D.R., D.D. Jones, G.E. Meyer, and R.M. Brand. 2008. Rule-based Mamdani-type fuzzy modeling of skin permeability. Applied Soft Computing, Vol. 8, pp. 285-294.
• Kumar, A., G.M. Ganjyal, D.D. Jones, and M.A. Hanna. 2007. Experimental determination of longitudinal expansion during extrusion of starches. Cereal Chemistry. Vol. 84(5), pp. 480-484.
• Miller, D.J., Carl A. Nelson, Dmitry Oleynikov, David D. Jones, 2006. A Fuzzy Inference System for the Ordering of Laparoscopic Tools in Minimally Invasive Surgery. 2006 Summer Bioengineering Conference Amelia Island, Florida. ASME BIO2006-156583, June 21-25, 2006.
• Wang, L., Ajay Kumar, David D. Jones, M.A. Hanna. 2007. Co-production of Chemical and Energy Products from Distillers Grains Using Supercritical Fluid Extraction and Thermochemical Conversion Technologies. ASABE Meeting Presentation; Minneapolis, Minnesota. ASABE Paper Number: 076064 June 17-20, 2007.
• Brown-Brandl, T.M, and David D. Jones. 2007. Development and Validation of an Animal Susceptibility Model. ASABE Meeting Presentation; Minneapolis, Minnesota. ASABE Paper Number: 074081, June 17-20, 2007.
• Kumar, A., Lijun Wang, Dennis A. Yuris, David D Jones, Milford A. Hanna. 2007. Thermogravimetric characterization of corn stover as gasification/Pyrolysis feedstock. ASABE Meeting Presentation; Minneapolis, Minnesota. ASABE Paper Number: 076146 Juen 17-20, 2007.
• Meyer, G., and David Jones. 2007. Advanced modeling in biological engineering using soft-computing methods. American Society of Engineering Education, AC2007-2729
• Halverson, M.J., D.D. Jones, D.D. Schulte. 2007. A knowledge-based model to assess odor annoyance. International Symposium on Air Quality and Waste Management for Agriculture. CD-Rom Proceedings of the 16-19 September 2007 Conference (Broomfield, Colorado) ASABE Publication Number 701P0907cd 2007.

Progress 10/01/05 to 09/30/06

Outputs
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, gasification of biomaterials, animal heat stress, machine vision systems, colorectal cancer, and description of annoyance from odors animal confinements. The objective is to model the residence time of material flow within the extruder and investigating strategies to scale-up extrusion processes. Further, the modeling reveals collaborative effects of processing parameters. Models were posed to describe the degree of annoyance associated with odors emanating from animal confinements.

Impacts
These developments allow for unbiased representations of design and configuration alternatives. Further, insights are gained about the interaction of competing underlying structures. Insights are gained into the impacts of management on feedlot cattle based on information about each individual animal.

Publications

• Brand, R.M., D.D. Jones, H.T. Lynch, R.E. Brand, P. Watson, R. Ashwathnayaran, H.K. Roy. 2006. Risk of Colon Cancer in Hereditary Non-polyposis Colorectal Cancer Patients as Predicted by Fuzzy Modeling: Influence of Smoking. World Journal of Gastroenterology, 12 (28):4485-4491.
• Kumar, A., G.M. Ganjyal, D.D. Jones, M.A. Hanna. 2006. Digital Image Processing for Measurement of Residence Time Distribution in a Laboratory Extruder. Journal of Food Engineering, 75, 237-244.
• Wang, L., D. Jones, C. Weller, M. Hanna. 2006. Modeling of Transport Phenomena and Melting Kinetics of Starch in a Co-Rotating Twin-Screw Extruder. Advances in Polymer Technology, 25(1):22-40.
• Ganjyal, G., M.A. Hanna, P. Supprung, A. Noomhorm, and D. Jones. 2006. Modeling Selected Properties of Extruded Rice Flour and Rice Starch by Neural Networks and Statistics. Cereal Chemistry, 83(3):223-227.
• Camargo Neto, J, G.E. Meyer, D.D. Jones. 2006. Individual leaf extractions from young canopy images using Gustofson-Kessel clustering and a genetic algorithm. Computers and Electronics in Agriculture, 51(2006):66-85.
• Camargo Neto, J, G.E. Meyer, D.D. Jones, A.K. Samal. 2006. Plant species identification using Elliptic Fourier leaf shape analysis. Computers and Electronics in Agriculture 50(2006):121-134.

Progress 10/01/04 to 09/30/05

Outputs
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, animal heat stress, machine vision systems and description of annoyance from odors animal confinements. The objective is to model the residence time of material flow within the extruder and investigating strategies to scale-up extrusion processes. Further, the modeling reveals collaborative effects of processing parameters. Work continues on the development of methods to extract information from digital images. This work is prominent in the field and has blended techniques from fuzzy set theory, genetic algorithms and traditional image processing into an impressive suite of analysis tools. Models were posed to describe the degree of annoyance associated with odors emanating from animal confinements.

Impacts
These developments allow for unbiased representations of design and configuration alternatives. Further, insights are gained about the interaction of competing underlying strucutures.

Publications

• Keshwani, D.R., D.D. Jones, and R.M. Brand. 2005. Takagi-Sugeno fuzzy modeling of skin permeability. Cutaneous and Ocular Toxicology, 24(3):147 -163.
• Wang, L., G.M. Ganjuyal, D.D. Jones, C.L. Weller, and M.A. Hanna. 2005. Modeling of bubble growth dynamics and nonisothermal expansion in starch-based foams during extrusion. Advances in Polymer Technology, 24(1)29-45.
• Brown-Brandl, T.M., D.D. Jones, and W.E. Woldt. 2005. Evaluating modelling techniques for cattle heat stress prediction. Biosystems Engineering. 91(4):513-524.
• Meyer, G.E., J. Camargo Neto, D. Jones and T.W. Hindman. 2004. Intensified fuzzy clusters for determining plant, soil, and residue regions of interest from color images. Computers and Electronics in Agriculture, 42(2004):161-180.

Progress 10/01/03 to 09/30/04

Outputs
Work continues on the development of methods to describe and model ambiguity in complex biological systems. The systems of interests include extrusion processes, animal heat stress, machine vision systems and transport of compounds through skin. The objective is to model the residence time of material flow within the extruder and investigating strategies to scale-up extrusion processes. To date we have developed models to describe residence time distributions by analytical procedures and instrumentation. A method to provide online measurement longitudinal expansion and density in extrusion was developed. Analytical analysis of the fluid flow, heat transfer and melting of biomaterials in a single-screw extruder was presented. Data collection occurred to support the analysis of animal heat stress in feedlots. The previously developed models will be refined and updated with these new observations. Work continues on the development of methods to extract information from digital images. This work is prominent in the field and has blended techniques from fuzzy set theory, genetic algorithms and traditional image processing into an impressive suite fo analysis tools. Models were posed to describe the transport of compounds through skin. Two approaches were used resulting in a data driven model and a knowledge driven model. Each model offers different insights and each are being refined.

Impacts
These developments allow for unbiased representations of design and configuration alternatives. Further, insights are gained about the interaction of competing underlying strucutures.

Publications

• Wang, L. G.M. Ganjyal, D.D. Jones, C.L. Weller, and M.A. Hanna. 2004. Finite element modeling of fluid flow, heat transfer and melting of biomaterials in a single-screw extruder. Journal of Food Science 69(5): 212-223.
• Meyer, G.E., T.W. Hindman, D.D. Jones and D.A. Mortensen. 2004. Digital camera operation and fuzzy logic classification of plant, soil, and residue color images. Engineering in Agriculture. 20(4):519-529.
• Kumar, A., G.M. Ganjyal, D.D. Jones, and M.A. Hanna. 2004. Modeling residence time distribution in extruder as a series of continuously stirred tank reactors. Annual meeting of American Society of Cereal Chemists, September 19-22, 2004 at San Diego, CA.
• Kumar, A., G.M. Ganjyal, D.D. Jones, and M.A. Hanna. 2004. Measurement of residence time distribution in extruder using image analysis and conductivity. Biannual meeting of Corn Utilization Technology Conference, June 7-9, 2004, Indianapolis, IN.
• Kumar, A., G.M. Ganjyal, D.D. Jones, and M.A. Hanna. 2004. Online measurement longitudinal expansion and density in extrusion. Biannual meeting of Corn Utilization Technology Conference, June 7-9, 2004, Indianapolis, IN.
• Brand, R.M., D. Jones, H. Lynch, R.E. Brand, A. Nickolov, P. Watson, and H. Roy. 2004. Use of fuzzy modeling to predict the risk of colon cancer in HNPCC patients. Presented at Digestive Disease Week, New Orleans, LA, May 16, 2004.
• Keshwani, D., D. Jones, and R. Brand. 2004. Fuzzy rule based model of skin permeability. 17th Annual Nebraska Biomedical Engineering Conference. Lincoln, NE, May 2004.

Progress 10/01/02 to 09/30/03

Outputs
This research continues to develop mechanisms and procedures to combine quantitative, qualitative, ambiguous, and competing information into a formal mathematical representation. This methodology has been used to perform modeling of extrusion processes, transport through skin, analysis of renewable energy systems, interpretation of machine vision images, animal stress modeling, and error modeling.

Impacts
These developments allow for unbiased representations of design and configuration alternatives. Further, insights are gained about the interaction of competing underlying strucutures.

Publications

• Meyer, G.E., J. Camargo Neto, D. Jones and T.W. Hindman. 2003. Intensified fuzzy clusters for determining plant, soil, and residue regions of interest from color images. Computers and Electronics in Agriculture, accepted for publication.
• Ganjyal, G., M. Hanna, and D. Jones. 2003. Modeling selected properties of extruded waxy maize cross-linked starches with neural networks. Journal of Food Science 68(4):1384-1388.
• Pannier, A., R. Brand, and D. Jones. 2003. Fuzzy modeling of skin permeability coefficients. Pharmaceutical Research. 20(2):143-148.
• Merino, G.G., D. Jones, L.D. Clements, and D. Miller. 2003. Fuzzy compromise programming with precedence order in the criteria. Applied Mathematics and Computation 134(1):184-205. ARD Journal Series No. 13195.
• Brown-Brandl, T.M., D. Jones, and W.E. Woldt. 2003 Evaluating modeling techniques for livestock heat stress prediction. ASAE Paper Number 034009, July, 2003
• Camargo Neto, J. G.E. Meyer, D. Jones, and A.J. Surkan. 2003. Adaptive image segmentation using a fuzzy neural network and genetic algorithm for weed detection. ASAE paper number 033088, July, 2003.
• Meyer, G.E. and D. Jones 2003. Thermodynamics of living systems: a fundamental course for biological engineering. The 2003 Annual International Meeting, Institute of Biological Engineering, Athens, GA, January 17-19, 2003.

Progress 10/01/01 to 09/30/02

Outputs
This research continues to develop mechanisms and procedures to combine quantitative, qualitative, ambiguous, and competing information into a formal mathematical representation. This methodology has been used to perform crop modeling, transport through skin, risk analysis, analysis of renewable energy systems, and error modeling.

Impacts
These developments allow for unbiased representations of design and configuration alternatives.

Publications

• Merino, G.G., F.E. Novoa, and D.D. Jones. 2002. Fuzzy Compromise Programming with Precedence Order in the Criteria. XI CLAIO. CONGRESO LATINO IBEROAMERICANO DE INVESTIGACION DE OPERACIONES. Concepcion Chile, 27-31 October 2002.
• X. Lin, K.G. Hubbard, D.D. Jones, and G. Merino, 2002: Fuzzy Rule-Based Approach to Evaluate Air Temperature Biases in Weather Stations. The 13th Conference on Applied Climatology. American Meteorological Society, Page J82-J83. 13-16 May 2002. Portland, Oregon.
• Jones, D.D. 2002. Graduate education for the bio-based products industry. American Chemical Society, 223rd National Meeting, Orlando, FL, April, 7-11, 2002.
• Pannier A.K., Brand R.M., and Jones D.D. 2002. Modeling skin permeability coefficients with fuzzy logic. Perspectives in Percutaneous Penetration. 8:27.
• Merino, G.G., D.D. Jones, L.D. Clements, and D. Miller. 2003. Fuzzy compromise programming with precedence order in the criteria. Applied Mathematics and Computation 134(1):184-205. ARD Journal Series No. 13195.

Progress 10/01/00 to 09/30/01

Outputs
This research continues to develop mechanisms and procedures to combine quantitative, qualitative, ambiguous, and competing information into a formal mathematical representation. This methodology has been used to perform crop modeling, irrigation scheduling, risk analysis, analysis of renewable energy systems, and error modeling.

Impacts
These developments allow for unbiased representations of design and configuration alternatives.

Publications

• Arumi, J.L. and D. Jones. 2001. Methodology for the analysis of risk analysis of irrigation structures. Hydraulic Engineering in Mexico. Volume XVI (3):67-74, July - Sept 2001. (In Spanish.)
• Merino, G.G., D. Jones, D. Stooksbury, and K.G. Hubbard. 2001. Determination of semivariogram models to krige hourly and daily solar irradiance in Western Nebraska. Journal of Applied Meteorology. 40(6):1085-1094. ARD Journal Series No. 12746.
• Jones, D., E.M. Barnes. 2000. Fuzzy composite programming to combine remote sensing and crop models for decision support in precision crop management. Agricultural Systems 65(3):137-158 ARD Journal Series No. 12846.
• Merino, G.G., D. Jones, and L.E. Stetson. 2000. Performance of a grid-connected photovoltaic system using actual and kriged hourly solar radiation. Transactions of the ASAE 43(4):1011-1018. ARD Journal Series No. 12879.

Progress 10/01/99 to 09/30/00

Outputs
This research has developed mechanisms and procedures to combine quantitative, qualitative, ambiguous, and competing information into a formal mathematical representation. This methodology has been used and demonstrated on problems associated with crop modeling and irrigation scheduling and selection of on-site renewable energy systems.

Impacts
These developments allow for unbiased representations of design and configuration alternatives.

Publications

• Merino, G.G., Jones, D., Stooksbury, D., and Hubbard, K.G. 2000. Determination of semivariogram models to krige hourly and daily solar irradiance in western Nebraska. Journal of Applied Meteorology. ARD Journal Series No. 12746. (Accepted for Publication. In Press).
• Jones, D., Barnes, E.M. 2000. Fuzzy composite programming to combine remote sensing and crop models for decision support in precision crop management. Agricultural Systems. ARD Journal Series No. 12846. (Accepted for Publication. In Press).
• Merino, G.G., Jones, D., and Stetson, L.E. 2000. Performance of a grid-connected photovoltaic system using actual and kriged hourly solar radiation. Transactions of the ASAE. ARD Journal Series No. 12879. (Accepted for Publication. In Press).

Progress 10/01/98 to 09/30/99

Outputs
Initial progress on this project has begun. To date, a partial literature review has been completed revealing a vast number of attempts to develop data manipulation schemes for odor classification. More investigation in this area is required. Development of a decision making model applied to precision crop management has been completed and is being tested. A decision making model applied to business activity has been completed. This activity provides validity and experience to the methodologies.

Impacts
Given the complex (and often conflicting) sources of information, fuzzy set theory is a useful means to resolve and describe poorly constructed arguments and data. This approach allows the data, the transformation of the data, and the results to be represented in linguistic and qualitative terms.

Publications

• Jones, D.D. and C.L. Jones. 1999. Strategic decision processes in information technology using fuzzy composite programming. Proceedings of the 7th European Congress on Intelligent Techniques and Soft Computing. Aachen, Germany, September 10-13, 1999.