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IMPORTANCE AND METHOD OF CROP CULTIVAR EVALUATION FOR ALSS: APPLICATION ON  TOMATO CULTIVAR SELECTION.   C. Moraru¹, C.M. Gregson¹, T-C Lee¹, L. Logendra² and H. Janes². ¹Food Science Dept., ²Dept. of Plant Sciences and ^1,2NJ-NSCORT, Rutgers University, New Brunswick, NJ.

     The challenge in selecting crops for an Advanced Life Support  System (ALSS) is to find cultivars able to meet nutritional and quality requirements while growing in limited space and generating low waste. The objective of this study was to establish a logical approach to assess potential plant cultivars for fresh consumption and/or processing within ALSS, and to test it using tomato as an example crop. 

     This approach started by choosing all pertinent quality attributes and defining for each the acceptable range and, when possible, the optimum value.  An evaluation scheme was developed based on a summation of weighted ranks, but only for cultivars whose attributes fell within the acceptable ranges. Finally, experimental data was used in this scheme to evaluate the quality of each cultivar and decide on the most suitable one. In our example, 11 growth, 12 physical/chemical and 7 sensory indexes were identified for ALS tomato. 16 tomato cultivars (10 processing and 6 fresh-consumption ones) were hydroponically grown, their attributes quantified and ranked using the proposed scheme. 

     In developing the evaluation method, the choice of significant attributes and their weight in the overall ranking depends highly on the mission goals and design.  However, once they are set, the comparison between similar or slightly different crops (eg. processing versus fresh-consumption tomato) is facilitated.  In this case, the best performance was shown by the SUN 6117 variety.  Some of its indexes were: soluble solids 5.33°Brix, lycopene content 12.8 mg/100g, harvest index 0.75, firmness of 10.9 N/mm and very good sensory ratings.  

     This method is a logical and essential approach for evaluating crop varieties based on the relevance of quality attributes for the mission design. Among its benefits, the ability to identify key quality attributes for rapid initial evaluation may also be interesting for crop developers. 

     (Supported by NJ-NSCORT)