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Gisele Schoene, Thomas Yeager, and Joe Ritchie

In crop models, it is important to determine the leaf area, because the amount of light interception by leaves influences two very important processes in the plant: photosynthesis and evaporation. Leaf area is dependent on leaf appearance and expansion rates. Leaf appearance rate is driven mainly by temperature. Although the influence of temperature on leaf area development is well known for several agronomic crops, there is no information for woody ornamentals. An experiment was conducted to study the relationship between temperature and leaf appearance of container-grown sweet viburnum. Plants were grown in field conditions in Gainesville, Fla., during two growing periods (Apr. to Aug. 2004 and Aug. 2004 to Jan. 2005). Daily maximum and minimum temperature and leaf appearance were recorded. Linear regression equations were fitted to data and maximum and minimum temperature and leaf appearance were recorded. Linear regression equations were fitted to data and base temperature was assumed to be 8 °C. Thermal time (°C d) was calculated as daily average maximum and minimum air temperature minus the base temperature and was regressed against leaf number. The sum of accumulated thermal time was found to be linearly correlated with leaf number. Phyllochron, which is the thermal time between the appearances of successive leaves, was estimated 51 °C per day. The information presented in this study will be useful in modeling water use of sweet viburnum in response to environmental conditions.

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Todd Rosenstock and Patrick Brown

Alternate bearing exerts economic and environmental consequences through unfulfilled yield potential and fertilizer runoff, respectively. We will discuss a systematic biological–statistical modeling management integration approach to address the concert of mechanisms catalyzing alternate bearing. New engineering technologies (precision harvesting, spatially variable fertigation, and mathematical crop modeling) are enabling optimization of alternate bearing systems. Four years of harvest data have been collected, documenting yield per tree of an 80-acre orchard. These results have shown variability within orchard to range from 20–180 lbs per tree per year. Results indicate irregular patterns not directly correlated to previous yield, soil, or tissue nutrient levels, or pollen abundance. Nor does significant autocorrelation of high or low yields occur throughout the orchard, suggesting that genetically dissimilar rootstocks may have significant impact. The general division of high- and low-yielding halves of the orchard may infer a biotic incongruency in microclimates. This orchard does not display a traditional 1 year-on, 1 year-off cyclic pattern. Delineation of causal mechanisms and the ability to manage effectively for current demands will empower growers to evaluate their fertilization, irrigation, male: female ratio, site selection, and economic planning. In comparison to annual crops, the application of precision agriculture to tree crops is more complex and profitable. When applied in conjunction, the aforementioned methods will have the ability to forecast yields, isolate mechanisms of alternate bearing, selectively manage resources, locate superior individuals, and establish new paradigms for experimental designs in perennial tree crops.

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Allen V. Barker

preserves the topics of analysis of yield in the first book and updates the first publication with information of phenology, crop modeling, and sustainable crop production. The new book has 10 chapters of text with numerous line drawings and tables and over

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Tasneem M. Vaid, Erik S. Runkle, and Jonathan M. Frantz

number in 15 ornamental annual crops modeled for the spring (•) and fall replication (○). When regression slopes were nonsignificant between the two replications ( P ≤ 0.05), data were pooled (■) for statistical analysis. Each symbol represents the

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Ellen T. Paparozzi, Neil Mattson, Mara Grossman, Stephanie Burnett, and Roberto Lopez

crop models during production using e-tools such as podcasts, grower alerts, and smartphone apps. There is a need to move beyond production research to develop strategies that ensure postharvest longevity and garden performance. Faculty must be able to

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Matthew G. Blanchard and Erik S. Runkle

was controlled by MDT and not DIF in pinnate dahlia ( Dahlia pinnata Cav.; Brøndum and Heins, 1993 ), pansy ( Niu et al., 2000 ), and vinca ( Catharanthus roseus L.; Pietsch et al., 1995 ). Crop models that predict flowering time under different

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Arthur Villordon, Christopher Clark, Tara Smith, Don Ferrin, and Don LaBonte

approach was used to estimate soil heat units. Representations of air and soil temperature as air and soil heat units, respectively, have been routinely used in crop modeling ( Pale et al., 2003 ; Riha et al., 1996 ). Descriptive statistics of

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Jonathan M. Frantz

.C. Langhans, R.W. Both, A.J. Albright, L.D. 1998 Shoot and root temperature effects on lettuce growth in a floating hydroponic system J. Amer. Soc. Hort. Sci. 123 361 364 Thornley, J.H.M. Johnson, I.R. 1990 Plant and crop modeling Clarendon Press Oxford, UK U

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Ralf Uptmoor, Mildred Osei-Kwarteng, Susanne Gürtler, and Hartmut Stützel

were largely reduced when yield and biomass were predicted on independent datasets. One major reason for the low accuracy of crop models in predicting genotype effects may be that experimental errors blur trait differences between genotypes and that

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Sezgin Uzun

understanding the factors affecting crop photosynthesis, which in turn account for the majority of variation in yield increases. The aim of plant or crop models is to describe mathematically the increase of biomass in terms of fresh weight, dry weight, volume