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Dru N. Montri, Bridget K. Behe, and Kimberly Chung

, 2010a ). A central terminal model EBT program at farmers markets, however, can alleviate much of the burden for individual vendors, increasing their sales especially among clientele who might not otherwise afford fresh produce. Under a centralized

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Juan C. Diaz-Perez, Silvia Bautista, and Ramon Villanueva

Sapote mamey is a sweet and aromatic tropical fruit that is very perishable. It is a climacteric fruit and has high rates of respiration and ethylene production. Maturity indices for this commodity are difficult to define because fruit show few changes in external appearance as they ripen. The fruit flesh, however, shows large changes in color, firmness, and sugar content measured as soluble solids content (SSC). The objective was to model fruit ripeness from measurements of SSC. We selected SSC because it is easy to measure and because sweetness is an important quality attribute in sapote mamey. Typical values of SSC range from 12% (immediately after harvest) to 30% to 35% (ripe fruit). A linear-plateau model was used to describe the changes in SSC over time of ripening fruit kept at different temperatures. The model assumed that, as fruit ripened, SSC increased at a linear rate reaching a maximum of 30% SSC at the ripe stage after which SSC changed little. From the model we calculated the rate of fruit ripening and the time to reach the ripening stage (30% SSC). The rate of ripening showed a quadratic relationship with storage temperature. Fruit kept at 27, 25, or 20 °C ripened 3.5, 5, or 7 days after harvest. The model can be used to estimate when fruit will reach the ripe stage, as long as we know the initial SSC and storage temperature. This model was constructed from data obtained over 2 years from fruit grown in the state of Morelos, Mexico. It is still to be tested for its applicability on fruit from other growing regions.

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Dewayne L. Ingram, Charles R. Hall, and Joshua Knight

life cycle. The goal of this research was to model and analyze production systems using LCA procedures for major environmental horticulture crop groups. Greenhouse gas (GHG) emissions and the subsequent carbon footprint (CF) have been reported for

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James E. Faust and Royal D. Heins

An energy-balance model is described that predicts vinca (Catharanthus roseus L.) shoot-tip temperature using four environmental measurements: solar radiation and dry bulb, wet bulb, and glazing material temperature. The time and magnitude of the differences between shoot-tip and air temperature were determined in greenhouses maintained at air temperatures of 15, 20, 25, 30, or 35 °C. At night, shoot-tip temperature was always below air temperature. Shoot-tip temperature decreased from 0.5 to 5 °C below air temperature as greenhouse glass temperature decreased from 2 to 15 °C below air temperature. During the photoperiod under low vapor-pressure deficit (VPD) and low air temperature, shoot-tip temperature increased ≈4 °C as solar radiation increased from 0 to 600 W·m-2. Under high VPD and high air temperature, shoot-tip temperature initially decreased 1 to 2 °C at sunrise, then increased later in the morning as solar radiation increased. The model predicted shoot-tip temperatures within ±1 °C of 81% of the observed 1-hour average shoot-tip temperatures. The model was used to simulate shoot-tip temperatures under different VPD, solar radiation, and air temperatures. Since the rate of leaf and flower development are influenced by the temperature of the meristematic tissues, a model of shoot-tip temperature will be a valuable tool to predict plant development in greenhouses and to control the greenhouse environment based on a plant temperature setpoint.

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Michel Génard and Michel Souty

The edible quality of peaches (Prunus persica L. Batsch) to a great extent depends on their sweetness, which is related to sugar composition. Our objective was to develop a model to predict carbon partitioning within fruit flesh and to predict the sucrose, sorbitol, glucose, and fructose contents. The model is dynamic and deterministic and was designed to be driven by the flesh dry-weight growth curve, flesh water content, and temperature data. It uses differential equations where the state of the system is defined by variables that describe how much carbon is present as each form of sugar and as other compounds (acids and structural carbohydrates). The rates of change of these amounts of carbon depend on the current values of corresponding variables and on the transfer functions between them. These functions are defined by rate constants or by functions of degree-days after full bloom. The model was calibrated and tested using data sets from treatments that covered several leaf: fruit ratios. The predictions of the model were in fairly good agreement with experimental data. A sensitivity analysis was performed to identify the most influential transfer function parameters. Carbon flows between sugar forms were analyzed. Sucrose, which was the most abundant sugar, and fructose, which is the sweetest, contributed most to fruit sweetness. Simulations were performed to study the effects of changes in fruit growth-curve parameters on sugar contents and concentrations.

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Patricia I. Garriz, Hugo L. Alvarez, and Graciela M. Colavita

Nondestructive estimation of pear fruit weight is an important horticultural element for size prediction, particularly when repeated measurements of the same tree must be made without affecting growth. Our objective was to develop a method for determining pear fruit weight (W) using models correlating it with fruit maximum diameter (D), an easily measured dimension. A mature crop of Pyrus communis L. cv. Williams was studied at our Experimental Farm. Five trees were selected at random and fruits were sampled at weekly intervals, starting in September, 21 days after full bloom (DFB) and ending in January, 142 DFB, during three growing seasons (1991–92, 1992–93, and 1993–94). Regression equations were developed using SYSTAT procedure. Data for three years were amalgamated because analysis showed that their curves did not differ. W vs. D was best fitted to the model W = 0,8236 D2.778 R 2 = 0,98. Variability of W and D increased with fruit growth.

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Jens J. Brondum and Royal D. Heins

Dahlia “Royal Dahlietta Yellow” plants were grown in controlled temperature chambers under 25 different day and night temperature environments ranging from 10°C to 30°C. The day length was 12 hours with an average PPF level of 300 micromolm-2 s-1 at canopy level. Leaf unfolding rate, shoot elongation and flower development rate were determined and models developed. Leaf unfolding rate increased as temperature increased up to 25°C. Stem elongation increased as the difference between day and night temperature increased. Flower initiation was delayed at high (30°C) temperature and flower development rate increased as temperature increased from 10°C to 25°C. Plants are currently being grown under greenhouse conditions to provide data for validating the models.

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Leena Lindén, Hannu Rita, and Terhi Suojala

Logit models were used to analyze freeze-survival data of apple (Malus domestica Borkh.). The effects of hardening and dehardening treatments and two treatment durations on lethal temperature were studied using two cultivars. The major benefits of logit models were 1) the form of the sampling variation in the qualitative response variable was taken into account, 2) the lethal temperatures could be estimated with confidence intervals, and 3) the effects of treatments could be interpreted and compared easily using odds ratios. The momentary frost resistance estimates for `Antonovka' and `Samo' were –46 and –43C, respectively. Dehardening at 14C raised the lethal temperature by 12 to 15C, whereas hardening at –15C did not affect the frost resistance of either cultivar.

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James A. Poss, Christy T. Carter, Catherine M. Grieve, and Peter J. Shouse

Common stock flower production can be achieved under moderate levels of salinity and relatively low levels of nitrogen with no significant decrease in quality in a closed-recirculating irrigation system. A 4 × 4 factorial design with partial replication was used to assess the effects of salinity and nitrogen on the production of Matthiolaincana (L.). Seeds were sown in outdoor volumetric lysimeters at the George E. Brown, Jr., Salinity Laboratory in Riverside, Calif., with target electrical conductivity (EC) levels of 2, 5, 8, and 11 dS·m–1 combined with four nitrogen treatments of 35, 50, 75, and 100 ppm N. An empirical model was implemented to evaluate the growth response of each combination of salinity and nitrogen treatments over the course of plant development. The three-phase model is represented by an initial size parameter (alpha), an estimation of the intrinsic growth rate of the exponential phase (beta), a transitional phase between the first two phases (tl), the length of the linear phase (epsilon), and the final intrinsic saturation rate (gamma), The model successfully fitted the plant height data over time for all 16 nitrogen and salinity treatment combinations. Effects of salinity on epsilon and t2 (epsilon + t1) were nonsignificant. Nitrogen treatments had no significant effect on any of the model parameters and the effect of salinity was greatest when irrigation water EC was 11 dS·m–1. The length of the flower-bearing stems exceeded the standards recommended for commercial acceptability in all treatments (>41 cm). If 60 cm is the minimum length acceptable, then 50 ppm N or more where the EC was 8 dS·m–1 or less is required. Nitrogen uptake per unit evapotranspiration increased with salinity and nitrogen.

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Bing-Rui Ni and Kent J. Bradford

Cell growth models were applied to characterize the response of seed germination, based upon the timing of radicle emergence, to y and ABA. Using probit analysis, three basic parameters can be derived to describe the population characteristics of seed lots. In the response of seed germination to osmotic stress, these three parameters are the “hydrotime constant” (q H), the mean base water potential (y b), and the standard deviation (s b) population. In the response to ABA, they are the “ABA-time constant” (q ABA), the mean base ABA concentration (ABAb), and the standard deviation (s ABAb) of the seed population. Using only these three parameters, germination time courses can be predicted at any corresponding medium y or ABA concentration. In the presence of both ABA and osmotic stress, the same parameters can be used to predict seed germination time courses with any combination of y and ABA concentration. The water relations model and the ABA model were additive and it appeared that the two factors slowed down germination independently. Effects of osmotic stress and ABA on the parameters in Lockhart equation are also discussed.