ISSN:1052-5378

Compiled By:
Karl R. Schneider
Reference and User Services Branch
National Agricultural Library, Agricultural Research Service, U. S. Department of Agriculture
Beltsville, Maryland 20705-2351

Compiled For:
The Alternative Farming Systems Information Center, Information Centers Branch
National Agricultural Library
10301 Baltimore Ave., Room 132, Beltsville, Maryland 20705-2351

National Agricultural Library Cataloging Record:

Schneider, Karl, 1946-

Computers and information technologies in agricultural production and management: Part II.

(Quick bibliography series ; 97-10)
1. Agriculture--Computer programs--Bibliography. 2. Agriculture-- Automation-- Bibliography. 3. Agriculture--Data processing-- Bibliography. 4. Precision farming-- Bibliography. 5. Robotics-- Bibliography. 6. Tissue culture--Bibliography. 7. Plant micropropagation--Bibliography. 8. Forest management-- Bibliography. 9. Soil management--Bibliography. 10. Natural resources--Management--Bibliography. 11. Animals--Diseases--Bibliography. 12. Plant diseases--Bibliography. 13. Animal breeding--Bibliography. 14. Plant breeding--Bibliography. 15. Animal genetics--Bibliography. 16. Plant genetics--Bibliography.
aZ5071.N3 no.97-10

Compiler's Notes

A great number of subject records were retrieved in searches for this update, because of the long time-span covered. To accommodate print document size limits, the 1997 update has two Parts with the same title. Part I, QB 97-09, contains records for items added to AGRICOLA from June 1991 through December 1993. Part II, QB 97-10, includes AGRICOLA records added from January 1994 through June 1997.

The extensive search utilized to locate all relevant technology applications records retrieved many items not suitable for this publication. Several hundred inappropriate records were removed to leave only those focused on practical use of the various technologies in production related areas. Broad classes of items omitted include records treating laboratory applications of sensors and other information technologies, broad scale water-resource management, food products and forest products industries' technology applications, biotechnology and biochemistry reports, and documents produced by the "Conservation Technology Information Center," covering BMP's (Best Management Practices) not directly employing specific information technology resources.

Included publications cover subjects ranging from precision farming to robotics to automated tissue culture and micro- propagation operations. Plant and animal disease management, forest, soil and natural resources management (including controlled burning and forest fires) are among subjects covered by records cited here. Various types of sensors, ranging from ion-selective electrodes to ultrasound to various satellite based systems are used in works listed. Several items treating computer use in plant and animal breeding and applied genetics and embryo transfer are included. The tendency to err toward inclusion of many documents describing research applications of production related technologies is admitted. The author was hoping to provide awareness for the reader of options and possibilities at hand. Computerized training systems in production and management are also present in this list, to show the availability of such management training tools. The included Search Strategy gives the details of terms and concepts utilized in the original search.

Your comments and suggestions are welcome, to aid in improving and refining any updates or supplements to this publication. Send comments to me, Karl Schneider. Mail to: Reference Section, Room 100, NAL-ARS-USDA, 10301 Baltimore Avenue, Beltsville, MD 20705. Electronic mail may be addressed to: kschneid@nal.usda.gov.

Thank you for your time and interest!

Alternative Farming Systems Information Center (AFSIC)

This publication is available in hardcopy, or electronically on computer diskette, or via AFSIC's Internet Web Site: http://afsic.nal.usda.gov. Please send comments and corrections regarding this publication to the author. Send requests for additional copies to:

Computers and Information Technologies in Agricultural Production and Management, Part II

2.
NAL Call No.: 49-J82
Additive genetic groups for animals evaluated in more than one breed association national cattle evaluation.
Golden, B. L.; Bourdon, R. M.; Snelling, W. M. J-anim-sci v.72(10): p.2559-2567. (1994 Oct.)
Includes references.
Descriptors: beef-cattle; american-angus; beef-breeds; progeny- testing; breeding-value; genetic-analysis; genetic-correlation; heritability; birth-weight; weaning-weight; milk-yield; accuracy; computer-techniques; computer-software; red-angus

Abstract: Additive genetic groups were included in the 1993 Red Angus Association of America national cattle evaluation for phantom parents of individuals who were registered with the American Angus Association (AAA). Genetic groups were formed for each component in two multiple- trait evaluations in which all animal effects were fit. Additive direct effects were included for birth weight, weaning weight (WW), and milk (MILK). In a second analysis the additive direct effect of 160-d postweaning gain was analyzed with WW and MILK. Of the 387,665 animals, 50,838 had at least one phantom parent assigned to one of five genetic groups fit as fixed effects for each additive component. Of these 50,838 animals, 1,324 were identified as registered with the AAA. An average of 906 animals per component had an AAA EPD available. Animals with a known AAA EPD were designated into one of three groups of equal numbers based on AAA EPD for each component (1 = low, 2 = medium, 3 = high). Animals in the fourth genetic group were those registered with the AAA but with no EPD available for the component. The fifth genetic group included all other animals with phantom parents. Grouping on AAA EPD allowed for EPD on animals out of parent(s) registered with the AAA to be more closely aligned to the AAA EPD because they were regressed from the group solution instead of zero. Grouping based on EPD from another NCE should be considered in the production of multibreed EPD.

3.
NAL Call No.: aSD11.U585
Aerial survey methods used in the Southern Region.
Barry, P. J. Rep-US-For-Serv-North-Reg-Timber-Coop-For-Pest-Manag (95- 4): p.19-21. (1995 Jan.)
Paper presented at the Aerial Pest Detection and Monitoring Workshop, April 26- 29, 1994, Las Vegas, Nevada.
Descriptors: forest-management; aerial-surveys; insect-pests; plant- diseases; mapping; aerial-photography; video-recordings; infrared-imagery; forest- pests; fungal-diseases; southern-states-of-usa

4.
NAL Call No.: S494.5.I47J68
Agricultural information via the Cleveland Free-Net.
Britton, C. J. J-agric-food-inf v.3(2): p.49-56. (1995)
Paper presented at the U.S. Agricultural Information Network National Conference on "Cultivating New Ground in Electronic Information: Use of the Information Highway to Support Agriculture," April 26-29, 1995, Lexington, Kentucky.
Descriptors: agriculture; domestic-gardens; information-services; public-services; on-line; information-technology; microcomputers; universities; extension; program-development; ohio; ohio-agricultural-and-development-center- oardc; world-wide-web; internet

5.
NAL Call No.: 290.9-Am32P
Agricultural robots(2): manipulators and fruits harvesting hands.
Kondo, N.; Monta, M.; Shibano, Y.; Mohri, K.; Yamashita, J.; Fujiura, T. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1992. (923518) 19 p.
Paper presented at the "1992 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 15-18, 1992, Nashville, Tennessee.
Descriptors: tomatoes; grapes; robots; harvesters

6.
NAL Call No.: 290.9-Am32P
Agricultural robots(3): grape berry thinning hand.
Monta, M.; Kondo, N.; Shibano, Y.; Mohri, K.; Yamashita, J.; Fujiura, T. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1992. (923519) 10 p.
Paper presented at the "1992 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 15-18, 1992, Nashville, Tennessee.
Descriptors: grapes; fruits; robots

7.
NAL Call No.: S671.A66
AGRISIM: A PC user-friendly transient simulation program for growing- finishing swine buildings.
Axaopoulos, P.; Panagakis, P.; Pitsilis, G.; Kyritsis, S. Appl-eng- agric v.10(5): p.735-738. (1994 Sept.)
Includes references.
Descriptors: pig-housing; microenvironments; environmental- temperature; computer-simulation; computer-software

Abstract: A simulation program (ACRISIM) running on personal computers was developed to study the transient behavior of the thermal microenvironment inside swine buildings housing pigs weighing from 20 kg (44 lb) to 100 kg (220 lb). The program accounts for a large number of parameters including the orientation and the structure of the building, the ventilation rates used and their staging with respect to inside temperature, the existence or not of a pit, and the pig metabolic heat and manure production. It accepts hourly climatic data, incorporates a library with various properties of insulation and structural materials, and uses pull-down menus. Results are presented in tables, shown at the screen, or printed. The program can be used to predict the thermal microenvironment conditions in the building along with the heating/cooling load required to keep the temperature within pigs' thermoneutral zone. Furthermore, it can be used to study the effects that various parameters have on the inside thermal conditions.

8.
NAL Call No.: 80-Ac82
The AGROBOT project for greenhouse automation.
Dario, P.; Sandini, G.; Allotta, B.; Bucci, A.; Buemi, F.; Massa, M.; Bosio, L.; Valleggi, R.; Gallo, E.; Bologna, A. Acta-hortic (361): p.85-92. (1994 June)
Paper presented at the International Symposium on New Cultivation Systems in Greenhouse held April 26-30, 1993, Cagliari, Italy.
Descriptors: lycopersicon-esculentum; horticulture; greenhouse- culture; automation; robots; spraying; fruits; picking; greenhouse-crops

9.
NAL Call No.: SF961.A5
AGROS: a program for veterinary and zootechnical herd health management.
Ranst, B. v.; Baecke, F.; Mattheeuws, M.; Zeveren, A. v.; Bouquet, Y. Am- Assoc-Bov-Pract-Conf. Stillwater, Okla. : The Association, [1992-. 1992. v. 2 v. 2 p. 23-29.
Meeting held on August 31-September 4, 1992, St. Paul, Minneosta.
Descriptors: dairy-herds; animal-health; computer-software

10.
NAL Call No.: 60.18-J82
Airborne synthetic aperture radar analysis of rangeland revegetation of a mixed prairie.
Smith, A. M.; Major, D. J.; Hill, M. J.; Willms, W. D.; Brisco, B.; Lindwall, C. W.; Brown, R. J. J-range-manage v.47(5): p.385-391. (1994 Sept.)
Includes references.
Descriptors: agropyron-cristatum; psathyrostachys-juncea; aerial-photography; radar; grazing-effects; canopy; rangelands; range-management; remote- sensing; botanical-composition; oversowing; revegetation; alberta; radar-backscatter

Abstract: Microwave radar is a potentially useful tool for monitoring the condition of the rangeland. A study was conducted in a mixed prairie community at the Agriculture Canada Research Substation at Onefour, Alberta in 1991 to examine the effects of historical management on synthetic aperture radar (SAR) data obtained from 2 aircraft flights, 24 May 1991 and 1 August 1991. Ground-truthing expeditions were conducted on the same days to obtain estimates of vegetation amounts, species distribution and soil moisture. A former grazing experiment established in 1955 and abandoned 20 years ago enabled comparison of 3 grazing treatments, continuous, rotation and free choice superimposed on native range, crested wheatgrass (Agropyron cristatum (L.) Gaertn.) and Russian wildrye (Elymus junceus Fish.). The ground data and imagery were integrated in a Geographic Resource Analysis Support System (GRASS). Fields that had been cultivated and seeded to Russian wildrye had higher radar backscatter than native range. The radar backscatter from crested wheatgrass fields was similar to native range in May but higher than native range in August. Radar backscatter was positively correlated with number of years since seeding with Russian wildrye. Generally there was little difference in radar backscatter with grazing treatment. Correlation analyses between radar digital number extracted from the ground truth sites and vegetation and soil parameters revealed, depending upon swath mode, significant relationships between radar backscatter and the amount of certain grass species, radar backscatter and canopy moisture, and radar backscatter and soil moisture in May. A significant negative correlation. indicated a role for SAR imagery in evaluating range characteristics.

11.
NAL Call No.: 4-AM34P
The ALFALFA CATALOG software package.
Townsend, M. S.; Henning, J. A.; Currier, C. G. Agron-j v.86(2): p.337- 339. (1994 Mar.-1994 Apr.)
Includes references.
Descriptors: medicago-sativa; computer-software; cultivars; germplasm; lines; genotypes; databases; new-mexico

Abstract: Due to modern plant breeding methods, agricultural producers have many cultivars available for many different species. Consequently, it is often difficult to recommend a cultivar for a particular growing area. A list of alfalfa cultivars, germplasms, and breeding lines available was published. However, due to the large number of entries in these publications finding pertinent information about a cultivar, breeding line, or germplasm was tedious. The objectives of this project were to (i) develop a computer program to access the alfalfa information in the original database, and (ii) update the database to include those alfalfa cultivars, breeding lines, and germplasms released through late 1992. A computer program was written using Microsoft QuickBasic, ver. 4.5. The original alfalfa database was converted to ASCII format. The resulting software package is entitled the ALFALFA CATALOG ver. 1.0 Three program files and four data files comprise the ALFALFA CATALOG software package. Users may rapidly search the database and retrieve entries by cultivar name, experimental designation, or germplasm. We also wrote a routine to print a list of all cultivars or germplasms that have a specific combination of traits. These search capabilities will allow plant breeders, extension agents, and consultants rapid access to pertinent alfalfa data. Currently, the ALFALFA CATALOG has 752 entries for cultivars and breeding lines, and 144 entries for germplasms. The database will be updated yearly. In its present form, the ALFALFA CATALOG is probably the most complete compilation of alfalfa cultivars, breeding lines, and germplasms available.

12.
NAL Call No.: SB193.F59
Alfalfa integrated management software: PROFALF.
Ward, C.; Limsupavanich, J.; Stark, A.; Cuperus, G.; Johnson, G.; Huhnke, R.; Stritzke, J.; Berberet, R. Proc-Am-Forage-Grassl-Counc-1992. Georgetown, Tex. : American Forage and Grassland Council. 1993. v. 2 p. 176-180.
Meeting held March 29-31, 1993, Des Moines, Iowa.
Descriptors: medicago-sativa; computer-software

13.
NAL Call No.: SB193.F59
Alfalfa quality measures and price relationships.
Ward, C. E. Proc-Am-Forage-Grassl-Counc-1992. Georgetown, Tex. : American Forage and Grassland Council. 1994. v. 3 p. 289-293.
Meeting held March 6-10, 1994, Lancaster, Pennsylvania.
Descriptors: medicago-sativa; crop-quality; prices; computer-software; computer-analysis; crude-protein; digestibility; oklahoma

14.
NAL Call No.: 290.9-Am32T
Algorithms for extracting leaf boundary information from digital images of plant foliage.
Franz, E.; Gebhardt, M. R.; Unklesbay, K. B. Trans-ASAE v.38(2): p.625- 633. (1995 Mar.-1995 Apr.)
Includes references.
Descriptors: crops; weeds; leaves; algorithms; computer-analysis; infrared-imagery

Abstract: Algorithms were developed to extract edge segments along leaf margins in digitized scenes of weed seedlings. Edge segments were linked based on endpoint conditions to form closed boundaries of vegetative regions. Since boundaries represented regions of either single or multiple leaves. methods were developed to partition regions based on interior boundaries and finally produce boundaries of single leaves, either completely visible or partially occluded. suitable for shape identification. The algorithms were evaluated based on a comparison of the number of leaves detected with the actual number of leaves in an image. The results indicated that 0.912. 0.875. 0.958, and 0.714 of the leaves in images of velvetleaf (Abutilon theophrasti), soybean (Glycine max), ivyleaf morning glory (Ipomoea hederacea), or foxtail (Setaria faberi) seedlings, respectively, were detected.

15.
NAL Call No.: SB931.P385--1996
Analyses in insect ecology and management. 1st ed.
Pedigo, L. P.; Zeiss, M. R. Ames, Iowa : Iowa State University Press, c1996. xi, 168 p. : ill. 1 computer disk (3 1/2 in.), "Including the ENSTAT system of computer programs developed by Thomas H. Klubertanz and Matthew P. Evanson."
Descriptors: Enstat; Insect-pests-Control-Computer-simulation; Insect- populations-Computer-simulation; Insect-pests-Ecology-Computer-simulation; Insect-populations-Ecology-Computer-simulation

16.
NAL Call No.: 44.8-J822
Analytical tools for material and energy balance, cash flow, and environmental loads in a dairy cattle enterprise.
Saama, P. M.; Koenig, B. E.; Koenig, H. E.; Anderson, J. H. J-dairy-sci v.77(4): p.994-1002. (1994 Apr.)
Includes references.
Descriptors: dairy-farming; computer-software; systems-analysis; network-analysis; material-balance; energy-balance; externalities

Abstract: Analytical tools for the preconstruction technical design and postconstruction management of a dairy enterprise are presented. The enterprise is represented as a network of production processes with alternative operating technologies and scale of operation as technical parameters of environmental loads and cash flow. The operating technologies of the network are represented by material conversion coefficients and energetic cost functions. Generalized laws of material and energy balance are used to define an on-line management accounting system for recording resource and product flows, physical energy, and human time involved in the production process. Cash flow and value added are computed from the technologies of the network, prices of material and energetic resources, and costs of operating facilities. A microcomputer application was developed to evaluate the environmental loads and the economic consequences of alternative technologies, product prices, and amortization schedules for facility and equipment costs. The concepts and analytical tools presented for the design and management of dairy enterprises provide a framework through which scientists across disciplines and producers across product lines can work together to increase overall farm profitability and to reduce environmental loads.

17.
NAL Call No.: S539.5.J68
Analyzing pork carcass evaluation technologies in a swine bioeconomic model.
Boland, M. A.; Foster, K. A.; Preckel, P. V.; Schinckel, A. P. J-prod- agric v.9(1): p.45-49. (1996 Jan.-1996 Mar.)
Includes references.
Descriptors: pigs; genotypes; carcasses; carcass-composition; evaluation; carcass-quality; technology; econometric-models; economic- evaluation; agribusiness

Abstract: Inaccurate pork (Sus scrofa) carcass evaluation technologies have the potential to send inaccurate economic signals to producers regarding leanness. The objective of this study was to estimate the difference in the optimal level of returns to management and operator labor under alternative assumptions about the carcass evaluation technology employed and the actual returns based on carcass dissection data. Two genotypes of barrows and gilts reflecting significant genetic variation were analyzed. The carcass evaluation technologies examined were: an optical probe (PROBE), electromagnetic scanner (EMSCAN), and a combination of both technologies (BOTH). A deterministic bioeconomic model of swine growth was formulated to measure the effect of these technologies on pork producer profitability. Relationships between biological variables for feed efficiency, live weight, lean weight, fat weight, carcass weight, and backfat depth were estimated as functions of time for two genotypes of barrows and gilts. Economic variables included production costs and revenues from a component pricing model with separate payments for lean, fat, and byproducts. Error was defined as the optimal return to management and operator labor derived from the bioeconomic optimization model minus the actual return as determined from carcass dissection. The range of error was $-5.41 (lean genotype gilts) to $0.23 per pig (fat genotype barrows) for the PROBE model. For the EMSCAN model this range was $-2.63 (lean genotype barrows) to $5.46 (fat genotype barrows) while the BOTH model had a range of $-3.54 (fat genotype gilts) to $1.54 (fat genotype barrows). The results indicated that the absolute error (sum of errors across genotype and sex) for each. model and highest for the EMSCAN model.

18.
NAL Call No.: SB379.A9A9
Andy Hensel brings new techniques to irrigation management.
Hall, R. Calif-grow v.19(10): p.25-26. (1995 Oct.)
Descriptors: consultants; irrigation-scheduling; computer-techniques; weather-data; computer-software; soil-water; costs; colorado; california

19.
NAL Call No.: 58.8-J82
Animal activity measured by infrared detectors.
Pedersen, S.; Pedersen, C. B. J-agric-eng-res v.61(4): p.239-246. (1995 Aug.)
Includes references.
Descriptors: movement; animals; simulation; detection; sensors; infrared-radiation; animal-housing; passive-infrared-detectors

20.
NAL Call No.: 290.9-Am32T
Animal-based control algorithm for natural ventilation in pig houses.
Klooster, C. E. v. Trans-ASAE v.39(3): p.1127-1133. (1996 May-1996 June)
Includes references.
Descriptors: pigs; pig-housing; natural-ventilation; environmental- control; automatic-control; air-quality; carbon-dioxide; liveweight; heat- balance; feed- intake; heating-costs; cost-control; microcomputers; algorithms; netherlands

Abstract: An algorithm is developed for environmental control in pig houses using natural ventilation. This controller requires input of animal data instead of climate setpoints. The controller includes both a growth model that predicts pig weight and feed intake and a heat balance model that determines animal-level climate setpoints. The algorithm uses a carbon dioxide balance to estimate air exchange. Therefore, the algorithm can be used in pig houses with natural ventilation. The control of air flow in pig houses allows for an energy- efficient use of heating systems in pig houses with natural ventilation.

21.
NAL Call No.: SB317.5.H68
Apple maturity prediction: an extension tool to aid fruit storage decisions.
Beaudry, R.; Schwallier, P.; Lennington, M. HortTechnology v.3(2): p.233-239. (1993 Apr.-1993 June)
Includes references.
Descriptors: apples; fruit-stores; controlled-atmosphere-storage; storage-quality; decision-making; prediction; harvesting-date; maturation- period; computer-software; growth-models; crop-quality; michigan

22.
NAL Call No.: 26-T754
Application of a computerized herd management and production control program in Costa Rica.
Dwinger, R. H.; Cappella, E.; Perez, E.; Baaijen, M.; Muller, E. Trop- agric v.71(1): p.74-76. (1994 Jan.)
Includes references.
Descriptors: farm-management; livestock-enterprises; computer- software; costa-rica

23.
NAL Call No.: QH301.A76-no.43
Application of large scale yield mapping to field experimentation.
Schroder, D.; Schnug, E. Field experiment techniques 11-13 December 1995, Churchill College, Cambridge /. Wellesbourne, Warwick, UK : The Association, [c1995]. p. 117-124.
Includes references.

24.
NAL Call No.: QK710.P55
Applications of a thermal imaging technique in the study of the ascent of sap in woody species.
Anfodillo, T.; Sigalotti, G. B.; Tomasi, M.; Semenzato, P.; Valentini, R. Plant-cell-environ. Oxford, Blackwell Scientific Publishers. Nov 1993. v. 16 (8) p. 997-1001.
Includes references.
Descriptors: forest-trees; sap-ascent; thermography; infrared- radiation; growth-rings

25.
NAL Call No.: 290.9-Am32P
Applications of simulation in design.
Coddington, R. C.; Hubele, J. D. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1992. (927034) 11 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: computer-software; planters

26.
NAL Call No.: S494.5.D3C652
Applying machine learning to agricultural data.
McQueen, R. J.; Garner, S. R.; Nevill Manning, C. G.; Witten, I. H. Comput- electron-agric v.12(4): p.275-293. (1995 June)
Includes references.
Descriptors: dairy-herds; cattle-husbandry; culling; expert-systems; databases; technology; learning; computer-software; case-studies

27.
NAL Call No.: 325.28-P56
Assessing corn yield and nitrogen uptake variability with digitized aerial infrared photographs.
Tomer, M. D.; Anderson, J. L.; Lamb, J. A. Photogramm-eng-remote- sensing v.63(3): p.299-306. (1997 Mar.)
Includes references.
Descriptors: zea-mays; crop-yield; minnesota

28.
NAL Call No.: 290.9-Am32P
Assessing the spatial variability of organic matter.
McCauley, J. D.; Engel, B. A.; Scudder, C. E.; Morgan, M. T.; Elliott, P. W. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1993. (93-1531/93-1560) 14 p.
Paper presented at the "1993 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 13-17, 1993, Chicago, Illinois.
Descriptors: soil-organic-matter; sensors; field-tests; variation; site-factors; site-specific-farming

29.
NAL Call No.: 49-J82
Assessment of lamb carcass composition from live animal measurement of bioelectrical impedance of ultrasonic tissue depths.
Berg, E. P.; Neary, M. K.; Forrest, J. C.; Thomas, D. L.; Kauffman, R. G. J- anim-sci v.74(11): p.2672-2678. (1996 Nov.)
Includes references.
Descriptors: lambs; live-estimation; carcass-composition; prediction; equations; ultrasonography; body-weight; impedance; carcass-yield; fat- thickness; body-measurements; coefficient-of-relationship; slaughter-weight; yield-grade

Abstract: Market weight lambs, average weight 52.5 kg (+/- 6.1), were used to evaluate nontraditional live animal measurements as predictors of carcass composition. The sample population (n = 106) represented U.S. market lambs and transcended geographic location, breed, carcass weight, yield grade, and production system. Realtime ultrasonic (RU) measurements and bioelectrical impedance analysis (BIA) were used for development and evaluation of prediction equations for % boneless, closely trimmed primal cuts (BCTPC), weight or % of dissected lean tissue (TDL), and chemically derived weight or % fat-free lean (FFL). Longitudinal ultrasonic images were obtained parallel to the longissimus thoracis et lumborum (LTL), positioning the last costae in the center of the transducer head. Images were saved and fat and LTL depths were derived from printed images of the ultrasonic scans. Bioelectrical impedance analysis was administered via a four-terminal impedance plethysmograph operating at 800 micro A at 50 kHz. Impedance measurements of whole-body resistance and reactance were recorded. Prediction equations including common linear measurements of live weight, heart girth, hindsaddle length, and shoulder height were also evaluated. All measurements were taken just before slaughter. Bioelectrical impedance measurements (as compared to RU and linear measurements) provided equations for %BCTPC, TDL, %TDL, FFL and %FFL with the highest R2 and lowest root mean square error. Even though BIA provided the best equations of the three methodologies tested, prediction of proportional yield (%BCTPC, %TDL, and %FFL) was marginal (R2 = .296, .551, and .551, respectively). Equations combining BIA, RU, and linear measurements greatly improved.

30.
NAL Call No.: TC801.I66
An assessment of project management software as a decision support system for irrigation management in Morocco.
Smith, L. E. D.; Keddal, H. Irrig-drain-syst v.9(4): p.329-335. (1995 Nov.)
Includes references.
Descriptors: pumps; maintenance; planning; irrigation-equipment; expert-systems; decision-making; monitoring; management; morocco; pump-stations

31.
NAL Call No.: SF961.A5
Assessment of the use of MOIRA (management of insemination through routine analysis): the delivery of fertility management via a module of DAISY-- The Daisy Information System.
Esslemont, R. J.; Williams, M. E. Am-Assoc-Bov-Pract-Conf. Stillwater, Okla. : The Association, [1992-. 1992. v. 1 p. 315-321.
Meeting held on August 31-September 4, 1992, St. Paul, Minnesota.
Descriptors: dairy-cows; estrus; computer-software

32.
NAL Call No.: S590.C63
Automated work-station for soil analysis.
McGrath, D.; Skotnikov, A. Commun-soil-sci-plant-anal v.27(5/8): p.1795-1812. (1996)
Paper presented at the 1995 International Symposium on Soil Testing and Plant Analysis: Quality of Soil and Plant Analysis in View of Sustainable Agriculture and the Environment held August 5-10, 1995, Wageningen, The Netherlands.
Descriptors: soil-analysis; physicochemical-properties; sample- processing; automation; structural-design; farming-systems; sustainability; precision-farming

Abstract: For site specific fertilizer and chemical application, an economically efficient collection, correlation, processing and analyzing of soil samples is needed. To do this, we have created the Automated Work-Station for Soil Analysis (AWSSA). The prototype AWSSA, where soil samples are automatically unpacked, prepared, processed and analyzed in sequential order is based on Rinkis method . All chemistry is built in one sequential line with branches, which permits to utilize only one soil sample (it increases precision and speed of process) for determination of all it parameters, such as pH; particle size;overall humus, alkali-soluble fraction of humus; sesquioxides-carbonates; concentration of the macronutrients; such as NO3, NH4, K, P, Ca, and Mg. The sample preparation unit consists of a mixer where soil is mixed with a water as a slurry, goes through the sieve to screen out large particles, and then through microwave humidity meter to a vessel for it weighting and further analyzing. The concentration of macronutrients are determined by means of ion selective sensors, which are placed in the flow of the extraction. Ceramic filters have being used for filtering the slurry on different stages in AWSSA. They can be subjected to vacuum for accelerating filtering process and back pressure for cleaning. For the determination of sesquioxides, alkali-soluble fraction of humus, overall humus, and P in AWSSA, we use automated photo-colourimeter. The AWSSA has approximately the size of a writing desk, it is economical and fast. It does one sample per minute after initial process setup time.

33.
NAL Call No.: SB317.5.H68
Automation in the greenhouse: challenges, opportunities, and a robotics case study.
Simonton, W. HortTechnology v.2(2): p.231-235. (1992 Apr.-1992 June)
Includes references.
Descriptors: crop-production; greenhouse-culture; robots; mechanization; automation; computer-techniques

34.
NAL Call No.: 60.19-So83
The beef animal model GRAZE: its status and application.
Loewer, O. J. Proc-South-Pasture-Forage-Crop-Improv-Conf. New 0rleans : Agricultural Research Service (Southern Region), U.S. Dept. of Agriculture, 1974-. 1993. (49th) p. 77-85.
Meeting held on June 14-16, 1993, Sarasota, Florida.
Descriptors: beef-cattle; grazing; computer-simulation; simulation- models; computer-software

35.
NAL Call No.: 421-J822
Binomial sequential sampling plans and decision support algorithms for managing the Russian wheat aphid (Homoptera: Aphididae) in small grains.
Legg, D. E.; Mowierski, R. M.; Feng, M. G.; Peairs, F. B.; Hein, G. L.; Elberson, L. R.; Johnson, J. B. J-econ-entomol v.87(6): p.1513-1533. (1994 Dec.)
Includes references.
Descriptors: population-density; monitoring; economic-thresholds; sequential-sampling; mathematical-models; computer-software; model-development

Abstract: A sequential-interval procedure was developed to calculate upper and lower stop values of binomial sequential sampling models for the Russian wheat aphid, Diuraphis noxia (Kurdjumov), infesting small grains. This procedure was developed for economic thresholds of 5, 10, and 20% infested tillers and will calculate upper and lower stop values for most proportions of maximum allowable sequential errors between 0.01 and 0.5. Average sample number and proportion of incorrect classification curves were established with three binomial sequential sampling models. In addition, the influence of maximum allowable number of samples and three terminal-error philosophies on the proportion of incorrect classifications was investigated. The sequential- interval procedure was tested via computer-simulated sampling experiments and field evaluations in Colorado, Idaho, Montana, Nebraska, and Wyoming. A computer program enabled users to produce easily sequential sampling stop values via the sequential- interval procedure.

36.
NAL Call No.: 424.8-Am3
BK-ECONOMICS: a money management model for beekeepers.
Degrandi Hoffman, G.; Templin, M.; Buchmann, S. L.; Erickson, E. H. JR. Am- bee-j v.136(5): p.331-337. (1996 May)
Descriptors: beekeeping; money-management; computer-software; computer-simulation

37.
NAL Call No.: Z672.I53
Bridging the gap between practice and policy: policy management challenges for agricultural information specialists.
Ballantyne, P. Q-bull-Int-Assoc-Agric-Inf-Spec v.39(1/2): p.24-30. (1994)
Paper presented at the "International Symposium on New Information Technologies in Agriculture," November 10-12, 1993, Bonn Germany.
Descriptors: agricultural-research; information-systems; information- services; policy; management; developing-countries; policy-formation

38.
NAL Call No.: 290.9-Am32T
Canal irrigation allocation planning model.
Akhand, N. A.; Larson, D. L.; Slack, D. C. Trans-ASAE v.38(2): p.545- 550. (1995 Mar.-1995 Apr.)
Includes references.
Descriptors: irrigation; water-allocation; irrigation-scheduling; canals; water-requirements; water-availability; crop-yield; simulation-models; computer- software; arizona

Abstract: A water allocation model was developed to recommend allocation of irrigation water to different crop fields in a canal-based irrigation project. Model components are an irrigation scheduling program to predict irrigation water demands, a crop response model to compute crop yields, and a canal delivery model to check the physical feasibility of water delivery. Multiperiod linear programming is utilized to determine the optimal allocation strategy, which maximizes irrigation benefits. Allocation constraints are irrigation water demand, irrigation water availability, canal delivery capacity, minimum irrigation limitations, and crop response model limitations. The allocation model was validated using crop, soil, canal, and irrigation management data for MAC, a University of Arizona farm.

39.
NAL Call No.: S612.I756
Canopy temperature as a measure of salinity stress on sorghum.
Kluitenberg, G. J.; Biggar, J. W. Irrig-sci v.13(3): p.115-121. (1992)
Includes references.
Descriptors: sorghum-bicolor; salinity; stress; detection; canopy; temperature; measurement; timing; irrigated-stands; soil-water-content; soil- salinity; water-use; water-uptake; crop-yield; grain; dry-matter-accumulation; california

Abstract: A complete understanding of plant response to combined water and salinity stress is desirable. Previous growth chamber and greenhouse experiments with sorghum and maize indicate that soil salinity, by negatively affecting growth processes, may reduce consumptive water use, thus prolonging the supply of available soil moisture. In the present field experiment, canopy temperature measurements were used to examine the effect of soil salinity on the plant-soil water relations of sorghum (Sorghum bicolor L. cv. Northrup King 1580). An infrared thermometer was used to measure canopy temperature during a 9-day period including two irrigations in plots of various salinities. The salinity treatments were created by a dual line-source sprinkler irrigation system, which applied waters of different quality. Excess irrigation allowed soil moisture to be uniform across the salinity treatments at the beginning of the measurement period. Consumptive water use and soil salinity were measured to quantify the salinity and water treatments. Grain and dry matter yields provided measures of plant response. Canopy temperature measurements were sensitive enough to detect differences across the salinity treatments when soil moisture was uniform for several days following irrigation. However, over the 9-day measurement period, plants in the low-salt plots used more water than plants in the high-salt plots. This differential water use eventually offset the salinity- induced stress, with the result that temperature differences were eliminated. Differences in temperature were observed again following irrigation. The results demonstrate that canopy temperature can be used as a tool to detect salinity stress on sorghum. Timing of measurements with regard to irrigation is identified as a key factor in detecting temperature differences that can be attributed to.

40.
NAL Call No.: 1-F766Fi
Changes at California's ITS.
Favro, A. P. Fire-Manage-Notes. Washington, U.S. Dept. of Agriculture Forest Service. 1995. v. 55 (2) p. 23.
Descriptors: information-services; information-technology; public- agencies; management; forestry; fire-control; california; department-of- forestry-and-fire-protection; information-technology-services

41.
NAL Call No.: 23-Au792
Changes in fat depths and muscle dimensions in growing lambs as measured by real-time ultrasound.
Hopkins, D. L.; Pirlot, K. L.; Roberts, A. H. K.; Beattie, A. S. Aust-j-exp- agric v.33(6): p. 707-712. (1993)
Includes references.
Descriptors: lambs; lamb-fattening; fat-thickness; muscles; body- composition; carcass-composition; grazing; animal-nutrition; growth-rate; liveweight- gain; animal-tissues; thickness

42.
NAL Call No.: SF207.S68
CHAPS summary for South Dakota--1991.
Boggs, D. L. S-D-beef-rep (92-2): p.2-4. (1992 Aug.)
Descriptors: cows; calving; computer-software; calf-production; performance; weaning-weight; birth-weight; south-dakota

43.
NAL Call No.: 49-J82
Characterization of growth parameters needed as inputs for pig growth models.
Schinckel, A. P.; De Lange, C. F. M. J-anim-sci v.74(8): p.2021-2036. (1996 Aug.)
Paper presented at a symposium "Revising the Nutrient Requirements of Swine: New Topics and Directions" at the ASAS 87th Annual Meeting, Orlando, FL.
Descriptors: pigs; genotypes; feed-intake; body-protein; mathematical- models; growth; lean; energy-cost-of-maintenance; energy-intake; sex- differences; body-weight; dietary-fat; lysine; backfat; protein-requirement; gilts; plane-of-nutrition; barrows

Abstract: Swine growth models have the potential to evaluate alternative management decisions and optimize production systems. However, the lack of economical, yet accurate methods to obtain the growth parameters required to characterize pig genotypes, and which are required by growth models, limits their widespread implementation. The four primary parameters required are 1) daily whole-body protein accretion potential, 2) partitioning of energy intake over maintenance between protein and lipid accretion, 3) maintenance requirements for energy, and 4) daily feed intake. Estimation of daily protein accretion rates requires that serial estimates of composition and growth be fitted to flexible nonlinear functions. Serial dissection and chemical analysis are too expensive to be routinely conducted on an adequate number of pigs for precise daily protein accretion rates at different live weights. Three alternate methods include 1) serial slaughter and double sampling; 2) use of serial live measurements to estimate composition, i.e., serial ultrasonic measurements; and 3) use of generalized functions that estimate daily protein accretion as a function of mean daily fat-free lean gain over a specified weight interval. The energy partitioning between lipid and protein accretion can be expressed as two interchangeable measurements, either as the slope of protein accretion or the change in the lipid: protein gain ratio as a function of energy intake at each live weight. Both methods require serial estimates of composition and scale feeding of pigs to specified energy intake levels. Maintenance requirements for energy are better expressed as a function of protein mass than body. Daily feed intakes at each live weight can be estimated by accurately collecting feed intake data at least three live weight ranges and fitting the data to nonlinear functions. An alternative method to estimate daily feed intake is to develop daily lipid and protein accretion curves. On the basis of their energetic costs of lipid and protein deposition and assumed maintenance requirements, daily energy intakes can be estimated. Genetic selection changes the underlying growth parameters. The selection criteria and testing environment direct the relative genetic change for each growth parameter. The different sexes may also be affected differently by selection. For this reason, each closed uniformly selected population must be evaluated for each parameter for each sex.

44.
NAL Call No.: SB435.5.A645
Choosing trees the easy way.
Gilman, E. F. Arbor-age v.14(7): p.14, 16. (1994 July)
Descriptors: choice-of-species; trees; computer-software; selection- criteria; tree-finder

45.
NAL Call No.: S79.E8
CLASS: Clean Chip Assessment System--technical report.
Belli, M. L.; Thomas, J. D.; Watson, W. F.; Straka, T. J.; Brooks, R. Jr. Tech-bull-Miss-Agric-For-Exp-Stn. Mississippi State, Miss. : The Station. Aug 1993. (190) 41 p.
Includes references.
Descriptors: whole-tree-chips; fuels; production-costs; computer- simulation; computer-software

46.
NAL Call No.: S79.E8
CLASS--clean chip assessment system: user's manual.
Belli, M. L.; Thomas, J. D.; Watson, W. F.; Straka, T. J.; Brooks, R. Jr. Tech-bull-Miss-Agric-For-Exp-Stn. Mississippi State, Miss. : The Station. Mar 1993. (187) 38 p.
Descriptors: wood-chips; production-costs; estimation; computer- software

47.
NAL Call No.: QH301.A76-no.46
Classification as a first step in the interpretation of temporal and spatial variability of crop yield.
Lark, R. M.; Stafford, J. V. Modelling in applied biology spatial aspects, 25-27 June 1996, Brunel University /. Warwick : Association of Applied Biologists, c1996.. p. 139-142.
Includes references.
Descriptors: crop-yield; spatial-variation; fields; hordeum-vulgare; mapping; cluster-analysis; multivariate-analysis; seasonal-variation; south- east- england; multivariate-clustering; yield-mapping

48.
NAL Call No.: 58.8-J82
Classification of tissue culture segments by colour machine vision.
Alchanatis, V.; Peleg, K.; Ziv, M. J-agric-eng-res v.55(4): p.299-311. (1993 Aug.)
Includes references.
Descriptors: solanum-tuberosum; tissue-culture; explants; automation; cutting; color-sorting; machinery; vision; image-processors; plantlet-segments

Abstract: Tissue culture techniques are finding increasingly widespread applications for cloning of many plants. Protocols for mass propagation of many species have been developed, but in spite of its advantages, large-scale commercial plant propagation by tissue cultures is largely limited to ornamental plants. This is due mainly to the intensive killed labour required for subculturing the propagules and in transferring individual shoots or plantlets into and out of culture containers. In order to cut down the production costs, a certain degree of automation is essential. A cost effective approach for automation is proposed, whereby tissue culture plantlets are chopped into approximately uniformly sized segments, on a conveying production line while using colour computer vision for identifying and locating the number and positions of propagation organs, in images of the plantlet segments. Plantlet segments without propagation organs are rejected, while properly cut segments with viable buds or shoots are automatically selected for subculturing. In this paper, some initial results of this approach are reported, in which stationary images of manually pre- cut potato plantlet segments were analysed and classified. Using colour machine vision and a Neural Networkbased classifier, a basis was laid for a practical system, which may be used for automatic classification of tissue culture segments of potato plantlets. Instead if the conventional use of black and white cameras and geometric features, colour features only are used together with colour frame manipulation capabilities, which are now available in most commercial imaging boards. This facilitates accurate, high-speed classification of plantlet images.

49.
NAL Call No.: S671.A66
Climate data file management for agricultural modeling.
Robbins, K. D. Appl-eng-agric v.9(1): p.49-53. (1993 Jan.)
Includes references.
Descriptors: weather-data; models; computer-software; louisiana

Abstract: This article presents a method to effectively manage climate data information for use in agricultural modeling. The method utilizes the Network Common Data Form (netCDF) system developed by the University Consortium for Atmospheric Research (UCAR). This system offers several advantages over traditional ASCII data file formats. These include: 1) the data files are "self-describing", a description of variables, storage units, the number of observations, and supplemental descriptions of the data are contained within the netCDF file; 2) a single netCDF data file can be used with different modeling applications to reduce data redundancy and simplify file version control; 3) individual data elements, or groups of elements, can be accessed directly without sequentially scanning the file; and 4) data elements can be easily modified, deleted, or appended within the file.

50.
NAL Call No.: S539.5.J68
Climprob: software for assisting climate-related decisionmaking.
Meyer, S. J.; Ameri, S. A.; Hubbard, K. G. J-prod-agric v.9(3): p.352- 358. (1996 July-1996 Sept.)
Includes references.
Descriptors: farm-management; decision-making; computer-software; climate; weather-forecasting; probability; probability-analysis; computer- techniques; climatological-probabilities

Abstract: Agricultural decisionmakers often base climate-related decisions solely on experience. Ideally, these management decisions should be based on quantifiable information, obtained by examination of long-term climatological records. The need to quickly and easily quantify climatic information was the primary incentive for the development of ClimProb (short for climatological probabilities). ClimProb, a PC-based IBM-compatible software package, is a tool that helps guide decisions by developing probabilities of climatic events based on the climatological history of a particular weather station. This software package allows the user to choose from 17 temperature options, six precipitation options, and eight degree day options. ClimProb's design is unique in two ways. First, the user defines a time window specific to a particular application. Second, the user chooses values for thresholds, accumulations, and extremes related to this application. ClimProb's tabular output can be saved or printed. It can also be graphically represented as a time series, cumulative probability distribution, or histogram. There are over 800 data sets for the 48 contiguous states available for use in ClimProb. Originally developed for extension education, the software now has broader applications including research, classroom instruction, and service/outreach.

51.
NAL Call No.: 290.9-Am32P
Closing report on the American-Hungarian fruit harvester robot.
Kassay, L.; Slaughter, D. C.; Molnar, S. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1994. (943069) 18 p.
Paper presented at the "1994 International Summer Meeting sponsored by the American Society of Agricultural Engineers," June 19-22, 1994, Kansas City, Missouri.
Descriptors: fruit-crops; harvesters; robots

52.
NAL Call No.: aSD11.A42
Collaborative decision process support tools from global change research.
Fox, D. G.; Faber, B. G. Gen-tech-rep-RM. Fort Collins, Colo. : Rocky Mountain Forest and Range Experiment Station, Forest Service, U.S. Department of Agriculture. Aug 1995. (262) p. 127-134.
Paper presented at the "Interior West Global Change Workshop," April 25-27, 1995, Fort Collins, Colorado.
Descriptors: ecosystems; forest-management; participative-management; decision-making; decision-analysis; cooperation; models; geographical- information-systems; information-technology; national-forests; natural- resources; resource-management; forest-resources; colorado; arapaho-roosevelt- national-forest

53.
NAL Call No.: QP251.A1T5
Collection of oocytes from cattle via follicular aspiration aided by ultrasound with or without gonadotropin pretreatment and in different reproductive stages.
Bungartz, L.; Lucas Hahn, A.; Rath, D.; Niemann, H. Theriogenology v.43(3): p.667-675. (1995 Feb.)
Includes references.
Descriptors: dairy-cows; heifers; ultrasonography; follicles; ovaries; cumulus-oophorus; oocytes; blastocyst; in-vitro; fertilization; embryonic- development; estrous-cycle; fsh; ovarian-follicles

Abstract: Ultrasound-guided follicular aspiration was performed on 29 Holstein-Friesian cows/heifers twice weekly at 3- to 4-d intervals over a period of 2 consecutive estrous cycles (total 42 d). For visualization of the ovaries and guidance of the aspiration needle, a 6.5 MHz fingertip probe on a 62 cm probe carrier was inserted into the vagina. The disposable aspiration needle was connected to a permanent rinse tubing system, thus ensuring minimum death of oocytes in the aspiration processs. After penetration of the vaginal wall, the needle was inserted into a follicle of the rectally fixed ovary. Cumulus oocyte complexes (COC) were aspirated at a pressure of 100 mm Hg. In the first experiment, the effect of an additional gonadotropin treatment 4 d prior to aspiration was investigated in 8 lactating cows. Following FSH-treatment, the number of aspirated follicles was higher (P <0.05) than in the nontreated animals (10.6 +/- 0.7 vs 8.9 +/- 0.5). The number of recovered COC (7.0 +/- 0.6 vs 5.8 +/- 0.5), the recovery rate (COC per aspirated follicle) (66.6% vs 65.4%), the percentage of viable COC (56.8% vs 52.1%), the cleavage rate upon in vitro maturation and in vitro fertilization (56.7% vs 59.8%) as well as the rate of morula/blastocyst formation (3.8% vs 2.9%) were similar in both groups. In the second experiment, follicles were aspirated in 4 lactating cows, 6 dry cows, 4 pregnant cows (first 35 d of pregnancy), and 4 heifers. The average number of aspirated follicles and recovered COC was higher (P <0.05) in the first 2 groups (10.6 +/- 0.6 and 9.3 +/- 0.7 follicles; 7.2 +/- 0.5 and 6.9 +/- 0.7 oocytes) than in the 2 other treatment groups (7.3 +/- 0.5 and 8.1 +/- 0.5 follicles; 5.0 +. 52.5 and 57.4%, respectively). Similarly, upon in vitro fertilization, cleavage rate was higher (P <0.05; 63.4%) in lactating cows than in the other groups (43.7, 50.5, 55.1% respectively). A total of 21.5, 22.7, 11.9 and 13.5%, respectively, in the 4 groups of the in vitro fertilized oocytes reached the morula and blastocyst stages. After transfer of a total of 48 embryos 22 pregnancies (45.8%) were established as detected on Day 65. We conclude that 1) repeated aspiration of viable COC at short intervals is possible, 2) additional FSH-treatment does not increase oocyte yields, and 3) viable blastocysts can be produced from cattle at various reproductive phases irrespective of the reproductive phase.

54.
NAL Call No.: Q184.R4
Combined use of optical and microwave remote sensing data for crop growth monitoring.
Clevers, J. G. P. W.; Leeuwen, H. J. C. v. Remote-sens-environ v.56(1): p.42-51. (1996 Apr.)
Includes references.
Descriptors: beta-vulgaris-var; -saccharifera; yield-forecasting; accuracy; remote-sensing; leaf-area-index; microwave-radiation; satellite- imagery; growth- models; netherlands; simplified-and-universal-crop-growth- simulator-sucros

55.
NAL Call No.: QH540.E23
Combining remote sensing and climatic data to estimate net primary production across Oregon.
Law, B. E.; Waring, R. H. Ecol-appl v.4(4): p.717-728. (1994 Nov.)
Includes references.
Descriptors: coniferous-forests; woodlands; scrub; biological- production; estimation; solar-radiation; interception; vegetation; remote- sensing; thematic-mapper; reflectance; red-light; infrared-radiation; infrared- imagery; climate; climatic-factors; xylem-water-potential; leaf-conductance; oregon; stomatal-conductance; intercepted-photosynthetically-active-radiation

56.
NAL Call No.: 290.9-Am32P
Comparative risk assessment primer.
Embleton, K. M.; Jones, D. D.; Engel, B. A.; Gorsky, L. Pap-Am-Soc-Agric- Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1994. (94-3020/94-3063) 8 p.
Paper presented at the 1994 Summer Meeting sponsored by the ASAE, June 19-22, 1994, Kansas City, Missouri.
Descriptors: environmental-policy; risk; environmental-management; computer-software

57.
NAL Call No.: TD420.W374
A comparison of ERS-1 satellite radar and aerial photography for river flood mapping.
Biggin, D. S.; Blyth, K. J-Inst-Water-Environ-Manag v.10(1): p.59-64. (1996 Feb.)
Includes references.
Descriptors: rivers; flooding; mapping; aerial-photography; remote- sensing; radar; satellite-surveys; satellite-imagery; south-east-england; synthetic-aperture-radar

Abstract: The extent of floodwater inundation, whether caused by river flooding or coastal storm surges, is required quickly (a) to enable the planning of emergency relief and repairs to communications and services, and (b) for the production of river flood risk maps. Unfortunately, by their nature, most floods occur in bad weather, which can severely restrict the use of aircraft, and extensive cloud cover precludes the use of most earth observing satellites which rely on sensors operating at optical wavelengths. Synthetic aperture radar, which can penetrate clouds, allows affected areas to be imaged, regardless of cloud cover or light conditions. This paper compares satellite acquired data of river flooding with photographic records obtained from a light aircraft to demonstrate the accuracy of the technique.

58.
NAL Call No.: 4-AM34P
Comparison of near-infrared spectroscopy and other soil nitrogen availability quick tests for corn.
Fox, R. H.; Shenk, J. S.; Piekielek, W. P.; Westerhaus, M. O.; Toth, J. D.; Macneal, K. E. Agron-j v.85(5): p.1049-1053. (1993 Sept.-1993 Oct.)
Includes references.
Descriptors: zea-mays; prediction; nutrient-availability; nitrogen; soil-testing; infrared-spectroscopy; crop-yield; grain; fertilizer-requirement- determination; sampling; soil-test-values; nitrogen-fertilizers; mathematical- models; pennsylvania

Abstract: Our ability to predict N fertilizer needs for corn (Zea mays L.) is improving, but more accurate and convenient tests are still needed. This work compared a new quick test for soil N availability using a near-infrared spectrophotometer (NIRS) with three published quick tests for predicting soil N- supplying capability (NSC) and relative corn grain yield. The other tests were the pre-sidedress nitrate test (PSNT), nitrate concentration (at-plant NO3), and absorbance at 200 nm of a 0.01 M NaHCO3 extract (UV-200 test) of 0- to 20-cm soil samples taken at planting. Soil samples taken at planting from 95 field experiments in Pennsylvania were analyzed at reflectance wavelengths from 400 nm to 2500 nm with NIRS. The coefficients of determination were the same (R2 = 0.49) for both linear and quadratic regressions of NSC and NIRS test values. The abilities of the four tests to predict NSC and relative corn grain yield were compared using data from 90 of the 95 experiments. The R2 values for linear and quadratic regressions between soil test values and NSC ranged from 0.49 to 0.58 for the NIRS, PSNT, and UV-200 tests; for the at-plant NO3 test, R2 was lower (approximately 0.40). Eliminating sites where corn directly followed a legume, R2 values for quadratic regressions between test values and NSC increased to approximately 0.60 for the NIRS, PSNT, and UV-200 tests. The PSNT test was slightly better than the other tests in predicting a grain yield response to N fertilizer, but this advantage lessened when. (R2 = 0.08-0.36). The NIRS test offers a convenient, rapid, and inexpensive alternative to the PSNT for predicting whether humid-region corn fields will respond to N fertilizer.

59.
NAL Call No.: 49-J82
Comparison of transverse and longitudinal real-time ultrasound scans for prediction of lean cut yields and fat-free lean content in live pigs.
Cisneros, F.; Ellis, M.; Miller, K. D.; Novakofski, J.; Wilson, E. R.; McKeith, F. K. J-anim-sci v.74(11): p.2566-2576. (1996 Nov.)
Includes references.
Descriptors: pigs; carcass-composition; live-estimation; ultrasonography; gilts; ultrasonic-fat-meters; halothane-susceptibility; genotypes; backfat; fat- thickness; longissimus-dorsi; body-weight; prediction; regression-analysis; lean; equations; correlation; sex-differences; barrows

Abstract: Live animal real-time ultrasound scans and carcass measures were taken on 80 pigs comprising two sexes (42 barrows; 38 gilts) and two halothane genotypes (40 carriers and 40 negatives) that were slaughtered between 108 and 148 kg live weight. Transverse scans (TRUS), at right angles to the midline, were taken on right (RS) and left (LS) sides at the last rib. Longitudinal scans (LON) were taken 6.5 cm off the midline immediately anterior (ANT) and posterior (PST) to the last rib on both the RS and LS. Longissimus muscle depth and area and backfat thickness over the longissimus muscle were measured on TRUS. Backfat thickness and longissimus muscle depth were measured at each end of the LON. Backfat thickness and longissimus muscle measurements were taken at the 10th and last rib on the RS of the carcass. Carcasses were fabricated using standard techniques to establish lean cut yields and carcass soft tissue was chemically analyzed to determine fat-free lean contents. Stepwise regression analysis was performed to develop equations to predict the weights and percentages of lean cuts and fat-free lean. Fat and muscle measures taken from ultrasound scans were generally less accurate than last rib carcass measures at predicting composition. There was little difference in R2 for equations based on either TRUS or ANT/LON; however, PST/LON, generally, were less accurate than ANT/LON. Combining measurements from more than one scan gave little improvement in R2 compared with the best single scan. Estimates of sex bias for carcass composition prediction were small. Halothane genotype and carcass lean content biases were detected; equations derived from the pooled data tended.

60.
NAL Call No.: Q184.R4
Complementarity of radar and visible-infrared sensors in assessing rangeland condition.
Smith, A. M.; Major, D. J.; McNeil, R. L.; Willms, W. D.; Brisco, B.; Brown, R. J. Remote-sens-environ v.52(3): p.173-180. (1995 June)
Includes references.
Descriptors: rangelands; prairies; reflectance; satellite-imagery; radar; remote-sensing; alberta

61.
NAL Call No.: S671.A66
Composting process design computer model.
Person, H. L.; Shayya, W. H. Appl-eng-agric v.10(2): p.277-283. (1994 Mar.)
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.

62.
NAL Call No.: TD201.U61
Computer-accessible resources for Canadian water resources management.
Belk, A. F.; Heathcoate, I. W. Water-resour-update (99): p.26-29. (1995 Spring)
In the special issue: Water related information sources on the Internet / edited by F. Anderson.
Descriptors: water-resources; water-management; information-services; information-technology; telecommunications; databases; information-systems; canada; world-wide-web; internet; home-page

63.
NAL Call No.: 290.9-Am32P
Computer aided design of waste management components.
Fulhage, C. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1994. (94-4042/94-4082) 4 p.
Paper presented at the 1994 International Summer Meeting Sponsored by the American Society of Agricultural Engineers, June 19-22, 1994, Kansas City, Missouri.
Descriptors: waste-treatment; computer-software

64.
NAL Call No.: 290.9-Am32P
A computer aided management system for egg production.
Lu, C.; Bao, C.; Huang, Z.; Tang, J.; Ke, Z.; Hu, J.; Chen, J. Pap-Am-Soc- Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1993. (93-2601/93-3510) 11 p.
Paper presented at the "1993 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 14-17, 1993, Chicago, Illinois.
Descriptors: egg-production; computer-software; feed-formulation; animal-husbandry

65.
NAL Call No.: 1-Ag84y
Computer assisted management: the case of Jim and Kathy Moseley.
Doster, D. H. Yearb-agric. Washington, D.C. : U.S. Dept. of Agriculture : For sale by the Supt. of Docs., U.S. G.P.O., [1980-. 1989. p. 147-150.
In the series analytic: Farm management: How to achieve your farm business / edited by D.T. Smith.
Descriptors: farm-management; computer-software; decision-making; farm-planning; case-studies

66.
NAL Call No.: SF601.C66
A computer-based body condition management system: case example.
Hady, P. J.; Domecq, J. J.; Kaneene, J. Compend-contin-educ-pract-vet v.16(10): p.1383-1386, 1388, 1390, 1400. (1994 Oct.)
Includes references.
Descriptors: dairy-cows; body-condition; subcutaneous-fat; computer- software; computer-techniques; dry-period; equations; data-collection; data- analysis; temporal-variation

67.
NAL Call No.: 80-Ac82
A computer-based farm-management package for pineapple farms.
Sinclair, E. R. Acta-hortic (334): p.191-196. (1993 Oct.)
Paper presented at the "First International Pineapple Symposium," November 2-6, 1992, Honolulu, Hawaii.
Descriptors: ananas-comosus; crop-production; crop-husbandry; crop- management; farm-management; computer-software; computer-analysis; australia; pinerec; pinegro

68.
NAL Call No.: S530.J6
A computer-based tool for introducing turfgrass species.
Fermanian, T. W.; Wehner, D. J. J-nat-resour-life-sci-educ v.24(1): p.45-48. (1995 Spring)
Includes references.
Descriptors: lawns-and-turf; management; computer-assisted- instruction; independent-study; college-curriculum; agricultural-education; computer- software; evaluation; microcomputers; species; agronomic- characteristics; climatic-factors; adaptation; establishment

69.
NAL Call No.: SB317.5.H68
A computer-controlled drip irrigation system for container plant production.
Gonzalez, R. A.; Struve, D. K.; Brown, L. C. HortTechnology v.2(3): p.402-407. (1992 July-1992 Sept.)
Includes references.
Descriptors: quercus-rubra; seedlings; container-grown-plants; trickle-irrigation; irrigation-scheduling; evapotranspiration; computer- techniques; computer-software

70.
NAL Call No.: SB317.5.H68
A computer-controlled drip irrigation system for container plant production.
Gonzalez, R. A.; Struve, D. K.; Brown, L. C. HortTechnology v.2(3): p.402-407. (1992 July-1992 Sept.)
Includes references.
Descriptors: quercus-rubra; seedlings; container-grown-plants; trickle-irrigation; irrigation-scheduling; evapotranspiration; computer- techniques; computer-software

71.
NAL Call No.: 1.98-Ag84
Computer custom-designs flumes.
Senft, D. Agric-res v.42(6): p.21. (1994 June)
Descriptors: chutes; structural-design; computer-software; irrigation; water-management; water-flow; measurement; agricultural-research

72.
NAL Call No.: 450-R34
A computer method for producing dot distribution maps.
Angelo, R. Rhodora v.96(886): p.190-194. (1994 Apr.)
Includes references.
Descriptors: equisetum-arvense; equisetum; maps; flora; computer- software; computer-techniques; geographical-distribution; new-england-states-of- usa; equisetum-pratense

73.
NAL Call No.: SB435.5.A645
The computer: "My electronic chain saw".
Brown, D. K. Arbor-age v.14(6): p.40, 42. (1994 June)
Descriptors: arboriculture; microcomputers; computer-software; computer-techniques; treenet

74.
NAL Call No.: 58.9-In7
A computer program for determining animate and inanimate power requirements for mechanised agriculture.
Aderoba, A. A. Agric-eng v.49(2): p.60-63. (1994 Summer)
Includes references.
Descriptors: farming; power-requirement; animal-power; human-power; computer-software; tractors; power; mechanization; appropriate-technology; models; production-costs; economic-analysis; economic-models; mechanical-power

75.
NAL Call No.: 4-AM34P
A computer program to analyze multiple-season crop model outputs.
Thornton, P. K.; Hoogenboom, G.; Wilkens, P. W.; Bowen, W. T. Agron-j v.87(1): p.131-136. (1995 Jan.-1995 Feb.)
Includes references.
Descriptors: computer-software; growth-models; simulation-models; computer-simulation; cropping-systems; rotations; crop-residues; crop-yield; soil- water; soil-fertility; long-term-experiments; sustainability; economic- analysis; crop-production; returns; prices; costs; crop-sequences

Abstract: Management-oriented simulation models of the growth, development, and yield of annual crops are useful tools for screening management options on the computer. Until recently, a limitation of these models has been the inability to simulate more than one cropping season at a time. The capability to simulate long-term field experiments with such models now exists, in which the simulated soil water, N, organic C, and crop residue outputs from one model run become the input conditions for the next. Simulations of crop rotations can produce large quantities of data, especially if the simulation experiment involves replications across different years. Computer software was written to perform simple analyses of such simulation experiments. The major purpose of the software is to allow the user to investigate the stability and profitability of crop sequences. The program calculates summary statistics for model output variables; these are presented to the user in tabular and graphical forms. Net monetary returns or gross margins can also be calculated, and price and cost variability can be taken into account in the analysis. The program allows rapid, preliminary analysis of a particular crop sequence from replicated simulation experiments and can help the user to assess whether the sequence warrants further evaluation. The program can also be used to summarize the results from historical long-term field trials. The analyses performed constitute a first step in investigating the sustainability of a particular cropping sequence for a specified length of time.

76.
NAL Call No.: 4-AM34P
A computer program to analyze single-season crop model outputs.
Thornton, P. K.; Hoogenboom, G. Agron-j v.86(5): p.860-868. (1994 Sept.-1994 Oct.)
Includes references.
Descriptors: crops; growth-models; computer-software; simulation- models; computer-simulation; microcomputers; economic-analysis; data-analysis

Abstract: Computer simulation models of the growth, development, and yield of annual crops can produce large quantities of data, especially if a simulation experiment involves many treatments and replications across different years. Computer software was written to perform simple analyses of such experiments, allowing the user to identify those treatments that are productive, stable, economically attractive, environmentally sound, or otherwise suitable for the purposes of the investigator. The computer program, which runs on a DOS (IBM-compatible) personal computer, can interface with output files produced by any crop model run on any other computer that conforms to a common output file structure. Summary statistics for a wide variety of model output variables are calculated and presented to the user in a number of tabular and graphical forms. Net monetary returns and gross margins can also be calculated, and price-cost variability can be taken into account in the analysis. The user can perform an economic comparison of simulation treatments using mean-Gini stochastic dominance or, visually, mean variance analysis. The results of all calculations and analyses are written to an output file that can be manipulated by the user to provide input to a spreadsheet or statistical package for further analysis of the simulated data. The program allows rapid, preliminary analysis of treatments from replicated simulation experiments and can help the user to identify particularly promising treatments that warrant further evaluation.

77.
NAL Call No.: aS21.R44A7
A computer program to assist nematode management in Georgia peach orchards.
Bertrand, P. F.; Taylor, B. G. ARS (122): p.92-105. (1994 Apr.)
Proceeding of the sixth Stone Fruit Tree Decline Workshop on New Insights & Alternative Management Strategies held October 26-28, 1992, Fort Valley, Georgia.
Descriptors: prunus-persica; orchards; plant-parasitic-nematodes; nematode-control; computer-software; georgia

78.
NAL Call No.: TD365.C54-1995
Computer programs to implement a livestock manure management plan.
Jones, D. D.; Sutton, A. L.; Huber, D. M.; Joern, B. C. Clean water, clean environment, 21st century team agriculture, working to protect water resources conference proceedings, March 5-8, 1995, Kansas City, Missouri /. St. Joseph, Mich. : ASAE, c1995.. v. 2 p. 87-90.
Includes references.
Descriptors: computer-software; manures; application-to-land; management; planning; application-date; storage; a-manure-program; budget- program

79.
NAL Call No.: S494.5.D3C652
Computer use and factors influencing computer adoption among commercial farmers in Natal Province, South Africa.
Woodburn, M. R.; Ortmann, G. F.; Levin, J. B. Comput-electron-agric v.11(2/3): p.183-194. (1994 Nov.)
Includes references.
Descriptors: microcomputers; commercial-farming; innovation-adoption; farm-management; farm-surveys; factor-analysis; demography; south-africa

80.
NAL Call No.: 290.9-Am32P
Computer vision for plant embryo quality evaluation.
Cheng, Z.; Ling, P. P. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1992. (923575) 14 p.
Paper presented at the "1992 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 15-18, 1992, Nashville, Tennessee.
Descriptors: imagery; coffee; computers; plant-embryos

81.
NAL Call No.: 290.9-Am32P
Computer vision for selecting somatic embryos.
Kurata, K.; Terada, M.; Komine, M.; Liyanage, K. H. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1991. (913054) 7 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: carrots; somatic-embryogenesis; computers; vision

82.
NAL Call No.: 290.9-Am32P
Computer vision identifiication on tomato seedlings in natural outdoor scenes.
Tian, L.; Slaughter, D. C. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Winter 1993. (93-3608) 17 p.
Paper presented at the "1993 International Winter Meeting sponsored by the American Society of Agricultural Engineers," December 13-17, 1993, Chicago, Illinois.
Descriptors: lycopersicon-esculentum; imagery; seedlings; algorithms; cotyledons; computer-analysis

83.
NAL Call No.: S494.5.D3C652
Computer vision system for on-line sorting of pot plants using an artificial neural network classifier.
Timmermans, A. J. M.; Hulzebosch, A. A. Comput-electron-agric v.15(1): p.41-55. (1996 May)
Includes references.
Descriptors: pot-plants; grading; computer-software; computer- hardware; imagery; discriminant-analysis; classification; sorting; patterns; quality; cactaceae; saintpaulia

84.
NAL Call No.: S494.5.D3C652
A computerised method for systematically analysing the livestock component of farming systems.
Udo, H. M. J.; Brouwer, B. O. Comput-electron-agric v.9(4): p.335-356. (1993 Dec.)
Includes references.
Descriptors: livestock-farming; farming-systems; small-farms; computer-techniques; data-collection; data-analysis; simulation-models; computer-software; livestock-numbers; population-dynamics; feeds; traction

85.
NAL Call No.: 47.8-Am33P
Computerization of recording and calculating egg production with programming designed for scientific research.
McDaniel, C. D.; Hester, P. Y. Poultry-sci v.73(4): p.591-595. (1994 Apr.)
Includes references.
Descriptors: egg-production; computer-software; data-collection; egg- shell-quality; accuracy; automation; labeling

Abstract: A computerized system for recording and calculating egg production, titled EGGSPERT, was developed to decrease the amount of time required for manual calculation of hen-day production. For 4 wk of production, hard-shelled (HS), soft-shelled (SS), shell-less (SL), SS + SL, and total hen- day egg productions were recorded and calculated both by hand and by the EGGSPERT system for 900 hens divided into 60 experimental units. Both methods of egg production analysis produced similar results with respect to HS, SS, SS + SL, and total hen-day production. However, analysis of SL egg production revealed a small, although significant (P& lt;.05) increase of computerized recording when compared with the manual method of recording and calculating egg production (1.39 vs 1.31%, SEM = .03). A major advantage of the EGGSPERT system was a 6.4 h/wk decrease in time and labor required to total and calculate hen- day egg production when compared with the manual method of calculation. In conclusion, the EGGSPERT system was found to be a very reliable, accurate, and timesaving method for recording and calculating egg production.

86.
NAL Call No.: SB435.5.A645
Computerized arborists: the end of the paper chase.
Delia, T. Arbor-age v.13(11): p.38-39. (1993 Nov.)
Descriptors: arboriculture; urban-forestry; computer-software; information-technology; record-keeping; treekeeper

87.
NAL Call No.: 99.8-F768
Computerized tools for participatory national forest planning.
Dean, D. J. J-for v.92(2): p.37-40. (1994 Feb.)
Includes references.
Descriptors: forest-management; planning; computer-software; usda; usda-forest-service

88.
NAL Call No.: 290.9-Am32P
Concept modeling automated seedling transfer from growing trays to shipping modules.
Brewer, H. L. Pap-Am-Soc-Agric-Eng. St. Joseph, Mich. : American Society of Agricultural Engineers,. Summer 1993. (933089) 18 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: vegetables; seedlings; transplanters; robots; automation

89.
NAL Call No.: Z672.I53
The concept of the literature and factural data management system LIMAS.
Plath, M.; Mangstl, A.; Pohlmann, J. M.; Friedrich, H. Q-bull-Int-Assoc- Agric-Inf-Spec v.41(2): p.226-228. (1996)
Descriptors: agricultural-sciences; forestry; information-services; information-technology; databases; management; microcomputers; telecommunications; information-retrieval; germany; german-information-system- on-food,-agriculture-and-forestry; literative-and-factual-data-management- systems; german-centre-for-agricultural- information-and-documentation-zadi; wide-area-networks; german-agricultural-information-network-gain

90.
NAL Call No.: S539.5.J68
Concepts of variable rate technology with considerations for fertilizer application.
Sawyer, J. E. J-prod-agric v.7(2): p.195-201. (1994 Apr.-1994 June)
Includes references.
Descriptors: crop-production; fertilizers; application-rates; variation; optimization; efficiency; profitability

91.
NAL Call No.: 290.9-Am32T
Conceptual modeling automated seedling transfer from growing trays to shipping modules.
Brewer, H. L. Trans-ASAE v.37(4): p.1043-1051. (1994 July-1994 Aug.)
Includes references.
Descriptors: transplanters; seedlings; transplanting; automation; computer-techniques; computer-analysis; computer-simulation; robots; containers; container-grown-plants; planting-stock; computer-assisted-design

Abstract: Automated field transplanters can plant several hundred seedlings per row per minute if the seedlings are presented to the transplanter in modules. Seedlings are grown in trays and transferred to the modules so that each cell in each module has a good seedling. If the operations to transform seeds into seedlings transplanted infields are automated, then machines to transfer seedlings from trays to modules must be developed. An experimental machine built in 1991 ejected plugs from cells, gripped stems of seedlings and lifted them, transferred seedlings from tray to module, and dropped seedlings into a module. The machine was slow and incomplete. This article reports on a design which was conceptually modeled on a computer to correct the deficiencies of the experimental machine that was build. Projections from the conceptual model indicate that three 200-cell trays of seedlings can be transferred per minute, which is about 80% of the rate required by one field transplanter.

92.
NAL Call No.: SB249.N6
Considerations for selecting a crop model.
Porter, D. O. Proc-Beltwide-Cotton-Conf. Memphis, Tenn. : National Cotton Council of America, 1991-. 1995. v. 1 p. 439-440.
Meeting held January 4-7, 1995, San Antonio, Texas.
Descriptors: crops; simulation; simulation-models; decision-making; computer-software; computer-hardware; usa

93.
NAL Call No.: 49-J82
Considerations on genetic connectedness between management units under an animal model.
Kennedy, B. W.; Trus, D. J-anim-sci v.71(9): p.2341-2352. (1993 Sept.)
Includes references.
Descriptors: livestock; animal-models; environmental-factors; genetic- analysis; genetic-variance; mathematical-models; prediction

Abstract: Connectedness among management units (e.g., herds or regions) is of concern in genetic evaluation. When genetic evaluation is under an animal model, connections occur through A, the numerator relationship matrix. It is argued that the most appropriate measure of connectedness is the average prediction error variance (PEV) of differences in EBV between animals in different management units. It is shown that PEV of differences is influenced by average genetic relationship between and within management units, which in turn affects the variances of estimates of differences between management unit effects. When PEV of differences cannot be computed, use of one of three alternative measures is proposed; the gene-flow method that measures the exchange of genes between management units, measurement of genetic drift variance based on average relationships between and within management units, and measurement of the variance of estimated differences between management units effects. These were correlated with PEV of differences in a test simulation. The gene-flow method, which is simplest to compute, had the lowest correlation (.671). The drift variance and variance of management unit effects methods were highly correlated with PEV of differences (.924 and .995, respectively).

94.
NAL Call No.: SB317.5.H68
Construction and use of an inexpensive in vitro ultrasonic misting system.
Tisserat, B.; Jones, D.; Galletta, P. D. HortTechnology v.3(1): p.75- 78. (1993 Jan.-1993 Mar.)
Includes references.
Descriptors: daucus-carota; tissue-culture; cultural-methods; micropropagation; nutrient-film-techniques; mist-irrigation; ultrasonics; aeroponics

95.
NAL Call No.: 58.8-J82
The control of errors in momentary yield data from combine harvesters.
Thylen, L.; Murphy, D. P. L. J-agric-eng-res v.64(4): p.271-278. (1996 Aug.)
Includes references.
Descriptors: combine-harvesters; grain; crop-yield; sensors; flow- meters; spatial-variation; monitoring; techniques; systems; errors; accuracy; data- collection; automation; microcomputers; kriging; statistical-analysis; yield-mapping; grain-flow-sensors; global-positioning-systems; data-screening- techniques; geostatistical-analysis

96.
NAL Call No.: 79.8-W41
Controlling weeds in corn (Zea mays) rows with an in-row cultivator versus decisions made by a computer model.
Schweizer, E. E.; Westra, P.; Lybecker, D. W. Weed-sci v.42(4): p.593- 600. (1994 Oct.-1994 Dec.)
Includes references.
Descriptors: zea-mays; cultural-weed-control; tillage; timing; decision-making; computer-software; computer-simulation; seed-banks; weeds; population- density; emergence; cultivators; crop-yield; grain; economic- analysis; gross-margins; weedcam

Abstract: A 3-yr field study was conducted to compare an in-row cultivator versus a standard row-crop cultivator to decisions made with WEEDCAM, a weed/corn management computer decision aid, for controlling annual weeds within the row in irrigated corn. In the absence of herbicides, weeds were always controlled better with the in-row cultivator than with the standard row- crop cultivator. However, grain yield and gross margin were affected only in 1991 when weeds emerged simultaneously with corn, and rain delayed the first cultivation 10 d. The in-row cultivator plots not only averaged 34% more grain ha-1 than the standard row-crop cultivator plots, but gross margin was $143 ha-1 more. Weed densities each year were about 95% less in plots managed in accordance with the computer model WEEDCAM simulations than in the non-herbicide treated post-planting tillage plots. Grain yields and gross margins were not affected by weed seedbank density, pre-cultivation tillage, or type of cultivator when weed management decisions were based on WEEDCAM simulation ranking. In the absence of herbicides, weeds can be controlled successfully in corn with an in-new cultivator, but success will depend on such factors as weed seedbank density, cultivation timeliness, and relative time of weed and corn emergence.

97.
NAL Call No.: S494.5.D3C652
CORAC, hops protection management systems.
Mozny, M.; Krejci, J.; Kott, I. Comput-electron-agric v.9(2): p.103- 110. (1993 Sept.)
Includes references.
Descriptors: hops; pseudoperonospora-humuli; phorodon-humuli; otiorhynchus-ligustici; plant-protection; simulation-models; microcomputers

98.
NAL Call No.: aHD9415.C67--1996
COSTBEN.wk4 : Lotus spreadsheet. COSTBEN. Documentation for the Animal Product Branch's cost-benefit calculation model for red meat and poultry.
Hahn, W. F.; United States. Dept. of Agriculture. Economic Research Service. Commercial Agriculture Division. [Washington, D.C.] : Economic Research Service, Commercial Agriculture Division, [1996] 1 computer disk 1 manual (15 p. ; 28 cm.)
Title from disk label. Title on manual: Documentation for the Animal Product Branch's cost-benefit calculation model for red meat and poultry / William F. Hahn. "April 1996"--Manual.
Descriptors: Animal-industry-United-States-Mathematical-models- Software; Livestock-United-States-Mathematical-models-Software; Poultry- industry- United-States-Mathematical-models-Software

Abstract: A spreadsheet model designed to forecast the effects of supply and demand shifts on livestock, meat, and poultry markets. This is not a stand- alone model and requires a pre-existing baseline forecast of production, trade, consumption and prices.

99.
NAL Call No.: SB249.N6
COTMAN: a computer-aided cotton management system for late-season practices.
Zhang, J. P.; Tugwell, N. P.; Cochran, M. J.; Bourland, F. M.; Oosterhuis, D. M.; Klein, C. D. Proc-Beltwide-Cotton-Conf. Memphis, Tenn. : National Cotton Council of America, 1991-. 1994. v. 3 p. 1286-1287.
Meeting held January 5-8, 1994, San Diego, California.
Descriptors: gossypium; expert-systems; crop-management; decision- making; computer-software

100.
NAL Call No.: 100-T31M
COTTAM: A cotton plant simulation model for an IBM PC microcomputer.
Jackson, B. S.; Arkin, G. F.; Hearn, A. B. Misc-publ,-Tex-Agric-Exp-Stn. College Station, Tex. : Texas Agricultural Experiment Station. Aug 1990. (1685) 242 p.
COTTAM software on one 5 1/4 inch diskette accompanies this article.
Descriptors: gossypium-hirsutum; crop-management; simulation-models; computer-simulation; microcomputers; computer-software

101.
NAL Call No.: S494.5.D3C652
Cow status monitoring (health and oestrus) using detection sensors.
Maatje, K.; Mol, R. M. de.; Rossing, W. Comput-electron-agric v.16(3): p.245-254. (1997 Feb.)
Includes references.
Descriptors: dairy-cows; bovine-mastitis; estrus; detection; diagnosis; automation; monitoring; sensors; milk-yield; temperature; electrical- conductivity; physical-activity; accuracy; microcomputers

102.
NAL Call No.: T1.I59
A critical perspective on information technology management: the case of electronic data interchange.
Gottardi, G.; Bolisani, E. Int-j-technol-manag v.12(4): p.369-390. (1996)
Includes references.

103.
NAL Call No.: 100-C12Cag
Crop management goes high-tech.
Calif-agric v.50(3): p.8. (1996 May-1996 June)
Descriptors: crop-management; monitoring; aerial-photography; photointerpretation; aerial-surveys; microcomputers; technology; california

104.
NAL Call No.: S627.C76C77--1995
Crop residue management-- gaining ground in the 90's : Enhanced Residue Management Planning Program. Updated. Enhanced Residue Management Planning Program.
American Cyanamid Company. [S.l.] : American Cyanamid, 1995. 1 computer disk : col.
Title from disk label.
Descriptors: Crop-residue-management-United-States-Software; Conservation-tillage-United-States-Software

105.
NAL Call No.: S441.S8557
CROPS, the crop rotation planning system, for whole-farm environmental and economic planning.
Stone, N. D. Agriculture in Concert with the Environment ACE research projects Southern Region. [1991-. 1995. 40 p.
SARE Project Number AS92-4. Record includes floppy disk. Record includes several articles on project. Date of report is May 1995. This is a final report.
Descriptors: alternative-farming; sustainability; crop-management; animal-wastes; management; economic-evaluation; computer-software; farm- planning; virginia; north-carolina; sustainable-farming-practices

106.
NAL Call No.: 4-AM34P
CropSyst: a collection of object-oriented simulation models of agricultural systems.
Van Evert, F. K.; Campbell, G. S. Agron-j v.86(2): p.325-331. (1994 Mar.-1994 Apr.)
Includes references.
Descriptors: computer-software; simulation-models; cropping-systems; crop-yield; pesticides; diuraphis-noxia; decision-making; plant-pests; washington

Abstract: Simulation of whole agricultural systems is now widely used in agronomy. Construction and maintenance of the large simulation models required for agricultural systems may benefit from the application of modern programming methods. In particular, object-oriented programming (OOP) methods claim several advantages over conventional procedural methods. We sought a programming approach that would allow (i) interchanging of component models within and between whole-system models, (ii) incremental model building without rewriting existing code, (iii) maintenance of more than one model of a component, and (iv) construction of a user-friendly interface from which all parameters can be assigned and component models run. Here we report results of an experiment in which we used OOP to construct a cropping system model called CropSyst. An OOP analysis of cropping systems led to the abstraction of component systems (objects) with minimal and well-defined interfaces. Examples of components, or objects, used in Cropsyst are Time, Weather, Crop, Soil, Crop residue, Tillage, Erosion, Aphid population, Aphid immigration, Pesticide application, Planting, Crop rotation, and Output. Different versions of CropSyst were implemented and used to simulate production and erosion for cropping systems in eastern Washington, and to simulate yield loss and pesticide dynamics associated with Russian Wheat Aphid infestation. These were constructed from existing objects. Different versions of the Crop object simulated the different crops in a rotation cycle. Parameters were assigned and models were run from a commercially supplied user interface, which was also programmed using OOP. We were able to meet our objectives using OOP.

107.
NAL Call No.: SB1.H6
Cultivation of grafted vegetables. II. Development of grafting robots in Japan.
Kurata, K. HortScience v.29(4): p.240-244. (1994 Apr.)
Includes references.
Descriptors: vegetables; grafting; robots; mechanization; prototypes; japan

108.
NAL Call No.: SF1.A56
Customized selection indices for dairy bulls in Australia.
Bowman, P. J.; Visschert, P. M.; Goddard, M. E. Anim-sci v.62(pt.3): p.393-403. (1996 June)
Includes references.
Descriptors: dairy-bulls; selection-index; breeding-programs; quantitative-traits; computer-software; milk-yield; milk-fat-yield; milk- protein-yield; productive-life; body-weight; milking-rate; temperament; sire- evaluation; breeding-value; heritability; genetic-correlation; profitability; equations- ; phenotypic-variation; australia

109.
NAL Call No.: SF247.D49--1995
The dairy control and management system in the robotic milking farm.
Devir, S. [1995?] 174, 6 p. : ill., Thesis (doctoral)--Landbouwuniversiteit te Wageningen, 1995.
Descriptors: Milking-machines; Dairying-Automation; Dairy-farms- Management

110.
NAL Call No.: 44.8-J822
Dairy-L: an electronic information exchange network for professionals advising dairy producers.
Varner, M. A.; Cady, R. A. J-dairy-sci v.76(8): p.2325-2331. (1993 Aug.)
Includes references.
Descriptors: dairy-industry; telecommunications; computer-techniques; computer-software; e-mail

Abstract: The objective of this study was to establish an electronic information exchange network, called Dairy-L, for professionals who advise dairy producers. Usage rates and types of communications were monitored to determine the utility of Dairy-L to dairy science programs. Listserv software loaded on an IBM 3081 mainframe computer was used to maintain a list of electronic mail addresses and to process submitted electronic mail for distribution to subscribers. The existence of Dairy-L was announced to ADSA Production Division members at meetings, by electronic mail, and by personal letter. Since its inception in February 1990 through December 1992, Dairy-L membership has increased to 322 subscribers. At various times, there have been subscribers from as many as 42 states and territories and 23 countries. Most subscribers were from academic institutions, but many were from private industry, demonstrating the potential for more widespread appeal. A total of 1342 messages were sent; most were questions and associated responses. Few questions went unanswered. Most questions received a response in less than 1 d. A network for professionals advising dairy producers has been successfully established, and use of Dairy-L is summarized.

111.
NAL Call No.: S37.F72
Dairy production and management records.
Pennington, J. A. FSA-Univ-Ark-Syst-Coop-Ext-Serv. [Little Rock, Ark.] : Cooperative Extension Service,. Nov 1994. (4005) 4 p.
Descriptors: dairy-herds; management; record-keeping; decision-making; computer-software; information-systems

112.
NAL Call No.: SB249.N6
Data logger technology and demonstration.
Munier, D. J. Proc-Beltwide-Cotton-Conf. Memphis, Tenn. : National Cotton Council of America, 1991-. 1994. v. 1 p. 195.
Meeting held January 5-8, San Diego, California.
Descriptors: gossypium; data-collection; monitoring; computer- software; decision-making; crop-production

113.
NAL Call No.: SB249.N6
Days suitable for fieldwork in Mississippi.
Spurlock, S. R.; Buehring, N. W.; Caillavet, D. F. Proc-Beltwide-Cotton- Conf. Memphis, Tenn. : National Cotton Council of America, 1991-. 1995. v. 1 p. 383-387.
Meeting held January 4-7, 1995, San Antonio, Texas.
Descriptors: gossypium; workable-days; risk; production-costs; weather-patterns; tillage; conservation-tillage; computer-software; no-tillage; farm- planning; mississippi

114.
NAL Call No.: 275.29-Ar4Mi
DD50 computerized rice management program.
Slaton, N.; Helms, R.; Wells, B. MP. [Little Rock] : Agricultural Extension Service, University of Arkansas Division of Agriculture ; [Washington, D.C.] : U.S. Dept. of Agriculture,. Jan 1994. (192,rev.) p. 24-27.
In the series analytic: Rice production handbook / edited by R.S. Helms.
Descriptors: oryza-sativa; crop-management; computer-software; prediction; growth-stages; herbicides; insect-pests

115.
NAL Call No.: SF85.4.A8A97
A decision support approach to sustainable grazing management for spatially heterogeneous rangeland paddocks.
Bellamy, J. A.; Lowes, D.; Ash, A. J.; McIvor, J. G.; Macleod, N. D. Rangeland-j v.18(2): p.370-391. (1996)
Includes references.
Descriptors: range-management; decision-making; computer-software; computer-analysis; australia

116.
NAL Call No.: 290.9-AM3Ps-IR
Decision support model for irrigation water management.
Prajamwong, S.; Merkley, G. P.; Allen, R. G. J-irrig-drain-eng v.123(2): p.106-113. (1997 Mar.-1997 Apr.)
Includes references.
Descriptors: irrigation-water; water-management; irrigation- requirements; irrigated-farming; decision-making; prediction; computer-software; simulation- models; soil-water-balance; water-supply; soil-properties; crop- yield; weather-data; utah; thailand; command-area-decision-support-model

117.
NAL Call No.: QA76.76.E95A5
A decision support system for designing juniper control treatments.
Engle, D. M.; Bernardo, D. J.; Hunter, T. D.; Stritzke, J. F.; Bidwell, T. G. AI-appl v.10(1): p.1-11. (1996)
Includes references.
Descriptors: woody-weeds; juniperus; computer-software; weed-control

118.
NAL Call No.: S494.5.D3C652
A decision support system for forecasting infestations of the black bean aphid, Aphis fabae Scop., on spring-sown field beans, Vicia faba.
Knight, J. D.; Cammell, M. E. Comput-electron-agric v.10(3): p.269-279. (1994 June)
Includes references.
Descriptors: aphis-fabae; vicia-faba; infestation; forecasting; decision-making; farm-management; computer-software

119.
NAL Call No.: S494.5.D3C652
A decision support system for mechanical harvesting and transportation of sugarcane in Thailand.
Singh, G.; Pathak, B. K. Comput-electron-agric v.11(2/3): p.173-182. (1994 Nov.)
Includes references.
Descriptors: sugarcane; mechanical-harvesting; transport; decision- analysis; computer-techniques; simulation-models; computer-software; thailand

120.
NAL Call No.: TD930.A55-1995
Decision support system for total watershed management.
Prato, T.; Fulcher, C.; Xu, F. Animal waste and the land-water interface /. Boca Raton : Lewis Publishers, c1995.. p. 333-342.
Includes references.
Descriptors: watershed-management; land-use; computer-programming; simulation-models; geographical-information-systems; models; decision-making; water-quality; pollution-control; computer-software; missouri; economic-models; wamadss

121.
NAL Call No.: SD13.C35
A decision support system that links short-term silvicultural operatingplans with long-term forest-level strategic plans.
Davis, R. G.; Martell, D. L. Can-j-for-res. Ottawa, National Research Council of Canada. June 1993. v. 23 (6) p. 1078-1095.
Includes references.
Descriptors: forest-management; silviculture; planning; decision- making; geographical-information-systems; computer-software; silviplan

Abstract: This paper describes a decision support system that forest managers can use to help evaluate short-term, site-specific silvicultural operating plans in terms of their potential impact on long-term, forest-level strategic objectives. The system is based upon strategic and tactical forest- level silvicultural planning models that are linked with each other and with a geographical information system. Managers can first use the strategic mathematical programming model to develop broad silvicultural strategies based on aggregate timber strata. These strategies help them to subjectively delineate specific candidate sites that might be treated during the first 10 years of a much longer planning horizon using a geographical information system and to describe potential silvicultural prescriptions for each candidate site. The tactical model identifies an annual silvicultural schedule for these candidate sites in the first 10 years, and a harvesting and regeneration schedule by 10- year periods for aggregate timber strata for the remainder of the planning horizon, that will maximize the sustainable yield of one or more timber species in the whole forest, given the candidate sites and treatments specified by the managers. The system is demonstrated on a 90 000 - ha area in northeastern Ontario.

122.
NAL Call No.: QA76.76.E95A5
Decision support system to interpret soil-moisture sensor readings for crop water management.
Thomson, S. J. AI-appl v.10(1): p.57-66. (1996)
Includes references.
Descriptors: irrigation-scheduling; computer-software

123.
NAL Call No.: DISS--F1994113
Design and evaluation of an optical scanner based log grading and sorting system for Scots Pine (Pinus sylvestris L.) sawlogs.
Grace, L. A. [Uppsala? : s.n., 1994?]. 1 v. (various paging) : ill., Thesis (doctoral)--The Swedish University of Agricultural Sciences, 1994.

124.
NAL Call No.: 58.8-J82
Design and management optimization of trickle irrigation systems using non-linear programming.
Saad, J. C. C.; Frizzo