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Doyle A. Smittle, W. Lamar Dickens, and James R. Stansell

An irrigation scheduling model for snap bean (Phaseolus vulgaris L.) was developed and validated. The irrigation scheduling model is represented by the equation: 12.7(i - 4) × 0.5ASW = Di-1 + [E(0.31 + 0.01i) - P - I]i, where crop age is i; effective root depth is 12.7(i - 4) with a maximum of 400 mm; usable water (cm3·cm-3 of soil) is 0.5 ASW, deficit on the previous day is Di-1; evapotranspiration is pan evaporation (E) times 0.31 + 0.01i; rainfall (mm) is P, and irrigation (mm) is I. The model was validated using a line source irrigation system with irrigation depths ranging from 3% to 145% of tbe model rate in 1985 and from 4% to 180% of the model rate in 1986. Nitrogen fertilization rates ranged from 50% to 150% of the recommended rate both years. Marketable pod yields increased as irrigation rate increased in 1985. Irrigation at 4%, 44%, 65%, 80%, 150%, and 180% of the model rate produced yields that were 4%, 39%, 71%, 85%, 92%, and 55% as great as yields with the model rate in 1986. Marketable pod yields increased as N rate increased when irrigation was applied at 80%, 100%, or 150% of the model rate in 1986, but pod yields varied less with N rate when irrigation was applied at 4%, 44%, 65%, or 180% of the model.

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William M. Randle

An interactive computer-based model has been developed to simulate the effects of precision planting onion on quality and yield. Variables used by the model are seed germination, plant survival, planter efficiency, onion growth potential, maximum onion size, sizing potential and inside-outside bed effects. Data bases obtained from 3 onion cultivars were used in the development of the model. The model shows when germination and plant survival are high, single seed drops by the planter results in high yield and large bulbs. At lower germination and survival values, however, a compromise is needed between maximizing yield and obtaining large bulbs.

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Duane W. Greene, Alan N. Lakso, Terence L. Robinson, and Phillip Schwallier

; McArtney and Obermiller, 2010 ; Ward and Marini, 1999 ). The premise on which our predictive model is based is the observation that fruit that are destined to drop will slow and stop growth well in advance of the actual time of abscission. This reduced

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Richard C. Beeson Jr.

In many sectors of agriculture, precision irrigation, applying only what water is needed for a given small area, has become a familiar term. Irrigation in most woody ornamental nurseries, though, has changed little since the 1960s. In many areas of the U.S., irrigation volumes required for nursery production have come under scrutiny due to projected, or real, competition for water with urban populations, or concerns over nursery runoff. Modeling of woody ornamental water use, and subsequent irrigation requirements, has been limited and focused mostly on trees. Previous research for modeling of non-tree water use is reviewed as an introduction to current efforts to develop models for precision irrigation of woody ornamentals. Pitfalls and limitations in current modeling efforts, along with suggestions for standardizing future research is emphasized. The latest model derived from recent research is presented.

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Silvia Jiménez Becker, Maria Teresa Lao, and Mari Luz Segura

rapidly, whereas the deductive regulation is potentially ideal to optimize the control of greenhouse crop mineral nutrition, it is based on the knowledge of plant responses to varying its environment, and it requires models ( Le Bot et al., 1998 ). The

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D. Schwarz, H.-P. Kläring, K.T. Ingram, and Y.-C. Hung

assistance. We also greatly appreciate Adolf Heissner for allowing us to use his empirical models of tomato photosynthesis and transpiration. The cost of publishing this paper was defrayed in part by the payment of page charges. Under postal regulations, this

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Jianlu Zhang and Cathy Taylor

appropriate fruit and nut species and cultivars for the climate of a given site, researchers have developed chilling models, which convert temperature records into a metric of coldness” ( Luedeling et al., 2009c ). The chilling process in trees is not

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Joanne Logan

water is in the barrel before the homeowner decides to use it. Most of these factors involve day-to-day decisions by the homeowner, and support the use of a model based on daily data. Taking these factors into consideration will help the extension agent

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Guangyao Wang, Jeff D. Ehlers, Philip A. Roberts, Eddie J. Ogbuchiekwe, and Milton E. McGiffen Jr.

Competitive cover crop varieties are needed to reduce weed problems and herbicide use. Identifying specific crop traits related to competitive ability would provide breeders with useful information that could be used to develop an ideotype for highly competitive cover crop varieties. Cowpea varieties with different growth habits were grown with sunflower or purslane to determinate which growth habit (erect, semi-erect, and prostrate) is more likely to be most competitive with tall or short growing weeds. Regression models were used to analyze additive and replacement series experiments. The results showed that erect varieties were more competitive with weeds than semi-erect varieties and prostrate varieties. However, the simple regression models did not provide much information about competitive mechanisms helpful to breeders. An ecophysiological model, INTERCOM, was used to understand competitive mechanisms. Validated INTERCOM model provided us with more information about competitive cover crop traits, including competitive growth habit.

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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.