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Engineering for Vegetable Storage Design and Management1. NATURE AND IMPORTANCE OF THE PROBLEM and RELEVANCE TO THE MISSION OF THE MAES:The emphasis in this research project is on assisting vegetable producers in Michigan to maintain quality during postharvest storage and handling, with an initial emphasis on potatoes, and including carrots (and possibly other vegetables) as development progresses. The market decides the definition of quality.
Another factor in the definition of quality is the amount of sprouting. Sprout inhibitors have been commonly applied to potatoes during storage. The potato industry is interested in reducing the use of chemicals, including those used for sprout inhibition. Low temperature storage (e.g. "cold chipping" varieties) offers the hope of reducing or eliminating the need for chemical sprout inhibitors. Agricultural crops in storage must be maintained at the proper environmental conditions to prevent deterioration. For example:
A better understanding of postharvest storage management response of new and existing varieties will assist growers in better managing potatoes in storage. The Michigan potato industry has identified storage as their second priority in the 2001 Project GREEEN plant industry priorities: Storage management is a significant component for the marketability of Michigan potatoes. Storage management profiles of new varieties and advanced seedlings are essential ... The Michigan carrot industry has also identified storage technology as one of their priorities. Past storage research has depended on small-scale and medium-scale storage of these products, sometimes replicated, to generate answers for the storage manager. While these data can help provide parameters to understand the storage process, they are necessarily limited in the range of their applicability due to bio-diversity and variations in environmental conditions. The proposed approach in this project is to extend the capabilities of computer simulation models of the storage process to include estimates of bio-chemical changes (such as starch - sugar conversion, produce maturity or sprouting), biological processes (such as rotting due to Phytophthora, Fusarium or Erwinia spp.) and variability due to the stochastic nature of biological and environmental aspects of agricultural produce storage. 2. LITERATURE REVIEWPotato storage research in Michigan (Brook 1995; Brook, 1999) is one of only two active U.S. programs. Past research has attempted to correlate the quality of potatoes in grower storages and in controlled research environments (Cargill 1986; Forbush 1989, 1993; Fick 1994. 1999). The success of that research led to the construction of four potato storage research bins in Bay County (Bishop, 1995). When those facilities became unavailable, the Michigan potato industry invested in the construction of a 6-bin facility adjacent to the MSU Montcalm potato research farm. For chip potatoes (the primary commercial crop in Michigan), sugars and chip color are the primary quality considerations. The reducing sugar content of the potato is affected by several factors, including variety, growing conditions, maturity at harvest, postharvest handling stress and the storage environment. Recommendations for managing chemically immature tubers have included pre-conditioning (Sowokinos 1988; Pritchard 1992). To avoid the build up of reducing sugars, a storage environment must be maintained that will inhibit the low temperature conversion of starch to sugar while enhancing tuber respiration to metabolize reducing sugars. On-going research is helping understand the metabolism of starch and sugars in the potato tuber (e.g. Sowokinos 1987, 1988, 1990; Copp, 2000). One concern for Michigan potato growers is a perceived need for extended season storage, with stored tubers marketed in to the months of May or June. One approach to making this work is to reduce the storage temperature to reduce the onset of tuber senescence (maturity). However, low tuber temperatures result in reduced respiration and can lead to low temperature sweetening (LTS - the accumulation of reducing sugars in the tubers; see Wismer 1995). However, as tubers age potato storage managers have found that LTS is not always reversible using reconditioning management techniques. Increases in amino acid content may help account for these observations (Brierley 1996). Current handling equipment has greatly reduced the time required for harvesting agricultural crops. However, the equipment can cause significant damage (Thornton 1985; Brook, 1993). A recent review of potato bruising has helped to outline the important factors (Brook, 1996). Postharvest handling stress does influence the sugar metabolism and chip quality of stored potatoes (Orr 1986; Sowokinos 1987, 1990). For potato storage managers, the occurrence of disease and subsequent rotting in storage is of concern. Condensation can occur on produce in a high humidity storage due to heat loss through the building envelope or due to temperature differences of potatoes brought in from the field. Condensation results in wet tuber surfaces which are the sites for tuber rot to begin (e.g. Hylmo 1976; Grahs 1977; Pringle 1996; Hardy 1997). The MSU agricultural produce storage model was initiated by Lerew (1978) and further tested for potatoes by Forbush (1989). However, it currently concentrates on heat and mass transfer in a two dimensional space. Other storage simulation research also concentrated mainly on heat and mass transfer (Hunter 1985; Marchant 1994b, 1994c; Gottschalk 1996). None of this previous research attempted to incorporate sugar metabolism related to chip quality or biological processes such as wound healing or disease development, from either a deterministic or stochastic viewpoint. The MSU grain dryer models have been adapted to consider the stochastic nature of these biological processes (Bakker-Arkema 1997; Liu 1997). Yang (1991) developed a 3-dimensional model of airflow in a potato storage. A model of the potato storage environment, along with estimations of bio-chemical and biological processes, can help also help develop improved real-time control processes (e.g. Marchant 1994a). The results of the simulation might also be used to develop expert systems for the management of storages (Schaper 1992; Landry 1994). 3. OBJECTIVETo develop a simulation of vegetable storages to better understand the effect of field production management, pre-storage handling stress, environmental conditions and storage management on produce quality, weight loss and disease control. 4. EXPERIMENTAL PROCEDURESModel: The MSU produce storage model (Lerew 1978) will be updated to run on modern PC's. In addition to the current heat-mass transfer calculations at each time-space point, the model will be modified or expanded to include descriptive equations of bio-chemical and biological processes important to understanding the response of the potato to the storage environment. The descriptive equations will initially be deterministic in nature. As the modeling effort progresses, the stochastic nature of the processes will be included in the equation parameters. Neural networks and other model development techniques will be used to help generate the necessary parameters for the descriptive equations. The bio-chemical and biological processes investigated will include:
Verification: The new MPIC experimental storage facility adjacent to the Montcalm potato research farm consists of six bins with independent air systems, refrigeration, humidification and environmental control computers. Each of the bins are filled in the fall with potatoes. Weight loss for each bin is monitored by weighing sample bags before and after storage, with the bags placed at three levels in each storage. Weight loss data is augmented by weighing the potatoes into and out of each storage. Potato samples are withdrawn on a regular basis during the storage season and analyzed for changes in potato quality (in particular, reducing sugar content and process product color). Each of the bins is operated according to different temperature management strategies or using different varieties to assess out-of-storage quality. The environmental control computers used in this facility record the operating conditions of each bin (temperature, humidity, carbon dioxide concentration, equipment operation times, etc) every 15-minutes. The data are stored on the storage facility computer and will be used for model verification, along with the results of the quality analysis on the potato samples and the final process quality of the potatoes in the bin. Other tuber sample constituents (such as amino acid content) will be investigated as a means of helping to understand quality changes in the tubers. The data discussed above will be used to verify the accuracy of the model. As model development continues, small-scale storage experiments will be conducted to help further develop and test aspects of the descriptive equations used in the model. Simulation: The parameters of the model will be adjusted (respiration, sugar metabolism and disease forecasting) to best approximate the response of the potatoes in the MPIC experimental storage. The model will then be used to simulate the produce response to different storage management strategies and ambient conditions. The results of these simulations will help the storage manager to understand the performance of that variety under a range of conditions. As descriptive equations are developed for new varieties and advanced seedlings, storage management profiles can be estimated before the varieties are introduced to the industry. Some questions that need evaluation under different potato storage management strategies and/or with different varieties include:
A model of the potato storage process that can be correlated with past practices and used to predict future effects can be a valuable tool for storage managers. Current services offered to the potato storage manager by Techmark, Inc. (Lansing, MI) include bi-weekly monitoring of tuber sugar content and chip quality, and monthly reports of storage environmental conditions and storage controler performance. Data from these efforts can be used to "ground truth" the model for individual bins. The model can then be used to predict short-term and long-term effects of past management practices, and recommend future management practices to maintain potato quality. The model can also be useful in further refining computer based strategies for control of the potato storage environment. Carrots: Similar efforts for modeling the response of carrots to the storage environment will be conducted. Carrot quality during storage is influenced by weight loss, color changes, development of undesirable flavors and potential disease development. When combined with our current understanding of airflow distribution based on potato storage experience, a model of the carrot storage environment will help carrot growers to better understand the effect of field production management, pre-storage handling stress, environmental conditions and storage management on produce quality, weight loss and disease control. 5. PLANS TO DISSEMINATE INFORMATION FROM STATE RESEARCHThe details of the storage simulation model will be published after its first transformation to run on modern PC's (it has not been published to date in any form outside the original Ph.D. dissertation). As the various descriptive equations are developed and validated, the use of the equation(s) with the model in generalized simulation situations will published (likely in cooperation with one of the relevant listed consultants). These publications will include validation with one or more yeats of data from the MPIC experimental storage bins. The project principal investigator will work with the storage and handling committee of the Michigan potato industry and the research committee of the Michigan carrot industry to develop relevant and useful simulation exercises. The results of these simulation exercises will be presented to storage managers at regional and state-wide meetings. Recommendations developed from these simulation exercises will be captured in MSU Extension bulletins. Eventual adaptation of the model by firms marketing storage environment control computers (such as Techmark, Inc.) is expected. The simulation model is expected to be a valuable part of on-going storage management information and recommendation programs. REFERENCES
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