Tomato Fresh Produce Inventory Traceability Software:

Tomato Fresh Produce Inventory Traceability Software for accurate order filling & production

View Fresh Produce Inventory Traceability Software Specifications.

TOMATO PACKING TECHNOLOGY
The most commonly used indicator of fecal contamination in fresh produce production and packing is Escherichia coli. In depth analysis of the prevalence and characteristics of naturally occurring E. coli strains in these environments is important because it can (1) serve as an indicator of sources of fecal contamination; and (2) provide information on strain pathogenicity, persistence, and other defining characteristics such as multidrug resistance. In this study, we analyzed 341 E. coli strains isolated from the jalapeño pepper, tomato and cantaloupe farm environments, in Northeast Mexico. Strains were isolated from produce, farmworkers' hands, soil and water. Pathotypes, genotypes, biofilm formation and antibiotic resistance were characterized. Phylogenetic subgroups and identification of diarrheagenic E. coli were determined by PCR; biofilm formation was quantified using a plate-based colorimetric method. Antibiotic resistance was analyzed by the Kirby Bauer diffusion disc method. Most isolates (N = 293, 86%) belonged to phylogenetic group A. Only four isolates (1.2%) were diarrheagenic: EPEC (N = 3) and ETEC (N = 1). Antibiotic resistance to tetracycline (23.2%) and ampicillin (19.9%) was high, and only 3.5% of the strains presented resistance to >5 antibiotics. Biofilms were produced by most strains (76%), among which 34.4% were categorized as high producers. The presence of antibiotic resistant E. coli strains that may contain gene markers for pathogenicity and which can form biofilms suggests potential health risks for consumers.

Tomato Fresh Produce Inventory Traceability Software manages food safety

TOMATO PACKING PROCESS
A fuzzy mathematical program is formed when the strict requirements within a mathematical program (objective coefficients, right-hand-side values, inequality conditions, etc.) are fuzzified. In general, such fuzzifying is appropriate for situations where the values or conditions are subjects of perception. In tomato packing, uncertain elements attributed to human perception are quite common. Such elements include harvest time, tomato packing rate, and shortage cost. In this paper, we first provide an LP formulation to determine the production schedule for a fresh tomato packinghouse. Then the corresponding fuzzy elements are fuzzified into a fuzzy model which is solved using an auxiliary model (mixed 0–1 LP). Using real-life data, we compare the cost obtained from the LP to that from the fuzzy model. It is found that the cost from the former is substantially higher. We observe that the rigid tomato packing requirements in the LP results in an unrealistic optimal solution, while the fuzzy programming seeks to realize a desirable solution (as perceived by the user) by relaxing some resource restrictions. It is further observed that such opportunistic relaxation of constraints to achieve a better solution is typical of decision-making behavior in tomato packing.