PUBLICATIONS

 

 

Books and Book Chapters : 

1.         Maas, S. J.  2003.  Irrigation scheduling by remote sensing technologies.  In B. A. Stewart and T. A. Howell (Eds.), Encyclopedia of Water Science.  Marcel Dekker, New York, NY.  pp. 523-527.

 

2.         Moran, M. S., S. Maas, V. Vandebilt, S. Miller, and E. Barnes.  Natural resources and environment:  Irrigated agriculture.  In S. L. Ustin (Ed.), Manual of Remote Sensing, Vol. 5.  John Wiley and Sons, New York, NY.  pp. 617-676.

 

Refereed Publications: 

1.         Arkin, G. F., J. T. Ritchie, and S. J. Maas.  1978.  A model for calculating light interception by a sorghum canopy.  Trans. ASAE, 21(2):303-308.

 

2.         Arkin, G. F., C. W. Richardson, and S. J. Maas.  1978.  Forecasting grain sorghum yields using probability functions.  Trans. ASAE, 21(5):874-877, 880.

 

3.         Arkin, G. F., S. J. Maas, and C. W. Richardson.  1980.  Forecasting grain sorghum yields using simulated weather data and updating techniques.  Trans. ASAE, 23(3):676-680.

 

4.         Maas, S. J. and G. F. Arkin.  1980.  Sensitivity analysis of SORGF, a grain sorghum model.  Trans. ASAE, 23(3)671-675.

 

5.         Maas, S. J., G. F. Arkin, and W. D. Rosenthal.  1987.  Relationships between the areas of successive leaves on grain sorghum.  Agronomy J. 79(4):739-745.

 

6.         Maas, S. J.  1988.  Use of remotely sensed information in agricultural crop growth models.  Ecological Model. 41:247-268.

 

7.         Maas, S. J.  1988.  Using satellite data to improve model estimates of crop yield.  Agronomy J. 80(4):655-662.

 

8.         Maas, S. J. and J. R. Dunlap.  1989.  Reflectance, transmittance, and absorptance of light by normal, etiolated, and albino corn leaves.  Agronomy J. 81(1):105-110.

 

9.         Maas, S. J.  1991.  Use of remotely sensed information in plant growth simulation models.  Advances in Agronomy, Council for Scientific Research Integration.  Trivandrum, India.  1:17-26.

 

10.       Delecolle, R., S. J. Maas, M Guerif, and F. Baret.  1992.  Remote sensing and crop production models: Present trends.  ISPRS J. of Photogrammetry and Remote Sensing 47:145-161.

 

11.       Maas, S. J.  1992.  GRAMI: A crop growth model that can use remotely sensed information.  Pub. ARS-91, Washington, DC.  78 pp.

 

12.       Wiegand, C. L., S. J. Maas, J. K. Aase, J. L. Hatfield, P. J. Pinter, Jr., R. D. Jackson, E. T. Kanemasu, and R. L. Lapitan.  1992.  Multisite analysis of spectral-biophysical data for wheat.  Remote Sensing of Environ. 42:1-21.

 

13.       Maas, S. J.  1993.  Parameterized model of Gramineous crop growth: I. Leaf area and dry mass simulation.  Agronomy J. 85:348-353.

 

14.       Maas, S. J.  1993.  Parameterized model of Gramineous crop growth: II. Within-season simulation calibration.  Agronomy J. 85:354-358.

 

15.       Maas, S. J.   1993.  Within-season calibration of modeled wheat growth using remote sensing and field sampling.  Agronomy J. 85:669-672.

 

16.       Moran, M. S., S. J. Maas, and P. J. Pinter.  1995.  Combining remote sensing and modeling for estimating surface evaporation and biomass production.  Remote Sensing Rev. 12:335-353.

 

17.       Maas, S. J.  1997.  Structure and reflectance of irrigated cotton leaf canopies.  Agronomy J. 89(1):54-59.

 

18.       Maas, S. J.  1998.  Method for estimating cotton canopy ground cover from remotely sensed scene reflectance.  Agronomy J. 90(3):384-388.

 

19.       Maas, S. J.  2000.  Linear mixture modeling approach for estimating cotton canopy ground cover using satellite multispectral imagery.  Remote Sensing Environ. 72(3):304-308.

 

20.       Dabrowska-Zielinska, K., M. S. Moran, S. J. Maas, P. J. Pinter, Jr., B. A. Kimball, T. A. Mitchell, T. A. Clarke, and J. Qi.  2001.  Demonstration of a remote sensing/modeling approach for irrigation scheduling and crop growth forecasting.  J. Water and Land Devel.  5:69-87.

 

21.       Officer, S., R. J. Lascano, J. Booker, and S. J. Maas.  2003.  Comparison of methods to extract correlations for canonical correlation analysis of cotton yields.  In J. Stafford and A. Werner (Eds.),  Precision Agriculture (peer-reviewed papers from the 4th European Conference on Precision Agriculture).  Wageningen Academic Publishers, the Netherlands.  pp. 475-480.

 

22.       Wanjura, D. F., D. R. Upchurch, S. J. Maas, and J. C. Winslow.  2003.  Spectral detection of emergence in corn and cotton.  J.  Precision Agriculture.  4:385-399.

 

23.       Fitzgerald, G. J., S. J. Maas,  and W. R. DeTar.  2004.  Spider mite detection and canopy component mapping in cotton using hyperspectral imagery and spectral mixture analysis.  J.  Precision Agriculture.  5:279-289.

 

24.       Wanjura, D. F., S. J. Maas, D. R. Upchurch, and J. C. Winslow.  2004.  Scanned and spot measured canopy temperatures of cotton and corn.  Computers and Electronics in Agriculture.  44:33-48.

 

25.       Baez, A. D., J. Kiniry, S. J. Maas, M. Tiscereno, J. Macias, J. Mendoza, C. Richardson, J. Salinas G., and J. R. Manjarrez.  2005.  Large-area maize yield forecasting using leaf area index based yield model.  Agronomy Journal.  97(2):418-425.

 

26.       Ko, J., S. J. Maas, R. J. Lascano, and D. Wanjura.  Modification of the GRAMI model for cotton.  Agronomy Journal, accepted.

 

27.       Bronson, K. F., J. D. Booker, S. J. Officer, R. J. Lascano, S. J. Maas, S. W. Searcy, and J. Booker.  2005.  Apparent electrical conductivity and soil properties in the Southern High Plains.  J. of Precision Agric.  6:297-311.

 

 

Technical Publications/Popular Articles:

1.         Maas, S. J. and J. R. Scoggins.  Structure of atmospheric turbulence in the friction layer below 500 meters.  NASA CR-2650.  National Aeronautics and Space Administration.  Washington, DC.  76 pp.

 

2.         Maas, S. J. and G. F. Arkin.  1978.  User’s guide to SORGF: A dynamic grain sorghum growth model with feedback capacity.  Research Center Program and Model Documentation No. 78-1, Texas Agricultural Experiment Station.  College Station, TX.  110 pp.

 

3.         Arkin, G. F., S. J. Maas, R. A. Fuhrmann, and R. W. Young.  1979.  1978-79 Tri-State Winter Wheat Study: Field data summary.  Texas Agricultural Experiment Station, Blackland Research Center.  Temple, TX.  115 pp.

 

4.         Arkin, G. F., S. J. Maas, R. A. Fuhrmann.  1979.  1978-79 Tri-State Winter Wheat Study: Weather data summary.  Texas Agricultural Experiment Station, Blackland Research Center.  Temple, TX.  104 pp. 

 

5.         Maas, S. J. and G. F. Arkin.  1980.  TAMW: A wheat growth and development simulation model.  Research Center Program and Model Documentation No. 80-3.  Texas Agricultural Experiment Station.  College Station, TX.  120 pp.

 

6.         Maas, S. J.  1982.  Forecasting yields using weather-related indices.  SRS Staff Report No. AGES820317.  USDA/ARS.  Washington, DC.  32 pp.

 

7.         Dunlap, J. R. and S. J. Maas.  1991.  Reproductive patterns of three melon cultivars in response to temperature accumulation.  Report No. 14, Cucurbit Genetics Cooperative.  College Park, MD.  pp. 61-62.

 

8.         Maas, S. J.  1998.  Remote Sensing: Value in a Bird’s-eye View.  A. F. Wrona (ed.).  Cotton Physiology Today, National Cotton Council.  Vol. 9., No. 2, pp. 13-15.

 

9.         Maas, S. J.  1998.  High and Dry.  J. Knight, New Scientist, Reed Business Information, Ltd.  Vol. 160, No. 2155, p. 15.

 

10.       Maas, S. J.  1998.  Remote Sensing Shows Dry Spots.  D. Bryant, California-Arizona Farm Press, Primedia Intertec.  Vol. 20, No. 22, pp. 1-8.

 

11.       Maas, S. J.  1999.  Determining Irrigation Needs from Thermal Imagery.  Jim Urbanek, Cotton Farming, Vance Publishing.

 

12.       Maas, S. J., K. B. Stelljes, D. Comis, and M. Wood.  1999.  From Sky to Earth… Researchers Capture “Ground Truth”.  Agricultural Research, USDA-ARS.  pp. 4-8.

 

13.       Fitzgerald, G. J., S. J. Maas, and W. R. DeTar.  2001.  Spying on spider mites from on high.  California-Arizona-Texas Cotton Magazine, Fall 2001.  p. 13, 15.

 

14.       Contributed to the article, “Distance Monitoring,” by Stephanie Fehr, published in CAAR Communicator, Dec. 2001, Vol. 22, No. 5, p. 28.

           

15.       Contributed to the article, “Spectral Imaging Finds a Place on the Farm,” by Brent D. Johnson, published in Photonics, Jan. 2002, p. 164-168.

 

Abstracts and Proceedings:   

1.         Maas, S. J. and P. R. Harrison.  1977.  Dispersion over water: A case study of a nonbuoyant plume in the Santa Barbara Channel, California.  Preprint Volume, Proc. Joint Conf. on Applications of Air Pollution Meterol.  Salt Lake City, UT.  pp. 12-15.

 

2.         Monk, R. L., G. F. Arkin, and S. J. Maas.  1978.  Environmental effects on the phenological and morphological development of wheat.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 12.

 

3.         Maas, S. J., G. F. Arkin, J. E. Bremer, and M. J. McFarland.  1979.  Sorghum Advisory Pilot Project: Application of operational weather forecasts to predicting management-oriented crop status.  Preprint Volume, Proc. 14th Conf. on Agric. and Forest Meterol.  Minneapolis, MN.  pp. 7-10.

 

4.         Russell, E. M. and S. J. Maas.  1981.  A developmental rate approach to phenological modeling.  Proc. Workshop on Crop Simulation.  Gainesville, FL.  pg. 27.

 

5.         Maas, S. J. and J. R. Dunlap.  1985.  Contributions of carotenoids and chlorophyll to spectral leaf reflectance.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p.13.

 

6.         Wiegand, C. L., S. J. Maas, and C. R. Perry.  1985.  A three parameter nonlinear expression of IPAR and APAR.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 16.

 

7.         Maas, S. J.  1986.  Improving model estimates of crop yield using Landsat vegetation index data.  Agronomy Abstracts,  Amer. Soc. Agronomy.  pp. 16-17.

 

8.         Maas, S. J., A. J. Richardson, C. L. Wiegand, and P. R. Nixon.  1986.  Use of plant, spectral, and weather data in modeling corn growth.  Proc. 19th Int. Symp. Remote Sensing of Environ.  Ann Arbor, MI.  pp. 167-186.

 

9.         Wiegand, C. L., A. J. Richardson, and S. J. Maas.  1986.  Spectral components analysis (SCA) results for wheat, cotton, and corn.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 21.

 

10.       Wiegand, C. L. and S. J. Maas.  1986.  Linkages between plant process crop models and remote observations.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 21.

 

11.       Maas, S. J.  1987.  Growth model for Gramineous crops utilizing remotely sensed data.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 15.

 

12.       Maas, S. J.  1988.  Using field observations to improve growth model performance.  Proc. Workshop on Crop Simulation.  Gainesville, FL.  p. 31.

 

13.       Maas, S. J., R. D. Jackson, S., B. Idson, P. J. Pinter, Jr., and R. J. Reginato.  1988.  Crop simulation model guided by remotely sensed LAI and CWSI data.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 22.

 

14.       Maas, S. J., R. D. Jackson, S. B. Idso, P. J. Pinter, Jr., and R. J. Reginato.  1989.  Incorporation of remotely sensed indicators of water stress in a crop simulation model.  Preprint Volume, Proc. 19th Conf. Agric. and Forest Meterol.  Charleston, SC.  pp. 228-231.

 

15.       Dunlap, J. R. and S. J. Maas.  1990.  Model for predicting muskmelon harvest dates in operational production systems.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 16.

 

16.       Maas, S. J.  1990.  Combined model of plant canopy growth and reflectance for cotton.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 18.

 

17.       Maas, S. J., R. Delecolle, M. Guerif, and F. Baret.  1990.  Incorporation of remotely sensed information into agricultural crop growth simulation models.  Proc. Beltsville Symp. XV, Remote Sensing for Agriculture.  Greenbelt, MD.  p. 40.

 

18.       Delecolle, R., F. Baret, M. Guerif, and S. J. Maas.  1991.  L’utilisation conjointe de la teledetection et des modeles d’estimation des productions agricoles: Tendences actuelles.  Proc. Fifth Int. Colloq. on Physical Measurements and Signatures in Remote Sensing.  Courchevil, France.  pp. 125-130.

 

19.       Maas, S. J.  1991.  GRAMI, GLYCI, and GOSSY: A family of crop models that utilize within-season calibration.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 21.

 

20.       Maas, S. J.  1991.  Validation of GRAMI wheat yield estimates for North Dakota using Landsat MSS data.  Preprint Volume, Proc. 20th Conf. on Agric. and Forest Meteorol.  Salt Lake City, UT.  pp. 23-26.

 

21.       Maas, S. J.  1992.  Implementation of within-season calibration in crop growth simulation models.  Proc. Workshop on Crop Simulation.  Corpus Christi, TX.  p. 30.

 

22.       Maas, S. J.  1992.  Leaf lifespan as a component of plant growth models.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 19.

 

23.       Moran, M. S., S. J. Maas, and R. D. Jackson.  1992.  Combining remote sensing and modeling for regional resource monitoring, Part I: Remote evaluation of surface evaporation and biomass production.  Proc. ASPRS/ACSM Conf.  Washington, DC.  Vol. 5, pp. 215-224.

 

24.       Maas, S. J., Moran, M. S., and R. D. Jackson.  1992.  Combining remote sensing and modeling for regional resource monitoring, Part II: A simple model for estimating surface evaporation and biomass production.  Proc. ASPRS/ACSM Conf.  Washington, DC.  Vol. 5, pp. 225-234.

 

25.       Doraiswamy, P. C. and S. J. Maas.  1993.  Estimation of county corn yields using a crop growth model and AVHRR data.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 11.

 

26.       Hart, G. F., S. J. Maas, and E. M. Perry.  1993.  Personal computer based image processing—A capability update.  Proc. ASPRS/ACSM Annual Conf.  New Orleans, LA.  Vol. 2, pp. 118-124.

 

27.       Maas, S. J., G. L. Anderson, and J. D. Hansen.  1993.  Implementing a remote sensing/agmet model in A GIS.  Proc. Workshop on Remote Sensing of Soils and Vegetation.  Phoenix, AZ.  p. 47.

 

28.       Maas, S. J., M. S. Moran, M. A. Weltz, and J. H. Blanford.  1993.  Model for simulating surface evaporation and biomass production utilizing routine meteorological and remote sensing data.  Proc. ASPRS/ACSM Annual Conf.  New Orleans, LA.  Vol. 2, pp. 212-221.

 

29.       Maas, S. J. and P. J. Pinter, Jr.  1994.  Model simulation of cotton growth in the 1989-91 FACE Experiment.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 19.

 

30.       Maas, S. J. and D. J. Munier.  1995.  Relationships between crop yield, light absorption, and canopy reflectance for cotton in the San Joaquin Valley of California.  Agronomy Abstracts,  Amer. Soc. Agronomy.  P. 19.

 

31.       Maas, S. J. and P. C. Doraiswamy.  1996.  Integration of satellite data and model simulations in a GIS for monitoring regional evaporation and biomass production.  Proc. 3rd International Conference on Integrating GIS and Environmental Modeling.  Santa Fe, NM.  (CD-ROM)

 

32.       Maas, S.  J.  1996.  Cotton canopy structure, light absorption, and growth in the San Joaquin Valley of California.  Proc. Beltwide Cotton Conf.  Nashville, TN.  pp. 1235-1237.

 

33.       Maas, S. J., W. R. DeTar, J. R. McLaughlin, R. J. Thullen, and J. H. Ayers.  1996.  Water relations of furrow and drip irrigation cotton.  Proc. Int. Conf. on ET and Irrigation Scheduling.  San Antonio, TX.  pp. 838-844.

 

34.       Moran, M. S., S. J. Maas, T. R. Clarke, P. J. Pinter, Jr., J. Qi, T. A. Mitchell, B. A. Kimball, and C. M. U. Neale.  1996.  Modeling/remote sensing approach for irrigation scheduling.  Proc. Int. Conf. on ET and Irrigation Scheduling.  San Antonio, TX.  pp. 231-238.

 

35.       DeTar, W. R., S. J. Maas, and J. R. McLaughlin.  1997.  The effect of degree days on the crop coefficient and water use by cotton.  Proc. Beltwide Cotton Conf.  New Orleans, LA.  pp. 370-376.

 

36.       Maas, S. J.  1997.  Competition among equally-spaced cotton plants grown at four plant population densities.  Proc. Beltwide Cotton Conf.  New Orleans, LA.  pp. 1485-1487.

 

37.       DeTar, W. R., S. J. Maas, and J. R. McLaughlin.  1998.  Cotton irrigation using subsurface drip: Growth, cutout and yield depend on amount of water applied.  Proc. Beltwide Cotton Conf.  San Diego, CA.  pp. 417-421.

 

38.       Maas, S. J.  1998.  Estimating cotton canopy ground cover using multispectral remote sensing imagery.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 16-17.

 

39.       Maas, S. J.  1998.  Extraction of crop parameters from remote sensing imagery and their use in plant growth simulation models.  Proc. Workshop on Crop Simulation.  Beltsville, MD.  p. 2.

 

40.       Maas, S. J.  1998.  Modeling plant canopy reflectance using commercial ray tracing software.  Proc. Beltwide Cotton Conf.  San Diego, CA.  pp. 1495-1499.

 

41.       Maas, S. J.  1998.  Remote sensing resources for agriculture in the next decade.  Proc. Beltwide Cotton Conf.  San Diego, CA.  pp. 36-38.

 

42.       DeTar, W. R., S. J. Maas, and G. J. Fitzgerald.  1999.  Drip vs. furrow irrigation of cotton on sandy soil with ¼ mile runs – Includes: Yield monitoring, remote sensing, and electronic soil survey.  Proc. Beltwide Cotton Conf.  Orlando, FL.  Vol. 1, pp. 375-381.

 

43.       Fitzgerald, G. J., S. R. Kaffka, D. L. Corwin, S. M. Lesch, and S. J. Maas.  1999.  Detection of soil salinity effects on sugar beets using multispectral remote sensing.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 17.

 

44.       Fitzgerald, G. J., S. J. Maas, and W. R. DeTar.  1999.  Detection of spider mites in cotton using multispectral remote sensing.  Proc. 17th Biennial Workshop on Color Aerial Photog. and Videography in Resource Management.  Reno, NV.  pp. 77-82.

 

45.       Fitzgerald, G. J., S. J. Maas, and W. R. DeTar.  1999.  Early detection of spider mite in cotton using multispectral remote sensing.  Proc. Beltwide Cotton Conf.  Orlando, FL.  Vol. 2, pp. 1022-1023.

 

46.       Maas, S. J.  1999.  Determining canopy temperature and water stress using multispectral remote sensing imagery.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 19.

 

47.       Maas, S. J., G. J. Fitzgerald, and W. R. DeTar.  1999.  Comparison among different types of spatially distributed field information of possible use in precision farming.  Proc. Beltwide Cotton Conf.  Orlando, FL.  Vol. 1, pp. 19-20.

 

48.       Maas, S. J., G. J. Fitzgerald, and W. R. DeTar.  1999.  Spatial and temporal correlations between crop yield and remotely sensed plant canopy characteristics.  Proc. 17th Biennial Workshop on Color Aerial Photog. and Videography in Resource Management.  Reno, NV.  pp. 106-110.

 

49.       Maas, S. J., G. J. Fitzgerald, W. R. DeTar, and P. J. Pinter, Jr.  1999.  Detection of water stress in cotton using multispectral remote sensing.  Proc. Beltwide Cotton Conf.  Orlando, FL.  Vol. 1, pp. 584-585.

 

50.       Sassenrath-Cole, G. F., C. Bednarz, W. R. DeTar, S. J. Maas, J. Lewis, L. Pachepsky, D. Wanjura, and J. Willers.  1999.  Validation of the cotton model across the U.S. Cotton Belt.  Proc. Beltwide Cotton Conf.  Orlando, FL.  Vol. 2, p. 1383.

 

51.       Gat, N., H. Erives, S. J. Maas, and G. J. Fitzgerald.  1999.  Application of low altitude AVIRIS imagery of agricultural fields in the San Joaquin Valley, California, to precision farming.  Proc., Airborne Geoscience Workshop.  Pasadena, CA.  (CD-ROM)

 

52.       Maas, S. J.  2000.  Mixture modeling and plant canopy simulation.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p. 15.

 

53.       Maas, S. J. and G. J. Fitzgerald.  2000.  Evaluation of an inexpensive imaging system for agricultural remote sensing applications.  Agronomy Abstracts,  Amer. Soc. Agronomy.  p.16.

 

54.       DeTar, W. R., S. J. Maas, and G. J. Fitzgerald.  2000.  Crop coefficients for irrigation of cotton.  Proc.,  Beltwide Cotton Conf.  San Antonio, TX.  Vol. 1, pp. 439-442.

 

55.       Fitzgerald, G. J., S. J. Maas, and W. R. DeTar.  2000.  Assessing spider mite damage in cotton using multispectral remote sensing.  Proc. Beltwide Cotton Conf.  San Antonio, TX.  Vol. 2, pp. 1342-1345.

 

56.       Maas, S.  J., G. J. Fitzgerald, and W. R. DeTar.  2000.  Determining cotton leaf canopy temperature using multispectral remote sensing.  Proc. Beltwide Cotton Conf.  San Antonio, TX.  Vol. 1, pp. 623-626.

 

57.       Maas, S. J.  2000.  3-Dimensional simulation of cotton canopy structure and reflectance: An interface between remote sensing and crop growth models.  Proc. Biological Systems Simulation Group Workshop.  Temple, TX.  pp. 1-2.

 

58.       Fitzgerald, G. J., S. J. Maas, and W. R. DeTar.  2000.  Multispectral multitemporal remote sensing for spider mite detection in cotton.  Proc. 5th International Conference on Precision Agriculture.  Bloomington, MN.  (CD-ROM) 

 

59.       Maas, S. J.  Use of yield prediction models in the YieldTracker project.  2001.  Abstracts,  Annual Meetings, Amer. Soc. Agronomy.  Charlotte, NC.  (CD-ROM)

 

60.       Maas, S. J., R. J. Lascano, and D. E. Cooke.  2002.  YieldTracker: A Yield Mapping and Prediction Information Delivery System.  Proc., IFAFS Workshop.  (CD-ROM)

 

61.       Wanjura, D. F., S. J. Maas, and D. R. Upchurch.  2002.  Thermal imaging of cotton canopies.  Proc., Beltwide Cotton Conference.  (CD-ROM)

 

62.       Bronson, K. F., S. J. Officer, R. J. Lascano, S. Maas, J. Booker, and J. D. Booker.  2002.  Relationship between soil properties and electrical conductivity in the Southerm High Plains.  Abstracts,  Annual Meetings, Amer. Soc. Agronomy.  Indianapolis, IN.   (CD-ROM)

 

63.       Maas, S., J. Brightbill, R. Lascano, D. Krieg, K. Bronson, A. Brashears, E. Hequet, E. Segarra, M. Parajulee, and D. Wanjura.  2003.  Precision Agriculture in the Texas High Plains.  Proc., 6th Annual National Conservation Tillage Conference.  Houston, TX.  pp. 58-61.

 

64.       Maas, S. J., E. Segarra, S. A. Mauget, and R. J. Lascano.  2003.  Can Seasonal Rainfall Forecasts Be Used To Guide Dryland Cotton Management?  Proc.,  Beltwide Cotton Conference.  Nashville, TN.  pp. 545-547.

 

65.       Maas, S. J., and J. Brightbill.  2003.  Relation Between Yield Maps and Mid-season Remote Sensing Imagery.  Proc., Beltwide Cotton Conference.   Nashville, TN.  pp.1732-1734

 

66.       Duesterhaus, J., and S. Maas.  2003. Microclimate of Dryland Cotton Production Systems.  Proc., Beltwide Cotton Conference.   Nashville, TN.  p.1939.

 

67.       Maas, S. J., R. J. Lascano, and D. E. Cooke.  2003.  Web-based Yield Prediction Information Delivery System.  Proc., Integrated Biological Systems Conf., San Antonio, TX.  (http://beaumont.tamu.edu/conference/presentation.asp)

 

68.       Maas, S. , and J. Ko.  Canopy architecture model for cotton.  Proc., 2004 Beltwide Cotton Conference.  San Antonio, TX.  p. 2139-2142.  (T-4-548)

 

69.       Guo, W., E. Hequet, S. Maas, and J. Brightbill.  Variability of cotton fiber quality in West Texas.  Proc., 2004 Beltwide Cotton Conference.  San Antonio, TX.  p. 2318-2325.  (T-4-550)

 

70.       Maas, S., J. Brightbill, and J. Hooton.  Remote sensing for precision agriculture in the Texas High Plains.  Proc., 2004 Beltwide Cotton Conference, Decision Aids Workshop.  San Antonio, TX.  p. 184-187.  (Invited Paper, T-4-549)

 

71.       Wanjura, D., D. Upchurch, and S. Maas.  Spectral Reflectance Estimates of Cotton Biomass and Yield.  Proc., 2004 Beltwide Cotton Conference.  San Antonio, TX.  p. 838-851. 

 

72.       Lascano, R., J. Booker, D. Upchurch, V. Acosta-Martinez, B. McMichael, and S. Maas.  Spatial Variability of Enzyme Activities, Chemical Properties, and Plant Characteristics in a Semiarid Soil Under Dryland Conditions.  Proc., 2004 Beltwide Cotton Conference.  San Antonio, TX.  p. 2662-2668. 

 

73.       Maas, S., R. Lascano, D. Cooke, C. Richardson, D. Upchurch, D. Wanjura, D. Krieg, S. Mengel, J. Ko, W. Payne, C. Rush,  J. Brightbill, K. Bronson, W. Guo, and S. Rajapakse  2004.  Within-season estimation of evapotrasnspiration and soil moisture in the High Plains using YieldTracker.  Proc., 2004 High Plains Groundwater Resources Conference.  Lubbock, TX.  pp. 219-226.

 

74.       Maas, S., J. Brightbill, R. Lascano, D. Krieg, K. Bronson, A. Brashears, E. Hequet, E. Segarra, M. Parajulee, and D. Wanjura.  2005.  Update on  Precision Agriculture in the Texas High Plains.  Proc., 8th Annual National Conservation Tillage Conference.  Houston, TX.   pp.  49-51.

 

75.       Maas, S., J.  2005.  An overview of interfacing models with remote sensing.  Proc., 35th Biological Systems Simulation Conference.  Phoenix, AZ.  p. 31-33.  (Invited Paper)

 

76.       Maas, S., S. Rajapakse, R. Lascano, W. Guo, J. Booker, and J. Ko.  2005.  Relation between RADARSAT imagery and cotton field characterisics.  Proc., Annual Beltwide Cotton Conference.  New Orleans, LA. 

 

77.       Guo, W., Maas, S., R. Lascano, and J. Brightbill.  2005.  Mapping spatial and temporal variability in cotton fields in West Texas.  Proc., Annual Beltwide Cotton Conference.  New Orleans, LA.  p. 2067-2073.

 

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