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Kent D. Kobayashi

The simulation programs Stella® (High Performance Systems) and Extend™ (Imagine That!) were used on Apple® Macintosh® computers in a graduate course on crop modeling to develop crop simulation models. Students developed models as part of their homework and laboratory assignments and their semester project Stella offered the advantage of building models using a relational diagram displaying state, rate, driving, and auxiliary variables. Arrows connecting the variables showed the relationships among the variables as information or material flows. Stella automatically kept track of differential equations and integration. No complicated programming was required of the students. Extend used the idea of blocks representing the different parts of a system. Lines connected the inputs and outputs to and from the different blocks. Extend was more flexible than Stella by giving the students the opportunity to do their own programming in a language similar to C. Also, with its dialog boxes, Extend more easily allowed the students to run multiple simulations answering “What if” questions. Both programs quickly enabled students to develop crop simulation models without the hindrance of extensive learning of a programming language or delving deeply into the mathematics of modeling.

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Katrin Kahlen and Hartmut Stützel

For many objectives in plant growth analysis and structural crop modeling, nondestructive measurement and estimation of plant organ dimensions and masses are highly desirable. One-dimensional traits such as organ length can be determined in situ

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J.D. Carlson and J.F. Hancock Jr.

Fifteen years of Michigan harvest data for highbush blueberry (Vacciniun corymbosum L.) were used in conjunction with daily maximum and minimum temperatures to determine appropriate heat-unit models for first-picking dates of 13 cultivars. For each cultivar, an optimal heat-unit model was chosen after evaluating the performance of a standard method with 72 combinations of three variables: a) starting date for the heat-unit accumulations (SDATE), b) low-temperature threshold (TLOW), and c) high-temperature threshold (THIGH). The optimal model sought to include the most important criteria values with respect to model performance and to minimize the average square of the prediction error (days) and the range in that error. Compared with a strict calendar-day method of estimating harvest dates, the heat-unit models reduced the standard deviation of the prediction error from 22% to 69%, depending on cultivar.

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Jens J. Brøndum and Royal D. Heins

Effects of temperature and photoperiod on growth rates and morphological development of Dahlia pinnata Cav. `Royal Dahlietta Yellow' were determined by growing plants under 45 combinations of day and night temperatures (DT and NT, respectively, and photoperiod. DT and NT ranged from 10 to 30C and photoperiods from 10 to 24 hours·day-1. Photoperiod influenced vegetative development more than reproductive development as plants flowered in all photoperiods. Lateral shoot count and length decreased and tuberous root weight increased as photoperiod decreased from 16 to 10 hours. Temperature interacted with photoperiod to greatly increase tuberous root formation as temperature decreased from 25 to 15C. Increasing temperature from 20 to 30C increased the number of nodes below the first flower. Flower count and diameter decreased as average daily temperature increased. Nonlinear regression analysis was used to estimate the maximum rate and the minimum, optimum, and maximum temperatures for leaf-pair unfolding rate (0.29 leaf pair/day, 5.5, 24.6, and 34.9C, respectively), flower development rate from pinch to visible bud (0.07 flower/day, 2.4, 22.4, and 31.1C, respectively), and flower development rate from visible bud to flower (0.054 flowers/day, 5.2, 24.4, and 31.1C, respectively). The results collectively indicate a relatively narrow set of conditions for optimal `Royal Dahlietta Yellow' dahlia flowering, with optimal defined as fast-developing plants with many large flower buds and satisfactory plant height. These conditions were a 12- to 14-hour photoperiod and ≈ 20C.

Open access

Ryan M. Warner

Twenty petunia (Petunia ×hybrida) cultivars were grown at 14, 17, and 20 °C to quantify the impact of temperature on time to flowering, flowering and development rates, and crop quality parameters. Increasing temperature increased vegetative development rates and reduced time to flower (TTF) for all cultivars. Linear functions generated to describe the effects of temperature on the flowering rate (1/TTF) revealed considerable variability in the temperature sensitivity of flowering rates across cultivars. The minimum temperature for the rate of progress toward flowering (Tbase) ranged from 0.15 °C for ‘Damask Purple’ to 7.1 °C for ‘Wave Purple’. The crop quality parameters plant height and branch and flower bud number were all influenced by interactions between cultivar and temperature. Plant height at flowering was unaffected by temperature for 13 of the 20 cultivars, whereas the height of five cultivars was lower at 20 °C compared with 14 °C, and two cultivars were shortest at 17 °C. The branch number of six cultivars was lower at 14 °C than at 17 or 20 °C, whereas three cultivars produced more branches at 17 °C compared with 20 °C. The branch number of 11 cultivars was not impacted by temperature. For 11 of the 20 cultivars, the flower bud number was greater at 14 °C than at 20 °C, whereas temperature did not influence the flower bud number for the other nine cultivars. The results of this work could help to improve production efficiency by allowing cultivars to be placed in temperature-response groups based on the temperature sensitivity of flowering time and/or crop quality parameters.

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Isabelle Grechi, Nadine Hilgert, Michel Génard, and Françoise Lescourret

efforts directed toward improved control of fruit quality and its variability are needed. Crop models are powerful tools for such research efforts ( Boote et al., 1996 ; Lentz, 1998 ). However, despite a few exceptions, quality is seldom addressed in

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Soo-Hyung Kim, Jig Han Jeong, and Lloyd L. Nackley

impacts and vulnerability. Crop models are essential tools for assessing climate impacts on crops, assisting crop breeding and management decisions, forecasting crop yield for policy and economic decisions, and developing adaptive cropping solutions in a

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Kenneth J. Boote, Maria R. Rybak, Johan M.S. Scholberg, and James W. Jones

objectives of this work are to: 1) use recent literature to update temperature-based crop model parameters of the CROPGRO-Tomato model; and 2) recalibrate and evaluate the model for more accurate simulation of temperature effects on crop development, daily DM

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L-Y. Li and J.H. Lieth

Greenhouse crop production involves high rates of energy input to implement a greenhouse microclimate that results in high productivity levels, correct crop timing, and desired product specifications. Producing quality crops while maintaining low energy consumption is achievable through improved crop management and environment control strategies. In this study, greenhouse crops and their microclimate were treated as an integrated system that was driven by solar radiation and external energy input. A set of simulation models were developed to describe the greenhouse climate, the crop, and their dynamic interactions. The temperature and light regimes were simulated using the greenhouse energy budget under typical weather patterns. The crop model simulated growth and development of several ornamental greenhouse crops. Coupling the crop model with the greenhouse energy model resulted in a system that allows determination of optimal strategies for crop management and environmental control. This greenhouse/crop system can be used to assist growers with formulating strategies of greenhouse production management.

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Bandara Gajanayake, K. Raja Reddy, Mark W. Shankle, and Ramon A. Arancibia

Sweetpotato [Ipomoea batatas (L.) Lam.] storage root formation is a complex developmental process. Little quantitative information is available on storage root initiation in response to a wide range of soil moisture levels. This study aimed to quantify the effects of different levels of soil moisture on sweetpotato storage root initiation and to develop functional relationships for crop modeling. Five levels of soil moisture, 0.256, 0.216, 0.164, 0.107, and 0.058 m3·m−3 soil, were maintained using sensor-based soil moisture monitoring and semiautomated programmed irrigation. Two commercial sweetpotato cultivars, Beauregard and Evangeline, were grown in pots under greenhouse conditions and treatments were imposed from transplanting to 50 days. Identification of storage roots was based on anatomical, using cross-sections of adventitious roots, and visual features harvested at 5-day intervals from 14 to 50 days after transplanting (DAT). Recorded time-series storage root numbers exhibited sigmoidal responses at all soil moisture levels in both cultivars. Time to 50% storage root initiation and maximum storage root numbers were estimated from those curves. Rate of storage root development was determined as a reciprocal of time to 50% storage root formation data. Time to 50% storage root initiation declined quadratically from 0.05 to 0.15 m3·m−3 soil moisture and increased slightly at the higher soil moisture levels in both the cultivars. Cultivars differed in time to 50% storage root initiation and the storage root developmental rate. Soil moisture optima for storage root initiation were 0.168 and 0.199 m3·m−3 soil, equivalent to 63% and 75% field capacity for cultivars Beauregard and Evangeline, respectively. The data and the inferences derived from the functional algorithms developed in this study could be used to advise growers to schedule irrigation more precisely, make planting decisions based on available soil moisture, and to develop sweetpotato crop models for field applications.