Water Quality Information Center of the National Agricultural Library
Agricultural Research Service, U.S. Department of Agriculture


Expert Systems, Decision Support Systems and Computer-Assisted Instruction for Water Resource Management(II)

 JULY 1993 - SEPTEMBER 1995
 90 citations from AGRICOLA
 by
 Diane Doyle
 Water Quality Information Center
 
 **************************************************************
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 awareness of recent investigations and discussions of a topic and
 is not intended to be in-depth and exhaustive. The inclusion or
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 construed as endorsement or disapproval. 
 
 Send suggestions for electronic bibliographies related to water
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 ************************************************************
 
 EXPERT SYSTEMS, DECISION SUPPORT SYSTEMS AND COMPUTER-ASSISTED
 INSTRUCTION FOR WATER RESOURCE MANAGMENT (II)
 
 
 1. Agricultural management alternatives: GLEAMS model
 simulations.
 Knisel, W. G.; Leonard, R. A.; Davis, F. M. 
 
 Proceedings of the 1989 Summer Computer Simulation Conference 
 July 24-27, 1989, the Stouffer Austin Hotel, Austin, Texas /
 edited by  Joe K Clema ; conference sponsor, the Society for
 Computer Simulation. San Diego, CA : The Society, c1989.. p.
 701-706. 
 Includes references.
 Descriptors: groundwater-pollution; pesticides-; water-quality;
 groundwater-; application-date; irrigation-scheduling;
 planting-date; computer- simulation; simulation-models; georgia-
 Abstract: The GLEAMS model was used to simulate potential
 pesticide loadings to groundwater for alternative management
 strategies. A 50-year climatic record at Tifton, Georgia was used
 to estimate impacts of alternate planting dates, irrigation
 scheduling and depths applied, and  pesticide selection and
 application dates on root zone leaching for two representative
 Coastal Plain soils. Results of simulation are given to 
 demonstrate the utility of comprehensive model applications to
 select among possible alternative systems to maintain or improve
 groundwater  quality.
 NAL Call No.: QA76.9.C65S95-1989
 *****************************************************************
 2. Applying case-based reasoning techniques to the WEPP soil
 erosion model.
 Meyer, C. R.; Flanagan, D. C. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1991. (91-2625) 9 p. 
 Paper presented at the "1991 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 17- 20, 1991, Chicago, Illinois.
 Descriptors: erosion-; simulation-models; expert-systems;
 decision-making
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 3. ARX : a spatial expert system shell for modelling
 environmental problems : user's manual.
 Whigham, P. 
 
 Canberra, ACT, Australia : CSIRO, Institute of Natural Resources
 and Environment, Division of Water Resources, [1993] 43 p..
 "December 1993.".
 S918.A8T44--no.93/21
 *****************************************************************
 4. Automated extraction of drainage network and watershed data
 from digital elevation models.
 Martz, L. W.; Garbrecht, J. 
 
 Water-resour-bull v.29, p.901-908. (1993).
 Includes references.
 Descriptors: drainage-; overland-flow; runoff-; watersheds-;
 hydrological-data; algorithms-; computer-software;
 geomorphology-; oklahoma-;
 digital-elevation-drainage-network-model-dednm
 Abstract: This paper discusses a computer program which extracts
 a number of watershed and drainage network properties directly
 from digital  elevation models (DEM) to assist in the rapid
 parameterization of hydrologic runoff models. The program
 integrates new and established  algorithms to address problems
 inherent in the analysis low-relief terrain from raster DEMs
 similar to those distributed by the U.S. Geological  Survey for
 7.5-minute quadrangles. The program delineates the drainage
 network from a DEM, and determines the Strahler order, total and 
 direct drainage area, length, slope, and upstream and downstream
 coordinates of each channel link. It also identifies the
 subwatershed of each  channel source and of the left and right
 bank of each channel link, and assigns a unique number to each
 network node. The node numbers are  used to associate each
 subwatershed with the channel link to which it drains, and can be
 used to control flow routing in cascade hydrologic  models.
 Program output includes tabular data and raster maps of the
 drainage network and subwatersheds. The raster maps are intended
 for  import to a Geographical Information System where they can
 be registered to other data layers and used as templates to
 extract additional  network and subwatershed information.
 NAL Call No.: 292.9-Am34
 *****************************************************************
 5. CERES-N model predictions of nitrogen mineralized from cover
 crop residues.
 Quemada, M.; Cabrera, M. L. 
 
 Soil-Sci-Soc-Am-j. [Madison, Wis.] Soil Science Society of
 America. July/Aug 1995. v. 59 (4) p. 1059-1065. 
 Includes references.
 Descriptors: cover-crops; crop-residues; decomposition-;
 nutrient-sources; nitrogen-; mineralization-; simulation-models;
 computer-simulation; modification-; carbohydrates-; lignin-;
 cellulose-; stems-; leaves-
 Abstract: Winter annual cover crops, widely used in no-till
 systems, can be an important source of N for the subsequent crop.
 Because many factors  affect net N mineralization from cover crop
 residues, computer models can be powerful tools to predict it.
 The CERES models, which are some  of the most widespread models
 for simulating the whole crop-soil system, have a common submodel
 (CERES-N) that describes N  transformations. The objectives of
 this study were to determine decay rate constants under
 nonlimiting conditions for the carbohydrates and  cellulose pools
 (CARB and CELL) of CERES-N for residues that decompose on the
 soil surface, and to test if two modifications to CERES-N  could
 improve the simulation of N mineralization. The two modifications
 were to: (i) allow the user to vary the relative size of the
 residue pools  (CARB, CELL, and lignin), and (ii) allow stems and
 leaves to decompose separately, having a common point of
 interaction through the  inorganic N pool. Results of a 6-mo
 laboratory incubation experiment with four cover crop residues
 were used to adjust rate constants and test  the effect of model
 modifications. The decay rates obtained were 0.14 and 0.0034 d-1
 for CARB and CELL, respectively. Allowing the user to  vary the
 relative size of residue pools greatly improved the simulation of
 net N mineralized (root mean square error of the model decreased 
 from 1.0 to 0.28 g m-2), whereas modeling the separate
 decomposition of leaves and stems only caused a slight
 improvement in the prediction  of net N mineralized.
 NAL Call No.: 56.9-So3
 *****************************************************************
 6. College students use of a computer authoring system in
 agriculture.
 Legacy, J.; Amadi, N. S.; Elkins, D. M. 
 
 NACTA-j v.38, p.42-44. (1994).
 Includes references.
 Descriptors: agricultural-education;
 computer-assisted-instruction; computer-software; evaluation-;
 college-students; usage-
 NAL Call No.: 275.9-N213
 *****************************************************************
 7. A comparison of traditional worksheet and linear programming
 methods for teaching manure application planning.
 Schmitt, M. A.; Levins, R. A.; Richardson, D. W. 
 
 J-nat-resour-life-sci-educ v.23, p.23-26. (1994).
 Includes references.
 Descriptors: animal-manures; application-to-land; farm-planning;
 decision-making; methodology-; comparisons-;
 computer-programming; management-; nutrient-management
 NAL Call No.: S530.J6
 *****************************************************************
 8. Composting process design computer model.
 Person, H. L.; Shayya, W. H. 
 
 Appl-eng-agric v.10, p.277-283. (1994).
 Includes references.
 Descriptors: composting-; wastes-; management-; operation-;
 systems-analysis; computer-programming; computer-software
 Abstract: A user-friendly computer package, COMPOST, was
 developed as a design, management, and educational tool to assess
 composting system  requirements. The user enters ingredient
 characteristics along with critical operational parameters.
 Output includes the quantity of amendment  required to supply the
 energy needed, the quantity of recycled compost required to
 adjust the initial moisture content, the mixture moisture 
 content, and the carbon-to-nitrogen ratio of the mixture. The
 volume required for active composting and curing is calculated
 along with air flow  rates for oxygen supply, moisture removal,
 and temperature control. The calculations in COMPOST are based on
 the assumption of a  continuous, completely mixed system where
 ingredients are continuously added and product is continuously
 removed. However, calculations  for mixtures of residue,
 amendment, and recycled compost and water also apply to batch
 systems. Peak airflow is calculated to reflect the  requirement
 for a batch system.
 NAL Call No.: S671.A66
 *****************************************************************
 9. Computer-aided conservation planning for the 1985 food
 security act.
 Monson, M. J.; Wollenhaupt, N. 
 
 J-soil-water-conserv v.46, p.260-262. (1991).
 Includes references.
 Descriptors: soil-conservation; computer-software;
 expert-systems; farmland-; cropping-systems; missouri-
 NAL Call No.: 56.8-J822
 *****************************************************************
 10. A computer aided integrated crop management system in winter
 wheat.
 Olesen, J. E.; Andreasen, F.; Andreasen, L. 
 
 Asp-appl-biol p.93-96. (1994).
 In the series analytic: Arable farming under CAP reform / edited
 by J. Clarke, A. Lane, A. Mitchell, M. Ramans and P. Ryan.
 Descriptors: triticum-aestivum; winter-wheat;
 interdisciplinary-research; expert-systems; integrated-systems;
 farm-management; crop-production; denmark-; advisory-systems
 NAL Call No.: QH301.A76
 *****************************************************************
 11. Computer-aided molecular modeling for development of
 biomarkers for human exposure to pesticides.
 Saleh, M. A.; Wallace, C. Jr.; Blancato, J. N. 
 
 ACS-symp-ser p.76-112. (1994).
 In the series analytic: Biomarkers of human exposure to
 pesticides / edited by M.A. Saleh, J.N. Blancato, and C.H.
 Nauman. Paper  presented at the 204th National Meeting of the
 American Chemical Society, August 23-28, 1992, Washington, D.C.
 Descriptors: insecticides-; toxicity-; exposure-; mode-of-action;
 receptors-; binding-site; prediction-; models-; computer-analysis
 Abstract: A molecular modeling and computer graphics study has
 been conducted on a group of insecticides including 50
 bicycloorthocarboxylates,  12 bicyclophosphorus esters and 20
 chlorinated insecticides which are known to have a common mode of
 action, i.e., binding to the gamma- aminobutyric acid chloride
 channel receptor. Three-dimensional steric and electrostatic
 fields were correlated with each compound's  toxicological
 properties using comparative molecular field analysis.
 Toxicological potencies were strongly influenced by the nature
 and  orientation of the substituent groups, molecular volume and
 dipole moment. Also described are models for predicting binding
 affinity to the  receptor and for predicting acute mammalian
 toxicity. These chemicals may serve as useful probes for
 elucidation of the topography of the  binding sites of the
 receptor and provide leads in the design of new compounds with
 more potent insecticidal activity and selectivity.
 NAL Call No.: QD1.A45
 *****************************************************************
 12. Computer anxiety and other factors preventing computer use
 among United States secondary agricultural educators.
 Fletcher, W. E.; Deeds, J. P. 
 
 J-agric-educ v.35, p.16-21. (1994).
 Includes references.
 Descriptors: agricultural-education; teachers-;
 computer-assisted-instruction; secondary-education; attitudes-;
 usage-; usa-
 NAL Call No.: S530.A4
 *****************************************************************
 13. Computer-assisted teaching: LANDCADD: professionalizing
 agricultural graphic applications in the classroom.
 Kirby, B. M. 
 
 Agric-Educ-Mag v.65, p.22-23. (1992).
 Descriptors: agricultural-education;
 computer-assisted-instruction; computer-software;
 computer-graphics; design-; planning-; graphs-
 NAL Call No.: 275.8-AG8
 *****************************************************************
 14. A computer controlled drainage and water quality field
 experimental system.
 Tait, R.; Madramootoo, C. A.; Enright, P. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1993. (93-3531) 16 p. 
 Paper presented at the "1993 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 14- 17, 1993, Chicago, Illinois.
 Descriptors: water-quality; drainage-; subsurface-irrigation;
 runoff-; computer-simulation; computer-analysis; quebec-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 15. Computer decision aids for reducing herbicide use.
 Coble, H. D. 
 
 Proc-annu-meet-Northeast-Weed-Sci-Soc. College Park, Md. : The
 Society. 1994. v. 48 p. 155-159. 
 Meeting held Janurary 3-6, 1994, Baltimore, Maryland.
 Descriptors: low-input-agriculture; herbicides-;
 application-rates; weed-control; chemical-control;
 decision-making; computer-software; herb-computer-software
 NAL Call No.: 79.9-N814
 *****************************************************************
 16. Computer multimedia instruction versus traditional
 instruction in agriculture.
 Marrison, D. L.; Tao, B. W.; Frick, M. J. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1993. (933544) 9 p. 
 Paper presented at the "1993 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 14- 17, 1993, Chicago, Illinois.
 Descriptors: agricultural-economics; students-;
 academic-achievement; computer-assisted-instruction; traditions-;
 comparisons-; indiana-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 17. Coupling geographic information systems and models for weed
 control and groundwater protection.
 Wilson, J. P.; Inskeep, W. P.; Rubright, P. R.; Cooksey, D.;
 Jacobsen, J. S.; Snyder, R. D. 
 
 Weed-technol v.7, p.255-264. (1993).
 Paper presented at the "Symposium on Geographic Information
 Systems," February 11, 1992, Orlando, Florida.
 Descriptors: weeds-; centaurea-maculosa; euphorbia-esula;
 weed-control; herbicide-residues; groundwater-; contamination-;
 geographical-information- systems; mathematical-models;
 computer-simulation; montana-
 NAL Call No.: SB610.W39
 *****************************************************************
 18. DD50 computerized rice management program.
 Slaton, N. A.; Helms, R. S.; Wilson, C. E. Jr.; Wells, B. R. 
 
 FSA-Univ-Ark-Syst-Coop-Ext-Serv. [Little Rock, Ark.] :
 Cooperative Extension Service,. June 1993. (2124) 4 p. 
 Insubseries: Computer Technical Series.
 Descriptors: oryza-sativa; mathematical-models; decision-making;
 growth-stages; herbicides-; application-date; air-temperature;
 arkansas-
 NAL Call No.: S37.F72
 *****************************************************************
 19. A decision support system for evaluating the effects of
 alternative farm management systems on water quality and
 economics.
 Yakowitz, D. S.; Stone, J. J.; Lane, L. J.; Heilman, P.;
 Masterson, J.; Abolt, J.; Imam, B. 
 
 Water-sci-technol v.28, p.47-54. (1993).
 Paper presented at the IAWQ First International Conference on
 "Diffuse (Nonpoint) Pollution: Sources, Prevention, Impact,
 Abatement."  September 19-24, 1993, Chicago, Illinois.
 Descriptors: water-quality; farm-management; systems-;
 decision-making; support-systems; farm-income; simulation-models;
 arizona-
 NAL Call No.: TD420.A1P7
 *****************************************************************
 20. Decision support system for groundwater quality assessment.
 Embleton, K. M.; Engel, B. A. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1991. (917578) 6 p. 
 Paper presented at the "1991 International Winter Meeting
 sponsored by The American Society of Agricultural Engineers,"
 December 17- 20, 1991, Chicago, Illinois.
 Descriptors: water-quality; groundwater-; expert-systems
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 21. A decision support system for pesticide use management.
 Arjoon, D.; Kok, R.; Prasher, S. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1993. (933043) 7 p. 
 Paper presented at the "1993 International Summer Meeting
 sponsored by The American Society of Agricultural Engineers,"
 June 20-23,  1993, Spokane, Washington.
 Descriptors: pesticides-; groundwater-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 22. A decision support system for wetland management on national
 wildlife refuges.
 Sojda, R. S.; Dean, D. J.; Howe, A. E. 
 
 AI-appl v.8, p.44-50. (1994).
 Includes references.
 Descriptors: nature-reserves; wildlife-; wetlands-; management-;
 support-systems; geographical-information-systems;
 expert-systems; usa-
 NAL Call No.: QA76.76.E95A5
 *****************************************************************
 23. Determining wastewater user service charge rates : a step by
 step manual.
 Farmer, H.;  Finane, W. J.;  Fitzgerald, S. H.; United States.
 Environmental Protection Agency. Office of Water. 
 
 Washington, D.C. : U.S. Environmental Protection Agency, Office
 of Water, 1992. 29 p. : ill.  2 computer disks..
 Cover title.
 Descriptors:
 Sewage-disposal-plants-United-States-Fees-Computer-programs;
 User-charges-United-States-Computer-programs;
 Financial-management- Computer-programs
 NAL Call No.: HD4477.F37-1992
 *****************************************************************
 24. Development and use of a system for predicting the
 macroinvertebrate fauna in flowing waters.
 Wright, J. F. 
 
 Aust-j-ecol v.20, p.181-197. (1995).
 In the special issue; Use of biota to assess water quality /
 edited by R.H. Norris, B.T. Hart, M. Finlayson and K.R. Norris.
 Descriptors: aquatic-insects; insect-communities;
 community-ecology; computer-software; rivers-; streams-;
 water-pollution; water-quality; indicator- species;
 biological-indicators; uk-; rivpacs-; pollution-indicators
 NAL Call No.: QH540.A8
 *****************************************************************
 25. Development of a biologically-based system for detection and
 tracking of airborne herbicides.
 Al Khatib, K.; Mink, G. I.; Reisenauer, G.; Parker, R.; Westberg,
 H.; Lamb, B. 
 
 Weed-technol v.7, p.404-410. (1993).
 Includes references.
 Descriptors: drift-; detection-; nontarget-effects; symptoms-;
 phytotoxicity-; monitoring-; air-pollutants; movement-;
 computer-simulation; mathematical- models; phaseolus-vulgaris;
 lens-culinaris; pisum-sativum; bromoxynil-; chlorsulfuron-;
 dicamba-; glyphosate-; metsulfuron-; paraquat-; 2,4-d-;
 tribenuron-; sulfonylurea-herbicides; thifensulfuron-
 NAL Call No.: SB610.W39
 *****************************************************************
 26. Development of a decision support system for prioritization
 of multimedia dischargers.
 Keyes, A. M.; Palmer, R. N. 
 
 Environ-Manage v.17, p.601-612. (1993).
 Includes references.
 Descriptors: water-pollution; air-pollution; hazards-; wastes-;
 risk-; environmental-protection; government-organizations;
 regulations-; environmental- impact; u; s;
 -environmental-protection-agency
 NAL Call No.: HC79.E5E5
 *****************************************************************
 27. Development of an expert system for the identification and
 control of weeds in wheat, triticale, barley and oat crops.
 Pasqual, G. M. 
 
 Comput-electron-agric v.10, p.117-134. (1994).
 Includes references.
 Descriptors: triticum-aestivum; hordeum-vulgare; avena-sativa;
 expert-systems; weed-control; identification-; australia-
 NAL Call No.: S494.5.D3C652
 *****************************************************************
 28. DIAGNOSIS--a novel, multimedia, computer-based approach to
 training crop protection practitioners.
 Stewart, T. M.; Blackshaw, B. P.; Duncan, S.; Dale, M. L.;
 Zalucki, M. P.; Norton, G. A. 
 
 Crop-prot v.14, p.241-246. (1995).
 Includes references.
 Descriptors: crops-; plant-protection; plant-pests;
 plant-diseases; training-; teaching-materials; computer-software
 Abstract: The multimedia computer package DIAGNOSIS provides a
 training aid to students of crop protection for pest and disease
 diagnosis. The  program simulates field and laboratory scenarios,
 in which students must actively seek clues and interpret
 observations on the cause of plant  problems. Output may consist
 of text graphics and video. The software allows the simple
 construction of local scenarios by individual tutors.  Once
 students have recorded their diagnosis, justification and
 recommendations for action, they receive an automatic debriefing
 on their  problem-solving approach. Student input is recorded to
 disk for later assessment by the tutor.
 NAL Call No.: SB599.C8
 *****************************************************************
 29. The effect of agricultural students' learning styles on
 academic achievement and their perceptions of two methods of
 instruction.
 Marrison, D. L.; Frick, M. J. 
 
 J-agric-educ v.35, p.26-30. (1994).
 Includes references.
 Descriptors: college-students; learning-ability;
 academic-achievement; teaching-methods;
 computer-assisted-instruction; lectures-; comparisons-;
 agricultural-education
 NAL Call No.: S530.A4
 *****************************************************************
 30. Evaluation of a farmstead drinking water quality decision
 support system.
 Embleton, K. M.; Engel, B. A.; Jones, D. D. 
 
 Appl-eng-agric v.10, p.863-869. (1994).
 Includes references.
 Descriptors: drinking-water; water-quality; water-pollution;
 risk-; assessment-; farmland-; farm-management; decision-making;
 expert-systems
 Abstract: A prototype decision support system (DSS) has been
 developed to provide information concerning the influence of
 common farmstead  management practices and site conditions on the
 quality of drinking water from private wells. This article
 describes prototype development and  testing procedures. Farmers,
 college students, agricultural extension agents, and risk
 assessment experts participated in the testing. Results  indicate
 that the DSS was more accurate and user friendly than the
 paper-based assessment tool from which the computer program
 evolved.
 NAL Call No.: S671.A66
 *****************************************************************
 31. Experimental evaluation of the effectiveness of a
 computer-assisted instructional unit on sustainable agriculture.
 Kahler, A. A. 
 
 J-Agric-Educ v.34, p.77-83. (1993).
 Includes references.
 Descriptors: agricultural-education; sustainability-;
 computer-assisted-instruction; environmental-education;
 secondary-education; iowa-
 NAL Call No.: S530.A4
 *****************************************************************
 32. Expert evaluation system for assessing field vulnerability to
 agrochemical compounds in Mediterranean regions.
 Rosa, D. d. la.; Moreno, J. A.; Garcia, L. V. 
 
 J-agric-eng-res v.56, p.153-164. (1993).
 Includes references.
 Descriptors: soil-pollution; groundwater-pollution; pollutants-;
 agricultural-chemicals; expert-systems; evaluation-; nitrates-;
 pesticides-; leaching-; soil- properties; microcomputers-;
 spain-; management-system-criteria;
 automated-land-evaluation-system;
 computer-based-expert-knowledge-system
 Abstract: An expert evaluation system (named ARENAL) has been
 developed using a knowledge-based approach thatallows
 estimation of the  relative vulnerability of soil and groundwater
 to diffuse agrochemicalcontamination.  ARENAL interprets
 groundwater vulnerability at the  field scale especially from  
 nitrate and pesticide leaching.  Soil properties and related
 agricultural land-featuresare-combined with  management system
 criteria for Mediterranean regions.  The Automated Land  
 Evaluation System (ALES) was used to acquire this computer-
 captured expert knowledge and allieddata.  The ARENAL expert
 system uses basic input data or "key" parameters from existing
 soil and  land  survey information.  Such an evaluation approach
 can be the basis for estimation of theenvironmental impact of
 agricultural activities, with  reference to chemical degradation
 of soiland water resources.
 NAL Call No.: 58.8-J82
 *****************************************************************
 33. Expert system for fertilization management of rice.
 Chai, K. L.; Costello, T. A.; Wells, B. R.; Norman, R. J. 
 
 Appl-eng-agric v.10, p.849-855. (1994).
 Includes references.
 Descriptors: oryza-sativa; flooded-rice; crop-management;
 fertilizers-; expert-systems; ricefertility-; nutrient-management
 Abstract: A computer-based decision support system called Rice
 Fertility has been developed to provide information and
 recommendations on  efficient utilization of fertilizer for the
 production of flooded rice in Arkansas. Conventional information
 sources regarding timing and rate of  fertilizer applications
 were consolidated in developing a computerbased tool that
 generated recommendations quickly for many situations. The  text
 of each recommendation was formulated to be sensitive to the
 tactical context of the individual problem scenario. The inputs
 to the expert  system included cultural system, rice cultivar,
 rice growth stage, flood status, soil texture, and soil pH.
 Appropriate recommendations were  generated for rates of early
 nitrogen (N), maximum tillering N, midseason N, and other soil
 fertility problems involving salinity, liming,  phosphorus,
 potassium, zinc, and/or sulfur. The system logic was successfully
 validated in 29 of 31  sample scenarios tested. The set of sample 
 scenarios was defined using the Arkansas Rice Research
 Verification Trials as a balanced source of fertilizer decisions
 made in growers' fields.A method of classifying the results of
 the validation testing was useful in evaluating the software.
 NAL Call No.: S671.A66
 *****************************************************************
 34. An expert system for soil erosion mitigation in logging
 operations on steep land.
 Ross, J. 
 
 AI-appl v.7, p.69-70. (1993).
 Includes references.
 Descriptors: erosion-; logging-; slopes-; expert-systems;
 new-south-wales
 NAL Call No.: QA76.76.E95A5
 *****************************************************************
 35. An expert system linked with a GIS database for spatially
 variable fertilizer application.
 He, B.; Peterson, C. L.; Mahler, R. L. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1992. (92-3556) 23 p. 
 Includes references.
 Descriptors: fertilizers-; application-rates; expert-systems;
 computer-software; simulation-models; maps-; idaho-;
 geographical-information-system
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 36. An expert systems approach for assessing the potential for
 pesticide contamination of ground water.
 Crowe, A. S.; Mutch, J. P. 
 
 Ground-water. Dublin, Ohio : Ground Water Pub. Co. May/June 1994.
 v. 32 (3) p. 487-498. 
 Includes references.
 Descriptors: pesticides-; groundwater-pollution; expert-systems;
 assessment-; models-
 NAL Call No.: TD403.G7
 *****************************************************************
 37. Expert systems, decision support systems and
 computer-assisted instruction for water resource management:
 January 1985 - June 1993.
 Emmert, B.; Makuch, J. 
 
 Quick-bibliogr-ser. Beltsville, Md., National Agricultural
 Library. Aug 1993. (93-62)  64 p. 
 Descriptors: water-management; support-systems; expert-systems;
 computer-assisted-instruction; bibliographies-
 NAL Call No.: aZ5071.N3
 *****************************************************************
 38. Expert systems for evaluating physicochemical property
 values. 1. Aqueous solubility.
 Heller, S. R.; Bigwood, D. W.; May, W. E. 
 
 J-chem-inf-comput-sci v.34, p.627-636. (1994).
 Includes references.
 Descriptors: pesticide-residues; chemical-analysis;
 computer-software; expert-systems; physicochemical-properties;
 solubility-; water-
 Abstract: Providing consistent data evaluation is critical to
 scientific studies.  An expert system for evaluating the efficacy
 of the reported  methodology for determining aqueous solubility
 is described and compared with two other similar manual data
 quality evaluation systems. The  expert system, SOL, is a
 post-peer review filter for data evaluation.  SOL has been
 designed to run on any IBM-PC compatible computer using  the
 CLIPS public domain expert system shell.
 NAL Call No.: 241.64-J82
 *****************************************************************
 39. An exploration of the economics of farm management
 alternatives to improve water quality.
 Heilman, P.; Yakowitz, D. S.; Stone, J. J.; Kramer, L. A.; Lane,
 L. J.; Imam, B. 
 
 Application of advanced information technologies  effective
 management of natural resources  proceedings of the 18-19 June
 1993  Conference, Spokane, Washington /. St. Joseph, Mich. :
 American Society of Agricultural Engineers, c1993.. p. 194-205. 
 Includes references.
 Descriptors: water-quality; pollutants-; farm-management;
 farm-income; decision-making; simulation-models; usda-; iowa-;
 prototype-decision-support-system; agricultural-research-service
 NAL Call No.: GE5.A66-1993
 *****************************************************************
 40. Farm application of the model-based-reasoning system
 GOSSYM/COMAX.
 Landivar, J. A.; Wall, G. W.; Siefker, J. H.; Baker, D. N.;
 Whisler, F. D.; McKinion, J. M. 
 
 Proceedings of the 1989 Summer Computer Simulation Conference 
 July 24-27, 1989, the Stouffer Austin Hotel, Austin, Texas /
 edited by  Joe K Clema ; conference sponsor, the Society for
 Computer Simulation. San Diego, CA : The Society, c1989.. p.
 688-694. 
 Includes references.
 Descriptors: gossypium-hirsutum; crop-production;
 plant-physiology; phenology-; equations-; computer-simulation;
 simulation-models; growth-models
 Abstract: The GOSSYM/COMAX system, a decision aid for cotton crop
 management, has been tested over the last five years on research
 and  commercial farms across the cotton belt of the United
 States. GOSSYM simulates the major biotic and abiotic processes
 which influence  growth, development and yield of cotton.
 Phenological and physiological rate equations derived from
 Soil-Plant-Atmosphere-Research (SPAR)  experimental databases are
 crucial to the model development process. COMAX is an expert
 system environment that provides data management  and a user
 friendly interface to GOSSYM. GOSSYM/COMAX is more properly
 called a model-based-reasoning system rather than an expert 
 system. This is due primarily to COMAX's use of rules to control
 its operation while the important knowledge about cotton resides
 in  GOSSYM. The rules used by COMAX contain the expert knowledge
 of the model builders on how to use GOSSYM and how to interpret
 the  model results. The belt-wide farm management test has
 provided useful information on designing an enhanced user
 interface and developing  improved rules to optimize management
 inputs.
 NAL Call No.: QA76.9.C65S95-1989
 *****************************************************************
 41. Farm-level economic and environmental impacts of eastern Corn
 Belt cropping systems.
 Foltz, J. C.; Lee, J. G.; Martin, M. A. 
 
 J-prod-agric v.6, p.290-296. (1993).
 Includes references.
 Descriptors: zea-mays; medicago-sativa; glycine-max;
 microeconomic-analysis; economic-impact; alternative-farming;
 environmental-impact; rotations-; continuous-cropping;
 simulation-models; computer-simulation; erosion-; runoff-;
 pesticides-; water-pollution; corn-belt-states-of-usa;
 epic-simulation-model; gleams-simulation-model
 NAL Call No.: S539.5.J68
 *****************************************************************
 42. Geophysics advisor expert system. Version 2.0.
 Olhoeft, G. R.; Mazzella, A. T.; Geological Survey (U.S.). 
 
 [Denver, Colo.? : U.S. Geological Survey?] ; Springfield, VA :
 Reproduced by NTIS, 1992? 1 computer disk  1 booklet (21 p. ; 28
 cm.) .
 Title from title screen.
 Descriptors: Geophysics-Computer-programs;
 Hazardous-waste-sites-Computer-programs
 NAL Call No.: QE501.O44-1992
 *****************************************************************
 43. Groundwater quality assessment expert system package.
 Embleton, K. M.; Engel, B. A. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1992. (927028) 14 p. 
 Paper presented at the "1992 International Summer Meeting
 sponsored by the American Society of Agricultural Engineers,"
 June 21-24,  1992, Charlotte, North Carolina.
 Descriptors: water-quality; expert-systems; risk-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 44. Guide to WEEDING version 1.0: a Weed Ecology and Economic
 Decision making INstructional Game.
 Wiles, L. J.; Wilkerson, G. G.; Buol, G. S.; Coble, H. D. 
 
 Res-rep-NC-State-Univ,-Dep-Crop-Sci. Raleigh : Dept. of Crop
 Science, N.C. State of the University at Raleigh, 1964-. Apr
 1992. (136)  48 p. 
 Includes references.
 Descriptors: glycine-max; weed-control; decision-making;
 simulation-models; computer-assisted-instruction; teaching-;
 materials-; educational-games; north-carolina
 NAL Call No.: 100-N8122
 *****************************************************************
 45. A hypermedia lecture aid for engineering education.
 Beck, H. W.; Smerage, G. H. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1993. (933541) 8 p. 
 Paper presented at the "1993 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 14- 17, 1993, Chicago, Illinois.
 Descriptors: engineering-; computer-assisted-instruction;
 databases-; teaching-materials; microcomputers-; models-;
 electronic-blackboard
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 46. An information management technology program for ex ante
 nutrient loss reduction from farms.
 Lemberg, B.; McSweeney, W. T.; Lanyon, L. E. 
 
 J-Environ-Qual v.21, p.574-578. (1992).
 Includes references.
 Descriptors: dairy-farms; fertilizers-;
 fertilizer-requirement-determination; nutrients-;
 losses-from-soil; use-efficiency; farm-management; environmental-
 impact; economic-impact; information-systems; computer-software;
 water-resources; environmental-protection
 Abstract: Reducing nutrient losses from farms to the environment
 can be done before or after the nutrients have been applied to
 the fields. If  effective best management practices can be
 implemented before nutrients are applied (ex ante), difficult and
 uncertain remedial management  practices can be avoided. The
 relative environmental and economic consequences of an
 information management technology program were  compared under
 two contrasting water resource protection perspectives by linear
 programming simulation of a dairy farm. The information  program
 was based on measuring the amount of materials transferred to and
 from the fields as crops and manure, and the sampling and
 analyses  of those materials. Potential N losses to the
 environment were reduced substantially and costs of the
 information management program were  generally more than offset
 by the savings in fertilizer expenditures compared to the outcome
 when no credit was given to manure nutrients in  the
 fertilization of farm crops. Exacting requirements for nutrient
 utilization under a restrictive water resource protection
 perspective resulted in  only a fraction of the total manure
 produced being spread on the farm fields, however. The negative
 economic impart of this limitation was  potentially much greater
 than the costs to implement the information management technology
 program. Standards for both the extent of the  information
 required to adequately meet the environmental expectations and
 the acceptable range of the expectations must be established if
 the  management practice is to be feasible and successful.
 NAL Call No.: QH540.J6
 *****************************************************************
 47. Information requirements and critical success factors for
 corn/soybean decision support systems.
 Barrett, J. R.; Thompson, T. L.; Campbell, W. P. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1991. (91-7501) 8 p. 
 Paper presented at the "1991 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 17- 20, 1991, Chicago, Illinois.
 Descriptors: maize-; soybeans-; crop-production; decision-making;
 support-systems; expert-systems
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 48. An instrumented, field-scale research facility for drainage
 and water quality studies.
 Tait, R.; Madramootoo, C. A.; Enright, P. 
 
 Comput-electron-agric v.12, p.131-145. (1995).
 Includes references.
 Descriptors: drainage-; irrigation-systems; water-quality;
 nitrogen-fertilizers; field-experimentation; cropping-systems;
 computer-software; runoff-; nitrates-; data-collection; quebec-;
 subirrigation-; soulanges-county,-quebec
 NAL Call No.: S494.5.D3C652
 *****************************************************************
 49. Integrated water-fertilizer-pest management for
 environmentally sound crop production.
 Fouss, J. L.; Willis, G. H. 
 
 Environmentally sound agriculture  proceedings of the second
 conference  20-22 April 1994 / p.53-61. (1994).
 Includes references.
 Descriptors: agricultural-land; crop-production;
 high-water-tables; water-management; soil-management;
 pest-management; integrated-systems; water- pollution;
 pollution-control; computer-simulation; simulation-models;
 projects-; usa-; lower-mississippi-valley
 NAL Call No.: S589.7.E57-1994
 *****************************************************************
 50. Integrated wheat crop management based on generic task
 knowledge-based systems and CERES numerical simulation.
 Kamel, A.; Schroeder, K.; Sticklen, J.; Rafea, A.; Salah, A.;
 Schulthess, U.; Ward, R.; Ritchie, J. 
 
 AI-appl v.9, p.17-28. (1995).
 Includes references.
 Descriptors: triticum-aestivum; irrigated-conditions;
 crop-management; crop-yield; expert-systems; simulation-models;
 ceres-wheat-model
 NAL Call No.: QA76.76.E95A5
 *****************************************************************
 51. Integration of geographic information systems and a computer
 model to evaluate impacts of agricultural runoff on water
 quality.
 He, C.; Riggs, J. F.; Kang, Y. T. 
 
 Water-resour-bull v.29, p.891-900. (1993).
 Includes references.
 Descriptors: runoff-; river-water; water-pollution;
 water-quality; nitrogen-; phosphorus-; simulation-models;
 geographical-information-systems; michigan-;
 geographic-resource-analysis-support-system-grass;
 grass-waterworks;
 agricultural-nonpoint-source-pollution-model-agnps; cass-river;
 saginaw-bay; best-management-practices
 Abstract: This study integrates an Agricultural Non-Point Source
 Pollution Model (AGNPS), the Geographic Resource Analysis Support
 System  (GRASS) (U.S. Army Corps of Engineers, 1987), and GRASS
 WATERWORKS (a hydrologic modeling tool box being developed at the 
 Michigan State University Center for Remote Sensing) to evaluate
 the impact of agricultural runoff on water quality in the Cass
 River, a  subwatershed of Saginaw Bay. AGNPS is used to estimate
 the amounts, origin, and distribution of sediment, nitrogen (N),
 and phosphorus (P)  in the watershed. GRASS and GRASS WATERWORKS
 are used to generate parameters needed for AGNPS from digital
 maps, which include  soil association, land use, watershed
 boundaries, water features, and digital elevation. Outputs of the
 model include spatially distributed  estimates of volume and peak
 runoff, overland and channel erosion, sediment yields, and
 concentrations of nitrogen and phosphorus.  Management scenarios
 are explored in the AGNPS model to minimize sedimentation and
 nutrient loading. Scenarios evaluated include  variations in crop
 cover, tillage methods, and other agricultural management
 practices. In addition, areas vulnerable to erosion are
 identified for  best management practices.
 NAL Call No.: 292.9-Am34
 *****************************************************************
 52. Interfacing issues for GOSSYM/COMAX/WHIMS.
 McKinion, J. M.; Olson, R. L. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1992. (923555) 11 p. 
 Paper presented at the "1992 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 15- 18, 1992, Nashville, Tennessee.
 Descriptors: gossypium-hirsutum; simulation-models; growth-;
 crop-yield; expert-systems; databases-; crop-management
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 53. It boggles the mind.
 Odell, K. S. 
 
 Agric-educ-mag. Henry, Ill. : The Agricultural Education
 Magazine, Inc., 1980-. Aug 1994. v. 67 (2) 5, 10. 
 Descriptors: educational-technology;
 computer-assisted-instruction; agricultural-education
 NAL Call No.: 275.8-Ag8
 *****************************************************************
 54. A knowledge based approach to extract input data from GIS.
 Srinivasan, R.; Engel, B. A. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1991. (917045) 6 p. 
 Paper presented at the "1991 International Summer Meeting
 sponsored by the American Society of Agricultural Engineers,"
 June 23-26,  1991, Albuquerque, New Mexico.
 Descriptors: expert-systems; pollution-; models-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 55. Knowledge-based system for environmental design of stream
 modifications.
 Shields, F. D. Jr.; Aziz, N. M. 
 
 Appl-Eng-Agric v.8, p.553-562. (1992).
 Includes references.
 Descriptors: watershed-management; streams-; modification-;
 expert-systems; erosion-control; flood-control
 Abstract: A knowledge-based, microcomputer software package was
 developed for preliminary selection of environmental features for
 use with  streambank protection projects, straightened and
 enlarged channels, and flood control levees. The system contains
 a module for each of the  three major alteration types: bank
 protection, levees, and channels. Each module queries the user
 for information regarding environmental  factors to be protected
 and a description of the project setting, with the internal logic
 configured to minimize the number of questions asked.  System
 output consists of a list of environmental design features
 suitable for the specific location and descriptive information.
 Help screens  explain why certain questions are asked, define
 terms, and suggest responses or sources of information. At the
 conclusion of a consultation,  additional help screens may be
 displayed that provide a discussion of each recommended feature,
 a list of existing projects that incorporate the  feature, and a
 bibliography. The streambank protection module screens a master
 list of 20 methods based on the dominant erosion mechanisms 
 operative at the project site, and the channel module performs a
 rough channel stability assessment using regime equations. The
 latest version of  the software aids in feature selection, but
 does not design channel alterations. However, the software
 interfaces with routines that perform basic  hydraulic
 computations (e.g., composite roughness, normal depth, riprap
 size) for steady flow in order to allow users to quickly evaluate 
 feasibility of in-channel environmental features. A survey of
 users indicated that the package has been used by entry-level and
 experienced  professionals to perform a limited range of
 specialized tasks. Seventy-four percent of the users described
 the software as a useful instrument for  planning and preliminary
 design.
 NAL Call No.: S671.A66
 *****************************************************************
 56. A knowledge-based system for insecticide management for rice
 crops.
 Gupta, C. P.; Suryanto, H. 
 
 Trans-A-S-A-E v.36, p.585-591. (1993).
 Includes references.
 Descriptors: oryza-sativa; insect-control; insecticides-;
 sprayers-; computer-software; droplet-size; mathematical-models;
 tropical-asia; basic-computer-program
 Abstract: A knowledge-based system was developed using an expert
 system shell to help farmers in insecticide management for rice
 crops for  tropical Asian countries. It has 72 rules for
 recommending insecticides and an external program written in
 BASIC for selecting sprayers.  Insecticides are recommended based
 on the type of insect, symptoms, economic threshold, cost, and
 the effectiveness of chemical. An attempt  was made to face this
 system with a real problem of rice leaf folder. Field experiments
 have been performed to evaluate the program's  recommendations
 for controlling the rice leaf folder. The program should be
 expanded for other major rice insects before it is used by
 farmers.  An external program for sprayer selection has been
 developed. Sprayer selection is based on droplet size, deposition
 efficiency, capacity, and  operating cost. Laboratory and field
 experiments using manually carried sprayers were to provide data
 required by the user.
 NAL Call No.: 290.9-AM32T
 *****************************************************************
 57. A knowledge-based system linked to AGNPS/GRASS interface.
 Mohite, M.; Whittaker, A. D.; Srinivasan, R. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1993. (933041) 20 p. 
 Paper presented at the "1993 International Summer Meeting
 sponsored by The American Society of Agricultural Engineers,"
 June 20-23,  1993, Spokane, Washington.
 Descriptors: erosion-; watersheds-; expert-systems
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 58. Knowledge-based systems for pest management: an applicat
 ions-based review.
 Edwards Jones, G. 
 
 Pestic-sci v.36, p.143-153. (1992).
 Paper presented at the symposium, "Artificial Intelligence
 Methods in Drug and Pesticide Research," March 3, 1992, London,
 UK.
 Descriptors: pest-management; computer-software; problem-solving;
 technology-transfer; research-support; literature-reviews; uk-;
 artificial-intelligence
 Abstract: Since the first application of artificial intelligence
 (AI) techniques to agricultural problems in 1982 nearly 300
 further systems have been  reported, of which 50 have been
 developed for pest management. Typically, these systems perform
 one of three tasks; diagnostics, treatment  prescription or
 strategy development. The characteristics of all three types of
 system are discussed with reference to several examples. Although 
 these examples serve to emphasise the power of AI techniques for
 aiding management decisions, few existing agricultural
 knowledge-based  systems utilise this potential to the full, and
 as yet there has not been a widespread adoption of this
 technology by practising pest managers.  Despite the failure to
 transfer this technology from the laboratory to the field, the
 potential of knowledge-based systems is widely recognised. 
 However, further development of this technology for agricultural
 use within the UK is likely to be hindered by funding
 constraints.
 NAL Call No.: SB951.P47
 *****************************************************************
 59. Lake Okeechobee agricultural decision support system
 (LOADSS).
 Lal, H.; Fonyo, C.; Negahban, B.; Boggess, W. G.; Kiker, G. A.;
 Campbell, K. L. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1991. (91-2623) 23 p. 
 Paper presented at the "1991 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 17- 20, 1991, Chicago, Illinois.
 Descriptors: water-pollution; water-quality; models-;
 geographical-information-systems; decision-making;
 support-systems; florida-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 60. Leading the commonwealth toward tomorrow.
 Breeze, P. R. ed.; Brinlee, B. ed. 
 
 Publication collection, Virginia Cooperative Extension Service.
 1991. (490-103) 18 p. 
 Includes references.
 Descriptors: cooperative-extension-service; programs-;
 food-safety; lymantria-dispar; integrated-pest-management;
 hydroponics-; fish-culture; environmental-protection; education-;
 zoning-; financial-planning; solid-wastes; youth-programs;
 microcomputers-; computer-software; agricultural-economics;
 dairy-education; geographical-information-systems; virginia-;
 virginia-geographic-information-system; solid-waste-management;
 women's-financial-information-program;
 crop-rotation-planning-system- crops;
 appalachian-integrated-pest-management-project
 NAL Call No.: S544.3.V8V52
 *****************************************************************
 61. Learning and knowledge refinement of a barley management
 expert system.
 Parente, A. C.; Broner, I.; Comstock, C. S. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1991. (91-7019) 14 p. 
 Paper presented at the "1991 International Summer Meeting
 sponsored by the American Society of Agricultural Engineers,"
 June 23-26,  1991, Albuquerque, New Mexico.
 Descriptors: barley-; education-; expert-systems; crop-management
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 62. Making the right choices.
 Osborne, E. 
 
 Agric-educ-mag v.67, p.3, 10. (1994).
 Descriptors: educational-technology; agricultural-education;
 computer-assisted-instruction
 NAL Call No.: 275.8-Ag8
 *****************************************************************
 63. Managing water resources: the Institute of Water Research.
 Peterson, S. 
 
 Futures v.11, p.20-22, 24. (1993).
 Descriptors: water-management; water-pollution;
 research-projects; computer-techniques; information-systems;
 community-education; michigan-
 NAL Call No.: S75.F87
 *****************************************************************
 64. Mapping contaminant plumes using geophysical methods.
 Brune, D. E.; Zheng, M. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Summer 1993. (934015) 28 p. 
 Paper presented at the "1993 International Summer Meeting
 sponsored by The American Society of Agricultural Engineers," and
 The  Canadian Society of Agricultural Engineering," June 20-23,
 1993, Spokane, Washington.
 Descriptors: animal-wastes; waste-disposal-sites; lagoons-;
 groundwater-; water-quality; soil-; conductivity-; pollution-;
 expert-systems
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 65. Merging your classroom onto the information superhighway.
 Murphy, T. 
 
 Agric-educ-mag v.67, p.6-8. (1994).
 Includes references.
 Descriptors: educational-technology;
 computer-assisted-instruction; agricultural-education; internet-;
 on-line-services
 NAL Call No.: 275.8-Ag8
 *****************************************************************
 66. Monitoring wheat for plant N, P, and K content and fertilizer
 management.
 Adams, D.; University of Arkansas (System). Cooperative Extension
 Service. 
 
 Little Rock, Ark. : University of Arkansas, Cooperative Extension
 Service, 1985. 16 p..
 Includes bibliographical references (p. 10-11).
 Descriptors: Wheat-Yield-Computer-programs
 NAL Call No.: SB191.W5M58--1985
 *****************************************************************
 67. N-expert--a decision support system for vegetable
 fertilization in the field.
 Fink, M.; Scharpf, H. C. 
 
 Acta-hortic p.67-74. (1993).
 Paper presented at the Workshop on Ecological Aspects of
 Vegetable Fertilization in Integrated Crop Production in the
 Field, September  7-11, 1992, Wadenswil, Switzerland.
 Descriptors: vegetables-; nitrogen-fertilizers;
 application-rates; computer-software; germany-
 NAL Call No.: 80-Ac82
 *****************************************************************
 68. Nitrogen fertilizer and the environment: the role of crop
 modelling in management and impact assessment.
 Thornton, P. K. 
 
 Proc-annu-meet-Fert-Ind-Round-Table p.150-157. (1993).
 Includes references.
 Descriptors: crops-; simulation-models; computer-simulation;
 mathematical-models; fertilizer-requirement-determination;
 decision-making; environmental-impact; assessment-;
 crop-management
 NAL Call No.: 57.09-F41
 *****************************************************************
 69. NPK$PLUS: a computer program to examine agronomic and
 economic value of alternative fertilizer rates.
 Johnson, G. V.; Nofziger, D. L. 
 
 J-Prod-Agric v.5, p.415-420. (1992).
 Includes references.
 Descriptors: fertilizers-; lime-; application-rates;
 decision-making; computer-software; economic-analysis;
 crop-management
 NAL Call No.: S539.5.J68
 *****************************************************************
 70. Parameter adjustment to a crop model using a sensor-based
 decision support system.
 Thomson, S. J.; Peart, R. M.; Mishoe, J. W. 
 
 Trans-A-S-A-E v.36, p.205-213. (1993).
 Includes references.
 Descriptors: arachis-hypogaea; crop-management; decision-making;
 expert-systems; growth-models; sensors-; simulation-models;
 soil-water; comax-software; modvex-software
 Abstract: A knowledge-based system was developed to adjust input
 parameters to the soil-water and rooting components of PNUTGRO, a
 process- oriented peanut growth model. The system was developed
 to provide a better representation of temporal water status in
 the root zone of a  growing crop. Soil water sensors provided
 input to adjust appropriate parameters based on interpretation of
 their readings. These interpretations  were programmed using
 human expertise combined with data from peanuts grown in
 lysimeters. A separate expert system screened sensor  readings to
 insure their validity before using their readings to adjust
 parameters. Tests of the system over one season showed that
 model-based  representations of soil-water status converged on
 sensor-based representations in the soil water regulation zone as
 the adjusted input parameters  converged on new static values
 early in the season.
 NAL Call No.: 290.9-AM32T
 *****************************************************************
 71. Personal computers--more than calculators and word
 processors.
 McCaslin, N. L. 
 
 Agric-Educ-Mag v.64, p.22-23. (1992).
 Includes references.
 Descriptors: agricultural-education;
 computer-assisted-instruction; microcomputers-;
 computer-mediated-communication
 NAL Call No.: 275.8-AG8
 *****************************************************************
 72. Relating United States crop land use to natural resources and
 climate change.
 Hubbard, K. G.; Flores Mendoza, F. J. 
 
 J-climate v.8, p.329-335. (1995).
 Includes references.
 Descriptors: agricultural-land; land-use; crop-production;
 zea-mays; glycine-max; triticum-aestivum; sorghum-;
 climatic-change; air-temperature; precipitation-;
 water-holding-capacity; regression-analysis; mathematical-models;
 usa-
 Abstract: Crop production depends not only on the yield but also
 on the area harvested. The yield response to climate change has
 been widely  examined, but the sensitivity of crop land use to
 hypothetical climate change has not been examined directly. Crop
 land-use regression models  for estimating crop area indices
 (CAIs)--the percent of land used for corn, soybean, wheat, and
 sorghum production--are presented. Inputs to the  models include
 available water-holding capacity of the soil, percent of land
 available for rain-fed agricultural production, annual
 precipitation,  and annual temperature. The total variance of CAI
 explained by the models ranged from 78% for wheat to 87% for
 sorghum, and the root- mean-square errors ranged from 1.74% for
 sorghum to 4.24% for corn. The introduction of additional
 climatic variables to the models did not  significantly improve
 their performance. The crop land-use models were used to predict
 the CAI for every crop reporting district in the United  States
 for the current climatic condition and for possible future
 climate change scenarios (various combinations of temperature and
 precipitation  changes over a range of -3 degrees to +6 degrees C
 and -20% to +20%, respectively). The magnitude of climatic
 warming suggested by GCMs  (GISS and GFDL) is from 3.5 degrees to
 5.9 degrees C for regions of the United States. For this
 magnitude of warming, the model suggests  corn and soybean
 production areas may decline while wheat and sorghum production
 areas may expand. If the warming is accompanied by a  decrease in
 annual precipitation from 1% to 10%, then the areas used for corn
 and soybean production could decrease by as much as 20% and  40%,
 respectively. The area for sorghum and. precipitation. In
 general, small changes in temperature or precipitation produced
 larger corresponding changes (on a percentage basis) in  soybean,
 wheat, and sorghum area than in corn area.
 NAL Call No.: QC851.J62
 *****************************************************************
 73. RES-N-Till crop residue conservation and tillage management
 software.
 Kok, H.; Thien, J. 
 
 J-soil-water-conserv. Ankeny, Iowa : Soil and Water Conservation
 Society. Nov/Dec 1994. V. 49 (6) p. 551-553. 
 Includes references.
 Descriptors: crop-residues; management-; soil-conservation;
 erosion-control; conservation-tillage; decision-making;
 computer-software
 NAL Call No.: 56.8-J822
 *****************************************************************
 74. RESMAN: a tool for soil conservation education.
 Stott, D. E. 
 
 J-soil-water-conserv v.46, p.332-333. (1991).
 Includes references.
 Descriptors: soil-conservation; computer-software;
 decision-making; expert-systems; crops-; tillage-; crop-residues
 NAL Call No.: 56.8-J822
 *****************************************************************
 75. Rule induction for systems predicting biological activity.
 Judson, P. N. 
 
 J-chem-inf-comput-sci v.34, p.148-153. (1994).
 Includes references.
 Descriptors: databases-; expert-systems; activity-;
 pharmaceutical-products; agricultural-chemicals;
 computer-analysis
 Abstract: Knowledge-based expert systems are now in practical
 use, giving advice about the potential biological activities of
 substances. Systems  depending on the automatic generation of
 rules for their knowledge bases had the disadvantage that rules
 were not easily comprehensible to  human users, making them
 difficult to verify. REX and DEREK link rule generation and the
 application of rules via a knowledge-base language  that is fully
 comprehensible to human users, so that scientists can edit rules
 and incorporate knowledge coming from diverse sources.
 NAL Call No.: 241.64-J82
 *****************************************************************
 76. SEASware: an expert consulting system for shoreline erosion
 control measures.
 Hardaway, C. S. Jr.; Posenau, J. H.; Baumer, J. C. 
 
 Application of advanced information technologies  effective
 management of natural resources  proceedings of the 18-19 June
 1993  Conference, Spokane, Washington /. St. Joseph, Mich. :
 American Society of Agricultural Engineers, c1993.. p. 278-390. 
 Includes references.
 Descriptors: coasts-; erosion-control; expert-systems;
 decision-making; virginia-; chesapeake-bay
 NAL Call No.: GE5.A66-1993
 *****************************************************************
 77. SELOMA: expert system for weed management in
 herbicide-intensive crops.
 Stigliani, L.; Resina, C. 
 
 Weed-technol v.7, p.550-559. (1993).
 Includes references.
 Descriptors: weed-control; decision-making; expert-systems;
 hordeum-vulgare; zea-mays; avena-sativa; secale-cereale;
 beta-vulgaris; sorghum-bicolor; triticum-durum;
 computer-hardware; computer-software; weeds-; integrated-control;
 herbicides-; chemical-control; cultural-weed-control
 NAL Call No.: SB610.W39
 *****************************************************************
 78. Simulation by NCSWAP of seasonal nitrogen dynamics in corn.
 II. Corn growth and yield.
 Lengnick, L. L.; Fox, R. H. 
 
 Agron-j v.86, p.176-182. (1994).
 Includes references.
 Descriptors: zea-mays; computer-simulation; calibration-;
 simulation-models; nutrient-uptake; nitrogen-;
 seasonal-variation; growth-rate; organic- fertilizers;
 fertilizers-; crop-yield; grain-; nitrogen-cycle; pennsylvania-;
 inorganic-fertilizers
 Abstract: The accurate simulation of crop growth is important in
 the effort to apply computer simulation models to improvements in
 the management  of N resources in agricultural systems. The
 objective of this study was to validate the crop growth submodel
 of the model NCSWAP using  seasonal corn (Zea mays L.) growth and
 final grain yields from a 3-yr N rate-study conducted in central
 Pennsylvania. The results of the  validation suggest that the
 model poorly simulated crop growth response under conditions of
 limited water or N availability. However,  NCSWAP accurately
 simulated observed seasonal corn growth and harvested yields in
 treatments with no N or water limitations. The crop  growth
 submodel has the potential to be useful in simulation of crop
 production, because with a minimum of inputs it can be calibrated
 for any  crop and can incorporate variables that influence crop
 growth and are specific to a local environment. Improvements in
 the simulation of crop  growth under N and water deficits would
 enhance the usefulness of NCSWAP to researchers exploring
 seasonal N cycling in soils and crops.
 NAL Call No.: 4-AM34P
 *****************************************************************
 79. Simulation by NCSWAP of seasonal nitrogen dynamics in corn.
 I. Soil nitrate.
 Lengnick, L. L.; Fox, R. H. 
 
 Agron-j v.86, p.167-175. (1994).
 Includes references.
 Descriptors: zea-mays; computer-simulation; calibration-;
 simulation-models; nitrogen-cycle; cycling-; carbon-;
 soil-fertility; nitrates-; seasonal- variation; leaching-;
 soil-water-movement; soil-structure; soil-morphological-features;
 agricultural-soils; edaphic-factors; organic-fertilizers;
 pennsylvania-; inorganic-fertilizers
 Abstract: Computer simulation models of crop-soil systems offer
 the potential to increase understanding of soil N cycle
 processes, thereby improving  management of N resources in
 agricultural systems. NCSWAP (Nitrogen, Carbon, Soil, Water, And
 Plant) is a comprehensive, deterministic  computer model of the
 plant-soil system that simulates seasonal soil C and N cycles
 under the control of temperature, moisture, microbial  activity,
 and crop growth. The objective of this study was to validate
 NCSWAP using data collected during a 3-yr N-rate study in central 
 Pennsylvania that investigated seasonal N dynamics in corn (Zea
 mays L.) provided with N as liquid dairy manure or as NH4NO3.
 Seasonal soil  NO3 concentration in the upper soil layer,
 seasonal aboveground N accumulation by corn, and water leached
 past 1.2 m during the second year  of the study were used to
 calibrate input values controlling soil water flow and NO3
 production from mineralization of soil organic N sources.  The
 validation of NCSWAP identified several limitations in the water
 flow and C and N cycling submodels as well as in the potential of
 the  model to simulate seasonal N dynamics in corn. Validation
 simulations were about as accurate as calibration simulations,
 reflecting the ability  of the model to simulate C and N dynamics
 without recalibration from year to year. Much of the simulation
 error was related to an  overestimation of NO3 leaching caused by
 the inability of the model's microporous flow submodel to
 simulate the macropore-influenced water  flow in the
 well-structured soil used in the validation.
 NAL Call No.: 4-AM34P
 *****************************************************************
 80. SOYHERB--A computer program for soybean herbicide decision
 making.
 Renner, K. A.; Black, J. R. 
 
 Agron-J v.83, p.921-925. (1991).
 Includes references.
 Descriptors: glycine-max; herbicides-; application-methods;
 weeds-; decision-making; weed-competition; computer-software
 Abstract: There has been a rapid increase in the number of
 herbicides and herbicide mixtures registered for use in soybean
 [Glycine max (L.) Merr.]  production. SOYHERB is a computer
 program developed to assist Cooperative Extension Service
 personnel, agribusiness, farmers, and  teachers in determining
 herbicide options for soybean production. Tillage practices,
 atrazine (6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-
 triazine-2,4-diamine) or simazine
 (6-chloro-N,N'-diethyl-1,3,5-triazine-2,4-diamine) use in a
 previous corn crop, soil type and percentage of  organic matter,
 soil pH, projected crop rotation plans, method of herbicide
 application, and weed species and weed pressure are entered by
 the  user. SOYHERB generates herbicide programs and their cost
 per acre that provide excellent control of all weed species at
 the weed pressures  indicated. Fair (80-90%) weed control options
 may also be generated. Additional screens describe control of
 perennial weeds, a summary of  herbicide premixes, and a table
 listing the maximum height of broadleaf weeds controlled by
 postemergence herbicides. Data can be saved for  future
 reference. A computer capable of running MS-DOS or PC-DOS version
 2.1 or greater with a minimum of 512K bytes of RAM is  required.
 NAL Call No.: 4-AM34P
 *****************************************************************
 81. A spatial decision support system for assessing agricultural
 nonpoint source pollution.
 Srinivasan, R.; Engel, B. A. 
 
 Water-resour-bull v.30, p.441-452. (1994).
 Includes references.
 Descriptors: pollution-; watersheds-; runoff-; erosion-;
 geographical-information-systems; simulation-models;
 integrated-systems; texas-
 Abstract: A spatial decision support system (SDSS) was developed
 to assess agricultural nonpoint source (NPS) pollution using an
 NPS pollution  model and geographic information systems (GIS).
 With minimal user interaction, the SDSS assists with extracting
 the input parameters for a  distributed parameter NPS pollution
 model from user-supplied GIS base layers. Thus, significant
 amounts of time, labor, and expertise can be  saved. Further, the
 SDSS assists with visualizing and analyzing the output of the NPS
 pollution simulations. Capabilities of the visualization 
 component include displays of sediment, nutrient, and runoff
 movement from a watershed. The input and output interface
 techniques/algorithms  used to develop the SDSS, along with an
 example application of the SDSS, are described.
 NAL Call No.: 292.9-Am34
 *****************************************************************
 82. Student responses to the initial use of a computer-based
 tutorial in an introductory agricultural economics course.
 Pompelli, G.; Hobbs, T. 
 
 NACTA-j v.34, p.33-36. (1995).
 Includes references.
 Descriptors: agricultural-education; agricultural-colleges;
 computer-assisted-instruction; student-participation; attitudes-;
 surveys-; tennessee-
 NAL Call No.: 275.9-N213
 *****************************************************************
 83. Teaching GIS and its application to water resources:
 multimedia applications.
 Srinivasan, R.; Zhuang, X.; Engel, B. A.; Rewarts, C. C. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1991. (91-5517) 5 p. 
 Paper presented at the "1991 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 17- 20, 1991, Chicago, Illinois.
 Descriptors: water-resources; education-; geography-;
 computer-assisted-instruction
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 84. Teaching systems courses using computer assisted lectures.
 Heinemann, P. H. 
 
 Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of
 Agricultural Engineers,. Winter 1993. (93-3565) 14 p. 
 Paper presented at the "1993 International Winter Meeting
 sponsored by the American Society of Agricultural Engineers,"
 December 14- 17, 1993, Chicago, Illinois.
 Descriptors: computer-assisted-instruction;
 agricultural-education; technology-; teaching-materials; models-;
 educational-courses; pennsylvania-
 NAL Call No.: 290.9-Am32P
 *****************************************************************
 85. Teams: a decision support system for integrated resource
 management.
 Covington, W. W.; Dewhurst, S. M.; Wood, D. B. 
 
 Proc-Soc-Am-For-Natl-Conv p.516-517. (1991).
 Meeting held Aug 4-7, 1991, San Francisco, California.
 Descriptors: forest-management; decision-making;
 computer-software; watershed-management; models-;
 american-indians; arizona-
 NAL Call No.: SD143.S64
 *****************************************************************
 86. Texas rice producers' technology adoption levels--computers,
 management, and production practices.
 Jarvis, A. M.; Rister, M. E.; Grant, W. R.; Mjelde, J. W. 
 
 Misc-publ,-Tex-Agric-Exp-Stn. College Station, Tex. : Texas
 Agricultural Experiment Station. Oct 1992. (1733) 16 p. 
 Includes references.
 Descriptors: oryza-sativa; farmers-; microcomputers-;
 expert-systems; farm-management; decision-making;
 crop-production; texas-
 NAL Call No.: 100-T31M
 *****************************************************************
 87. Using computer assisted hypermedia in the classroom.
 DeFelice, M. S.; Monson, M. J. 
 
 N-A-C-T-A-J v.37, p.40-43. (1993).
 Includes references.
 Descriptors: agricultural-education;
 computer-assisted-instruction; teaching-methods; pilot-projects;
 missouri-
 NAL Call No.: 275.9-N213
 *****************************************************************
 88. Using GLEAMS to evaluate the agricultural waste application
 rule-based decision support (AWARDS) computer program.
 Ford, D. A.; Kruzic, A. P.; Doneker, R. L. 
 
 Water-sci-technol v.28, p.625-634. (1993).
 Paper presented at the IAWQ First International Conference on
 "Diffuse (Nonpoint) Pollution: Sources, Prevention, Impact,
 Abatement."  September 19-24, 1993, Chicago, Illinois.
 Descriptors: agricultural-wastes; application-to-land;
 computer-software; pollutants-; loads-; water-pollution;
 simulation-models; groundwater-pollution; surface-water;
 groundwater-loading-effects-of-agricultural-management-systems;
 artificial-intelligence
 NAL Call No.: TD420.A1P7
 *****************************************************************
 89. Validation of AGNPS for small watersheds using an integrated
 AGNPS/GIS system.
 Mitchell, J. K.; Engel, B. A.; Srinivasan, R.; Wang, S. S. Y. 
 
 Water-resour-bull v.29, p.833-842. (1993).
 Includes references.
 Descriptors: watersheds-; pollution-; runoff-; sediment-;
 erosion-; catchment-hydrology; simulation-models;
 geographical-information-systems; integrated-systems;
 topography-; illinois-; agricultural-nonpoint-source
 Abstract: The AGNPS (Agricultural NonPoint Source) model was
 evaluated for predicting runoff and sedimentdelivery from
 small watersheds of  mild topography. Fifty sediment yield events
 were monitored fromtwo watersheds and five nested
 subwatersheds in East Central Illinois  throughout the growing  
 season of four years. Half of these events were used to calibrate
 parameters in the AGNPS model.Average calibrated parameters
 were used as input for the remaining events to obtain runoff and 
 sediment yield data. These data were used to evaluate the 
 suitability of the AGNPS model forpredicting runoff and
 sediment yield from small, mild-sloped watersheds. An integrated
 AGNPS/GIS system was used to efficiently create the large
 number of data input changes necessary to thisstudy. This
 system is one where the AGNPS  model was integrated with the
 GRASS (GeographicResources Analysis Support System) GIS
 (Geographical Information System) to develop a  decision  
 support tool to assist with management of runoff and erosion from
 agricultural watersheds. Theintegrated system assists with the 
 development of input GIS layers to AGNPS, running the model,  
 and interpretation of the results.
 NAL Call No.: 292.9-Am34
 *****************************************************************
 90. VISITT, vendor information form. Version 4.0 : to be
 completed for participation in the Vendor Information System for
 Innovative  Treatment Technologies (VISITT), version 4.0. Version
 4.0.  Vendor Information System for Innovative Treatment
 Technologies.
 United States. Environmental Protection Agency. Office of Solid
 Waste and Emergency Response. 
 
 Washington, DC : U.S. Environmental Protection Agency, [1994] 1
 v. (various pagings) : ill., forms  1 computer disk (3 1/2 in.).
 Cover title.
 Descriptors:
 Hazardous-wastes-Technological-innovations-Computer-programs;
 Hazardous-wastes-Computer-programs
 NAL Call No.: TD1050.T43V57--1994
 *****************************************************************
 


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