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Dissertations / Theses on the topic 'Agriculture – Arizona'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Chen, Changping 1958. "Production variability for major Arizona field crops." Thesis, The University of Arizona, 1991. http://hdl.handle.net/10150/291617.

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Previous variability studies in both U.S. and worldwide agriculture have indicated that crop production has been accompanied by increasing variation. In this research, four different variability indexes were estimated in order to evaluate the production variability associated with the major Arizona field crops. Results show that major Arizona field crops, which are all irrigated, did not have a uniform production variability over the last 24 years and the variability of these crops did not generally increase between the periods of 1967-1978 and 1979-1990. Although biological factors (e.g. pests, weather) influenced variability, the variation of crop production measures over time also was related to market factors (e.g. prices), government farm programs, producers' crop management experience, and the geographical area selected for the analysis. Crops covered by government farm programs usually varied more in harvested acreage and fluctuated less in yield per acre than vegetable crops.

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2

Budhabhatti, Jennifer. "Integrating agriculture and aquaculture in Arizona." Diss., The University of Arizona, 1991. http://hdl.handle.net/10150/185676.

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This research project was designed to test the feasibility of growing catfish (Ictalurus punctatus) in cages at two densities in three types of irrigation waters in Arizona in 1989 and 1990. The types of waters studied were a pre-irrigation flowing water ditch, an irrigation return water sump and a pre-irrigation stationary water reservoir. Cages were designed for each type of water. The duration of the experiment was 76 days in 1989 and 117 days in 1990. Growth of fish was poor at both densities in pre-irrigation flowing water in 1989. Poor growth was probably due to the velocity of water and size variability of fish at stocking (coefficient of variability = 48%). Hand grading and the addition of baffles to cages resulted in increased growth and decreased size variability (25%) in 1990. Poor growth and low food conversion (5.2) were seen at both densities in irrigation return waters in 1989. Reduced growth and poor feed conversion were due in part, to wild fish bumping cages until food was lost. High variability in final weight (48.9%) was due to stocking of ungraded fish. In 1990, wild fish were removed from the pond and catfish were handgraded at stocking. These procedures resulted in higher final weights (660 g), lower conversion ratios (1.3) and lower size variability (31%). In 1989, poor growth and high size variation (55.4%) also occurred at both densities in pre-irrigation standing water. In 1990, grading fish at stocking and lowering stocking densities resulted in increased growth (570.6 g) and a lower coefficient of variability (28.7%). However, the food conversion ratio (2.6) was still high, due to food loss from cages, a disease outbreak and the associated mortality. Growing fish in all three types of irrigation waters appears to be biologically feasible. Fish in irrigation return flow waters had better growth rates than fish in flowing pre-irrigation water or in stationary pre-irrigation water. However, questions concerning the possible addition of contaminants to the system from agriculture effluent and the economics of integrating aquaculture into agriculture requires further study.

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3

McCoy, Jan. "Revitalizing Rural Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1989. http://hdl.handle.net/10150/295628.

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4

McGinley, Susan. "Arizona Veterinary Diagnostic Laboratory: Assisting Arizona Veterinarians and the Public." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 1998. http://hdl.handle.net/10150/622301.

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5

Bush, David B., and William Edwin Martin. "Potential Costs and Benefits to Arizona Agriculture of the Central Arizona Project." College of Agriculture, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/310777.

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6

Knight, Susan M. "Selling Apples from Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1991. http://hdl.handle.net/10150/295693.

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7

Littlefield, Joanne. "Arizona Horse "Cents": The economic impact of the industry to Arizona." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2007. http://hdl.handle.net/10150/622105.

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8

Renfrow, Crystal. "Phytophthora in Arizona Citrus." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 1995. http://hdl.handle.net/10150/622384.

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9

McCormick, Suzanne, and Lorraine Kingdon. "Wilderness Law and Arizona Ranchers." College of Agriculture, University of Arizona (Tucson, AZ), 1992. http://hdl.handle.net/10150/295708.

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10

Oliveira, Aureo Silva 1965. "Determination of head lettuce crop coefficient and water use in central Arizona." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/282779.

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The assessment of crop evapotranspiration (ET) has received intensive research due to its critical role in irrigation management and water conservation studies. Because weather conditions largely determine ET, various methods based on meteorological factors have been developed to estimate ET rates. In order to accommodate the concept of reference crop ET (ETo), evaluation of weather data quality has been addressed. In this research, 9 year (1989-1997) weather data from the AZMET weather station at the Maricopa Agricultural Center were used to compare daily and 10 day average ETo estimated by the Hargreaves (HARG), FAO 24 Penman (FAOP), and FAO Penman-Monteith (FAOPM) methods. Before ET calculation, the weather data were evaluated for the influence of aridity at the weather station site and sensor calibration/malfunctioning problems. Corrections were made on temperature and solar radiation data. Reference ET as reported by the AZMET was also considered for comparison purposes. In general, the weather data correction decreased ETo estimates 18.3%, on average. The highest reduction (23.5%) was obtained with the FAOPM method. When this method was used as the standard for ETo estimate comparison, the FAOP method corrected for site aridity ranked first as predictor of ETo despite its tendency for overestimation. At the Maricopa Agricultural Center, a two year field research (Fall-Winter of 1996/97 and 1997/98) was carried out to derive head lettuce (Lactuca sativa L.) crop coefficient (Kc) and to investigate the effects of ETo method in the shape and values of the crop coefficient curve. For the periods of low crop ET, the 2 year (Kc) from the HARG, FAOP, and FAOPM methods did not differ significantly. However, in the peak demand period, crop coefficients derived from the three methods peaked at different values. The predicted peak (Kc) was 0.87, 0.72, and 0.82 for the HARG, FAOP, and FAOPM methods, respectively. These results reflect the tendency of ETo underestimation by the HARG method and overestimation by the FAOP method under and conditions. Crop coefficients derived in the 96/97 growing season were then used to investigate the effects of (Kc) and ETo mismatching in the water use and yield of lettuce during the 97/98 growing season. To reach such objectives, an experiment design in Latin square with four replications and four treatments was carried out. Differences in seasonal water depth were as high as 33 mm among treatments. The analysis of variance revealed that the treatments did not induce lettuce marketable yield statistically different at the 5% significance level.

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11

Jones, Jennifer S., John C. Palumbo, and Peter C. Ellsworth. "Arizona Crop Information Site." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2004. http://hdl.handle.net/10150/215239.

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The Arizona Crop Information Site (ACIS) http://cals.arizona.edu/crops was launched by the University of Arizona in 2001. This site provides a one-stop resource for those seeking information on Arizona crop protection and production information. The site is the result of input and cooperation across Arizona’s agricultural community. The amount of information on the site continues to grow as does the site’s importance, usefulness and number of visitors.

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12

Renfrow, Crystal. "Shifty Trees in Southeastern Arizona." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 1995. http://hdl.handle.net/10150/622371.

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13

Renfrow, Crystal. "Tracking Goshawks in Northern Arizona." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 1995. http://hdl.handle.net/10150/622372.

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14

Kingdon, Lorraine B. "Havesting Snow In Water Shy Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1987. http://hdl.handle.net/10150/295539.

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15

Littlefield, Joanne. "Walk Across Arizona: Community Fitness Program." College of Agriculture, University of Arizona (Tucson, AZ), 2004. http://hdl.handle.net/10150/295864.

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16

McGinley, Susan. "New Tomato Virus Identified in Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 2007. http://hdl.handle.net/10150/295900.

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17

Kingdon, Lorraine B. "Organic Market Soft for Arizona Growers." College of Agriculture, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/295665.

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18

Rudstrom, Margaretha Veronica 1962. "Optimal timing and quantity of sale of Arizona apples." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/291405.

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Arizona apple producers compete with Washington for fresh apple markets. As Arizona's apple production increases, its market share should also increase. Using quadratic programming to determine the spatial equilibrium between the wholesale markets of Los Angeles and Denver, the timing and quantity of apple sales from Arizona to these two wholesale markets are determined for current and potential fresh apple production in Arizona. The quadratic programming model is used to determine the feasibility of controlled atmosphere storage for Arizona. The quantity of apples sold monthly to Los Angeles and Denver wholesale markets are determined given restrictions on the percentage of the wholesale markets that Arizona apple producers could supply. Revenue from controlled atmosphere storage exceeds the variable costs associated with storage, marketing, and storage of apples.

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19

Kingdon, Lorraine B. "Women: The Driving Force in African Agriculture." College of Agriculture, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/295699.

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20

Suarez-Rey, Elisa Maria. "Subsurface drip irrigation of bermudagrass turf in Arizona: Benefits and limitations." Diss., The University of Arizona, 2002. http://hdl.handle.net/10150/280210.

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Subsurface drip irrigation was compared to sprinkler irrigation on bermudagrass turf during three consecutive years using tertiary treated wastewater. Irrigation amount required by each treatment, visual appearance of the grass, shoot biomass production, and soil salinity were measured, and potential management problems were identified. The amount of irrigation water applied via subsurface irrigation was similar or higher than that applied via sprinkler irrigation for a turf of similar quality. Shoot biomass production did not differ between both irrigation methods when similar amounts of water were applied. Soil salinity, measured as electrical conductivity, was monitored at the beginning and end of each season. The changes in electrical conductivity at the end of every irrigation season did not negatively affect the appearance of the turf in any of the years. Emitter clogging by root intrusion was identified as a potential problem in the subsurface drip irrigation system. A series of greenhouse experiments were conducted to evaluate the effect of different herbicides and acids at several concentrations on root intrusion into subsurface drip emitters. The first greenhouse experiment was a study intended to identify chemical concentrations that could inhibit bermudagrass root growth in soil without negatively affecting the visual appearance of the grass. As a result, two herbicides, trifluralin and thiazopyr, and one acid, phosphoric acid, were selected for a second greenhouse experiment. The second greenhouse experiment focused on the effects of the two herbicides and the acid on root intrusion into subsurface drip emitters. Only the emitters treated with thiazopyr at the highest dose were completely clean, root-free emitters.

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21

Taylor, Kathryn C. "Nutrition Survey in Arizona Citrus." College of Agriculture, University of Arizona (Tucson, AZ), 1996. http://hdl.handle.net/10150/220554.

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22

Sherif, Souad Mohammed. "The economic feasibility of introducing aquaculture into traditional farming systems in Arizona." Diss., The University of Arizona, 1998. http://hdl.handle.net/10150/288781.

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The primary objective of this study was to evaluate the economic feasibility of introducing fish culture into irrigated cotton production on farms in central Arizona. The representative farm adopted in this study is a cotton farm described in Arizona Field Crop Budgets, 1994-95. The only adjustment necessary for the farmer to make is to keep water in the ditches at all times. Water as a production variable for fish production was thus calculated only for the additional quantity required. Analysis of these production systems was accomplished by budgeting procedures as well as statistical analysis. The economic-engineering (synthetic firm technique) was employed to develop the input-output coefficients necessary for analysis. Five fish densities and eight ditch capacities were tested. The production function was estimated using input and yield data. Three functional forms (linear, quadratic and Cobb-Douglas) were examined to determine how well they estimated the production system. Using budget analysis, a fish stocking density of six fish per cubic meter and a ditch capacity of 2,925 m3 appear to provide the optimal production scenario, if the percentage of fish reaching harvestable size is improved from 66 percent to at least 80 percent. This density has been proven to require minimum production costs and to provide the most efficient use of resources. However, production functions estimated in this study indicate that profits can be increased through additional use of feed. At any ditch capacity, a density of six fish per cubic meter, provides the optimal economic results, MVP = PX2 Finally, the implication of the findings of this study are that raising tilapia in irrigation ditch systems on cotton farms in central Arizona is feasible at a stocking density of six fish per cubic meter. Studies to improve the percentage of fish reaching marketable size at this density is very critical. Increasing the initial size of the fingerlings could be a consideration in improving the percentage of fish reaching marketable size and eventually increasing optimum economic returns.

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23

Ellsworth, P. C., J. P. Diehl, J. C. Silvertooth, P. W. Brown, T. F. Watson, L. R. Hood, S. H. Husman, et al. "Sweetpotato Whitefly in Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1993. http://hdl.handle.net/10150/209578.

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Whitefly management has become a complex objective in Arizona in the past several years. A tremendous amount of research and extension effort is now focused on this significant pest. The purpose of this paper is to describe the position and guidelines of the University of Arizona's Cotton Team regarding the Sweetpotato Whitefly. The information presented is credited to no single source, but represents a collection of information from numerous research and extension scientists within and outside of the U of A system and careful analyses of the presently available data on whitefly management dynamics. Where possible, only the results of research are reported and suggestions based only on experience or speculation are duly noted.

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24

Weinert, Tom L. "Optimizing nitrogen management for microsprinkler irrigated citrus in central Arizona." Diss., The University of Arizona, 2000. http://hdl.handle.net/10150/284169.

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A High N fertilizers citrus rates may contribute to a rise in the appearance of groundwater NO₃ around groves in central Arizona. Nitrogen fertilizer recommendations need to be reevaluated for citrus due to recent changes in fertilizers, irrigation technology, and increasing groundwater NO₃. Studies were initiated to optimize fertilizer N management for microsprinkler-irrigated citrus. Navel oranges were planted in Jan. 1997 with varying N rates and frequency of liquid urea NH₄-NO₃ or granular controlled-release fertilizers (CRFs) in order to determine tree response, N partitioning, N balance, and residual soil N. Trees grew slowly in 1997 with no more than 6% of the fertilizer N taken up by trees, while < 94% of fertilizer N remained in the top 0.9 m of soil. Leaf N was higher in fertilized plots than in controls as trees grew rapidly in 1998 with < 25% of the fertilizer N taken up by the trees. The soil contained low NO₃ concentrations, suggesting most of the fertilizer N was leached. Nitrogen is not needed during the first season after planting and rates of 68 to 136 g N tree⁻¹ applied in monthly intervals during the second season maintain adequate tree growth and N reserves. Application of CRFs resulted in little tree response during the two year study. Soil inorganic N was highest in the surface 0.6 m in 1997. In 1998, ammonium sulfate treatments resulted in higher NO₃ leaching than plots that received CRFs. Eight-year old 'Redblush' grapefruit trees were treated with two N rates and three fertigation frequencies in a factorial arrangement. There no differences in trunk diameter, or fruit quality on trees between 1996 and 1998. Leaf N content was > 18 mg kg⁻¹ in all plots in 1996. Leaf N declined in Aug. 1997 and control plots had lower leaf N than the other treatments. Yields tended to be the greatest at high N rates with monthly fertigation. Soil N levels were proportional to fertilizer N inputs. In 1998, the high N treatment at weekly and monthly frequencies increased leaf N compared to the other treatments. Results suggest that N rates of 272 to 408 g tree⁻¹ year⁻¹ at weekly or monthly frequencies may be optimal for desert-grown mature grapefruit.

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25

Littlefield, Joanne. "Direct Farm Marketing and Agri-Tourism in Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 2004. http://hdl.handle.net/10150/295857.

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26

Albert, Steven Keith 1960. "Desert mule deer and forage resources in southwest Arizona." Thesis, The University of Arizona, 1992. http://hdl.handle.net/10150/278157.

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I measured digestible protein consumed by 4 (2 M, 2 F) captive desert mule deer (Odocoileus hemionus crooki). Deer were fed native forage collected from the Belmont Mountains, Arizona. Intake of forage differed significantly (P < 0.05) between sexes in every season. Intake of digestible protein for both sexes was highest in fall, lowest in the spring and summer for males and females, respectively. Significant (P < 0.05) differences of forage biomass were recorded among all vegetation associations and seasons in the Belmont Mountains. The most forage biomass was available in winter, the least in spring. Desert mule deer in the Belmont Mountains are close to the nutritional carrying capacity of the range. Other efforts to increase the deer population may not be effective if the forage base is not increased.

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27

Andrade-Sanchez, Pedro, and John T. Heun. "Things to Know About Applying Precision Agriculture Technologies in Arizona." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2010. http://hdl.handle.net/10150/146428.

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7 pp.
In this publication, we will make the case of what Precision Agriculture (PA) technologies can do to enhance the productivity of farming systems, with particular attention to the case of irrigated agriculture in the semi-arid Arizona. This guide is intended to aid growers to select the right technology when considering the need to acquire new, or upgrade existing equipment.

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28

Oebker, Norm, Ed Ryder, Fred Harper, and Marcia White. "Lettuce Tipburn Studies in Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/214492.

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29

Nandasiri, Ratnayake Mudiyanselage 1957. "Institutional constraints affecting county extension agents in Arizona." Thesis, The University of Arizona, 1990. http://hdl.handle.net/10150/277302.

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The purpose of this study was to determine the county extension agents' perceptions of institutional constraints to the performance of their duties within the Arizona Cooperative Extension System. Study population was 66 county extension agents in the state of Arizona. They were surveyed by mailed questionnaire. Study results indicated, on the average, most of the institutional constraints affect slightly on the county extension agents' work performance. Considerable variation observed among respondents in their perceptions of severity of the constraints. Some of the other important findings include; (1) 4-H agents perceived constraints more severe than Agriculture or Home Economic Agents. (2) County agents perceived more constraints in salary and promotion more severe than county directors. (3) County agents with more than 5 years of service perceived more of the constraints in the area of Personnel Evaluation more severe than agents with 5 years or less service.

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30

Haney, Richard A. Jr, Hector J. Gonzalez, and Patricia Paylore. "College of Agriculture: A Century of Discovery." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/558261.

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31

Silvertooth, Jeffrey C. "Review of the 2002 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2003. http://hdl.handle.net/10150/197721.

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32

Tronstad, Russell, Steve Husman, Randy Norton, Eric Norton, Pat Clay, and Mohammed Zerkoune. "Review of the 2004 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2005. http://hdl.handle.net/10150/198157.

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33

Tronstad, Russell, Kurt Nolte, Eric Norton, Randy Norton, and Erin Taylor. "Review of the 2006 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2007. http://hdl.handle.net/10150/198204.

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34

Silvertooth, Jeffrey C. "Review of the 2001 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2002. http://hdl.handle.net/10150/197453.

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35

Tronstad, Russell, Steve Husman, Randy Norton, Eric Norton, Pat Clay, and Mohammed Zerkoune. "Review of the 2003 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2004. http://hdl.handle.net/10150/198123.

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36

Tronstad, Russell, Pat Clay, and Eric Norton. "Review of the 2005 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 2006. http://hdl.handle.net/10150/198189.

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37

Silvertooth, Jeffrey C. "Review of the 1997 Arizona Cotton Season." College of Agriculture, University of Arizona (Tucson, AZ), 1998. http://hdl.handle.net/10150/210333.

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38

Littlefield, Joanne. "Controlled Environment Agriculture: Greenhouses Feature High-Tech Hydroponics." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2001. http://hdl.handle.net/10150/622255.

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39

Oebker, Norm, Fred Harper, Rick Gibson, and Marcia White. "Sweet Corn Cultivar Trials at Maricopa Agricultural Center, 1989." College of Agriculture, University of Arizona (Tucson, AZ), 1990. http://hdl.handle.net/10150/214489.

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40

Kingdon, Lorraine. "Peanuts, Popcorn, and Peppers: Arizona Farmers to Alternative Crops." College of Agriculture, University of Arizona (Tucson, AZ), 1986. http://hdl.handle.net/10150/295522.

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41

Kingdon, Lorraine B. "The Central Arizona Project: Water with a Bitter Twist." College of Agriculture, University of Arizona (Tucson, AZ), 1993. http://hdl.handle.net/10150/295716.

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42

Tickes, Barry R. "Wheat Variety Demonstration, Yuma Valley Agricultural Center." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/200476.

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43

Nischwitz, Claudia. "Factors influencing charcoal rot of melon in Arizona." Thesis, The University of Arizona, 2001. http://hdl.handle.net/10150/291652.

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Studies were initiated to determine if drip irrigation contributes to increased incidence of Charcoal Rot, caused by Macrophomina phaseolina , in melons in Arizona. Soil samples from furrow- and drip- (with and without plastic mulch) irrigated fields were analyzed for soil chemical and physical parameters: pH, moisture, salinity and temperature; and for microbial factors: inoculum density, mycorrhizal infection, nematode abundance, and basal respiration. Results show a significant decrease in pH and increase in temperature in drip versus furrow-irrigated soils. Also, the interaction of pH, salinity, moisture, and irrigation type was significant for inoculum density of M. phaseolina which was up to 150 times higher in drip irrigated fields. In greenhouse trials, disease incidence increased significantly as salinity of irrigation water increased, but was not affected by root-knot nematode. Therefore, soil characteristics of drip-irrigated soils may contribute to a soil environment conducive to an increase in Charcoal Rot in melon.

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44

McGinley, Susan. "Archiving Ecosystems: The University of Arizona Campus Herbarium." College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2005. http://hdl.handle.net/10150/622189.

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45

Brown, P., B. Russell, J. Silvertooth, L. Moore, S. Stedman, G. Thacker, L. Hood, S. Husman, D. Howell, and R. Cluff. "The Arizona Cotton Advisory Program." College of Agriculture, University of Arizona (Tucson, AZ), 1992. http://hdl.handle.net/10150/208639.

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Arizona Cooperative Extension produced and distributed weather -based Planting Date and Cotton Development Advisories for 8 cotton production areas (Marana, Litchfield Pk, Pinal Co., Parker, Safford, Yuma Valley, Dateland and Aguila) in 1991. Planting Date Advisories were distributed from mid - February through the end of April and stressed 1) planting full season cotton varieties according to heat unit accumulations rather than calendar date and 2) the importance of soil temperature to good germination. Cotton Development Advisories were distributed from early May through mid- September and provided growers updates on crop development, insects, weather and agronomy. The Cotton Advisory Program will continue in 1992 with the major change being an expansion in coverage to include Paloma, Queen Ck, and Mohave Valley.

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46

Brown, P., B. Russell, J. Silvertooth, P. Ellsworth, S. Stedman, G. Thacker, L. Hood, S. Husman, R. Cluff, and D. Howell. "The Arizona Cotton Advisory Program." College of Agriculture, University of Arizona (Tucson, AZ), 1993. http://hdl.handle.net/10150/209317.

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Arizona Cooperative Extension generates and distributes weather -based Planting Date and Cotton Development Advisories for 10 cotton production areas (Marana, Litchfield Pk, Pinal Co., Parker, Safford, Yuma Valley, Dateland and Aguila). Planting Date Advisories are distributed from mid - February through the end of April and stress 1) planting all (particularly full season varieties) cotton varieties according to heat unit accumulations rather than calendar date and 2) the importance of soil temperature to good germination. Cotton Development Advisories are distributed from early May through mid -September and provide updates on crop developmen4 insects, weather and agronomy to growers. The Cotton Advisory Program will continue in 1993 and growers may obtain the advisories by mail (far only in Yuma County only) from the local county extension office or by computer from the AZMET computer bulletin board.

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47

Ellsworth, Peter C. "Integrated Lygus Management in Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1998. http://hdl.handle.net/10150/210367.

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Integrated Lygus management depends on the same fundamentals of management for any pest. There needs to be a system of monitoring (sampling), understanding of the density-yield relationship (thresholds) and other insecticide optimization practices (e.g., resistance management), and a plan for reducing the chance of infestation and need for remedial measures (avoidance). While all these guidelines are under current study, current recommendations represent a fundamental base on which to build an integrated Lygus management program that will also manage for susceptibility to our current insecticides. Key to this sustainable susceptibility system is limiting insecticide use to the lowest practical levels. This is best accomplished by careful sampling, careful assessment of thresholds and selection of the right compound for the job, but, most of all, avoidance of the problem from the start. Current recommendations are detailed below in light of the most recent research findings.

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48

Martin, E. C., D. C. Slack, and E. J. Pegelow. "Basal Crop Coefficients for Vegetables in Central Arizona." College of Agriculture, University of Arizona (Tucson, AZ), 1995. http://hdl.handle.net/10150/221461.

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The world supply of quality water for irrigation of crops is being depleted. Growers in the arid and semi-arid regions of the world, where irrigation is a requirement for crop production, are looking for ways to conserve their water use and increase their irrigation efficiency. One tool that has been useful in helping growers reduce their irrigation water inputs is computerized irrigation scheduling programs. This study is part of a joint project between the government of Egypt (National Agricultural Research Project), USA1D and The University of Arizona. Working together, researchers from Egypt and Arizona are developing water management tools that will help both countries better use their scarce water resources in arid environments. The main thrust of this segment of the project is to develop water use data on vegetables grown in both regions. These data will then be used to develop crop coefficient data to be used in AZSCHED, a computerized irrigation scheduling program developed at the University of Arizona. Using a subsurface drip irrigation (SDI) system, carrots, cauliflower, head lettuce, and tomatoes were grown to determine water use patterns and develop basal crop coefficients. Water use data were collected using a neutron moisture gauge and a time domain reflectometer (TDR). Soil water data were collected 1 day following an irrigation and just prior to the next irrigation. Additionally, three different watering regimens were employed using available water content in the rootzone as a trigger to initiate irrigation (20 %, 30% and 40% depletion). The carrots, cauliflower and lettuce were planted in early October, 1993, using a randomized block design. Yield data showed no significant differences between treatments for any of the vegetables. Also, the soil moisture data did not indicate water stress in the treatments. In March of 1994, tomato transplants were planted and the irrigation treatments were altered to 30 %, 40% and 50% depletion, in an attempt to get significant differences between treatments. The results for all four vegetables showed high variability in soil water data between replications, although an initial determination of basal crop coefficients was possible. Additional data will be required to better refine the crop coefficients.

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49

Klaas, Larry. "Looking Ahead: Project Agriculture's Future." College of Agriculture, University of Arizona (Tucson, AZ), 1985. http://hdl.handle.net/10150/295368.

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50

Fox, Lisa Marie 1964. "Nutritional content of forage in Sonoran pronghorn habitat, Arizona." Thesis, The University of Arizona, 1997. http://hdl.handle.net/10150/278586.

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I determined if Sonoran pronghorn (Antilocapra americana sonoriensis) could meet water and mineral requirements through consumption of forage. I sampled vegetation using dry weight rank and comparative yield methods in southwestern Arizona from June 1995 to May 1996 to determine preformed water, nutrient content, mineral content, and vegetation abundance. Water and nutrient content of plants varied between 2 sites and among 5 seasons (P ≤ 0.05). Plants consumed by pronghorn were higher in moisture and nutrients (P ≤ 0.05) than non-forage species. I constructed a model for Sonoran pronghorn diet based on field data. I used the model to describe dietary intake. Water intake predicted by diet models ranged from 1.1 to 6.1 L/animal/day; often exceeding predicted total water requirements (1.8-3.4 L/animal/day). Models predicted that forage provided adequate water for pronghorn during 5 seasons at 1 of 2 study sites and deficiencies for 5 of 11 minerals at both study sites.

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