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Steven C. Adams

Seed vigor has a very subtle effect on the productivity of greenhouses producing vegetable transplants, celery, cauliflower, lettuce, etc. and on todays highly mechanized automatic or semi-automatic transplanting operations. As greenhouse production technology moves from traditional bare root to plug/tray growing systems and as automatic and semi-automatic transplanting operations increase in number, the impact of poor seed vigor is realized.

Measures to mitigate the impact of poor seed vigor in the nursery are: Seed density grading; increased growing cycle in the nursery, hand culling or replanting. Measures to mitigate the impact of poor seed vigor in automatic transplanting operations: increase the number of people following the planter to replace poor vigor plants; use hand fed transplanters.

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Steven C. Wiest

Digitized photographic images of turf plots composed of bermudagrass, buffalo grass, tall fescue, and zoysiagrass were taken at a height of about 150 cm with a 28-mm lens. Fast Fourier transforms of these images were performed, and a radial plot of the power spectrum was obtained from each image. Hurst plots (log frequency vs. log intensity) were used to subtract “background” from the power spectra, so peaks would be more evident. The peak of the power spectrum occurs at the average spacing between leaves (more precisely, between areas of the canopy that reflects a significant amount of light) and defines the characteristic dimension. Zoysiagrass had the lowest characteristic dimension, while tall fescue had the highest. The width of the power spectrum is indicative of the variability of the characteristic dimension within the canopy. The minimum characteristic dimension (occurring at the highest frequency) was less than 1.7 cm, whereas all the other species had about the same minimum characteristic dimension of ≈1.9 cm. The maximum characteristic dimension was greatest for fescue (6.9 cm), followed by buffalo grass (3.8 cm), bermudagrass (3.3 cm), and zoysiagrass (2.8 cm). These results indicate that the characteristic dimension can be a useful tool for discriminating between turfgrass species in digitized images.

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Steven C. Wiest

A system for the digital analysis of photographic prints of turfgrass plots is being developed. The 3-year-old turfgrass plots included Meyer zoysiagrass, Midlawn bermudagrass, Prairie buffalograss and Mustang tall fescue. The plots were photographed by a camera with a small dual bubble level on the camera back and a 28-mm-wide angle lens. Photographs were digitized with flatbed scanners. The images can then be analyzed in a variety of ways. For example, a series of photographs were taken from mid-Sept. through late Oct 1995 and spectral analysis of the resultant digital images were made. The initial RGB (red-greenblue) format of the images was converted to HSI (hue-saturation-intensity) for analysis. The results indicate, obviously, that hue changed from 104 (i.e., green) to 75.7 degrees (i.e., brownish) between the beginning and end of Oct. 1995. Similarly, intensity changed from ≈0.12 to ≈0.16 during the same time period, indicating that the images became darker over time. These phenomena were observed in all four species examined. However, the saturation value evoked a significant species * date interaction. The three warm-season species showed a decrease in saturation, while Mustang had no significant decrease during Oct. Spectral as well as textural analysis are likely the two most useful techniques in the digital analysis of turfgrass plots. Examples of both will be presented.

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V. A. Khan and C. Stevens

Staminate and pistillate flower production and fruiting characteristics of `Crimson Sweet' watermelons were evaluated under VisPore row cover plus clear polyethylene mulch (VCM), VisPore row cover plus black polyethylene mulch (VBM), clear polyethylene mulch (CM), black polyethylene mulch (BM) and bare soil (BS). VCM produced significantly higher numbers of pistillate and staminate flowers than other treatments. All mulched and mulched plus VisPore treatments were significantly different from BS with regards to the 1st nodal position of the staminate and pistillate flowers. Fruit-set among the treatments between 53-55 days after transplanting were: 100%, 75%, 59% and 32% for VCM, VBM, CM and BM, respectively. Average number of fruits per plant were: 4, 3, 3, 3 and 1 for VCM, VBM, CM, BM and BS, respectively.

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Douglas C. Needham and Steven Dobbs

Twenty-three students of HORT 2212: Herbaceous Ornamental Plants divided into five teams, each selecting one of the ground beds at the television studio gardens of Oklahoma Gardening to design with the aid of MacDraw II and Macintosh computers. The team approach promoted cooperative learning, where those who were skilled in design worked cooperatively with those individuals more skilled at developing the theme gardens' cultural pamphlets. This project encouraged individual students to develop various communication skills to support their team's thematic garden-visual, in the form of a CAD plot of the garden design; written, in the form of a garden pamphlet; and telecommunication, in the form of Oklahoma Gardening television segments.

The students and OBGA Ambassadors started the seeds and, then, planted the gardens, resulting in a very practical experience. This design and installation project not only prepared students for the cooperative efforts that they are likely to encounter in the ornamental horticulture and landscape design and maintenance industries, but also imparted pride in their work, which was viewed by over 150,000 television viewers and visitors weekly.

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Steven C. Blank and Raymond Venner

This study develops a method of estimating wind machine effectiveness. The method captures the important variables affecting cost-effectiveness and can be applied at little cost. The present-value method outlined may be applied when evaluating frost protection for other crops and other risk-reducing inputs, such as irrigation equipment. Oranges in California are presented as a case study. The empirical results presented indicate that wind machines are generally not cost-effective for California orange producers. However, when the nonfinancial benefits of yield risk reduction are included, it is possible that wind machines are cost-effective for some growers.

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Steven C Wiest and Edward W. Hellman

Scanning electron micrographs of grape berry surfaces, which resemble mountainscapes, contain a wealth of structural information. A typical statistical characterization of features such as root mean square peak-to-peak spacings, peak density, etc., is readily performed on these images. However, a much richer base of information is accessible by analyzing the images with fractal geometry. Fractal box dimension is a quantitative measure of surface roughness, and varies with the contour at which it is determined in both cultivars `Foch' and `Perlette', suggesting that the surfaces are multifractal structures. Fourier spectral analyses of the surfaces produce a similar conclusion. Thus, the unambiguous quantitative resolution of cultivars on the basis of their wax surface structure looks promising, but requires further work.

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C. Elizabeth Succop and Steven E. Newman

Fresh-market sweet basil (Ocimum basilicum) is in high demand from specialty produce markets and commercial restauranteurs. Many consumers are also demanding produce that has been organically grown. Three hydroponic media systems were evaluated twice over two years, rockwool slabs, perlite frames, and commercial sphagnum peat/perlite/compost medium, where the bag was laid flat on the bench. Plants grown in these systems were fertilized with nutrient solutions derived from either organic or conventional, saltbased fertilizer sources. Few differences in yield were detected between basil plants grown in the commercial medium with either fertilizer source. Total yield from plants grown in perlite with the organic fertilizer was 22% greater in the first study and 100% greater in the second study than those for plants grown with the conventional fertilizer. Plants grown in rockwool with the conventional fertilizer were 17% more productive in the first study and 46% more productive in the second study than those grown with the organic fertilizer. Taste test panelists (69%) could discern differences between samples from organically and conventionally grown basil plants, yet no preferences were shown.

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Steven C. Wiest and Roth E. Gaussoin

The following model simulates hourly temperature fluctuations at 6 Kansas stations:

\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \[T_{h}=\frac{(T_{x}-T_{n})}{2}\left[\mathrm{exp}\left(\frac{0.693h}{DL_{M}}\right)-1\right]+T_{n};{\ }0{\leq}h{\leq}DL_{M}\] \end{document}
\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \[T_{h}=\frac{(T_{x}-T_{n})}{2}\left[1+\mathrm{sin}\frac{{\pi}(h-DL_{M})}{2(23-DL_{M})}\right]+T_{n};{\ }DL_{M}{\leq}h{\leq}23\] \end{document}
where h = time (hours after sunrise), DLM = 20.6 - 0.6 * daylength (DL), Th = temperature at time h, and TX and Tn = maximum and minimum temperature, respectively. Required inputs are daily TX and Tn and site latitude (for the calculation of DL). Whereas other models have been derived by fitting equations to chronological temperatures, this model was derived by daily fitting of hourly temperatures sorted by amplitude. Errors from this model are generally lower, and less seasonally biased, than those from other models tested.

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Steven C. Wiest and Roth E. Gaussoin

The following model simulates hourly temperature fluctuations at 6 Kansas stations:

\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \[T_{h}=\frac{(T_{x}-T_{n})}{2}\left[\mathrm{exp}\left(\frac{0.693h}{DL_{M}}\right)-1\right]+T_{n};{\ }0{\leq}h{\leq}DL_{M}\] \end{document}
\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \[T_{h}=\frac{(T_{x}-T_{n})}{2}\left[1+\mathrm{sin}\frac{{\pi}(h-DL_{M})}{2(23-DL_{M})}\right]+T_{n};{\ }DL_{M}{\leq}h{\leq}23\] \end{document}
where h = time (hours after sunrise), DLM = 20.6 - 0.6 * daylength (DL), Th = temperature at time h, and TX and Tn = maximum and minimum temperature, respectively. Required inputs are daily TX and Tn and site latitude (for the calculation of DL). Whereas other models have been derived by fitting equations to chronological temperatures, this model was derived by daily fitting of hourly temperatures sorted by amplitude. Errors from this model are generally lower, and less seasonally biased, than those from other models tested.