Large quantities of fresh water are used intensively in the washing, cutting, peeling and disinfection of fruits and vegetables, resulting in high solids loading of the wash-water. Review of the literature shows that there is limited information available on how to treat this wash-water on-site. Accordingly, an investigative program was established by sampling wash-water from two industrial partners processing root vegetables to determine the best available approach. Bench scale technologies tested for solids removal were dissolved air flotation (DAF) and centrifuge, followed by ultraviolet (UV) disinfection to evaluate the potential for water reuse. The results showed that DAF and centrifuge were able to remove solids at an efficiency greater than 95%. The DAF process was also able to remove higher levels of dissolved matter and nutrients in comparison to the centrifuge. The DAF process was also able to produce waters with higher transmittance, which leads to improved filtration and UV disinfection for water reuse. Membrane filtration feasibility testing showed that high quality waters can be produced as low as 2 NTU and 4 NTU, following pretreatment with DAF and centrifuge, respectively. However, filtration was unable to remove E. coli. Collimated beam results show that UV disinfection is needed to allow for water reuse.

Wastewaters from the fresh produce processing industry are high in solids and organic matter requiring adequate treatment prior to disposal or recycling. Characterization of the processing wastewater, also referred to as wash-water is challenging, as the quality is a function of the produce. Analysis of water quality parameters, such as total suspended solids, total solids, total dissolved solids, chemical oxygen demand, biochemical oxygen demand, total nitrogen, total phosphorus, ammonia, and electrical conductivity from different fruit and vegetable operations were analyzed to develop the innovative power function models and ranking system to estimate wash-water quality. The developed models take the form of Y = a(x), where Y, a, x, and b are estimate, scale, rank, and location parameters, respectively. The location and rank range from -0.65 to -3.18 and 0.05 (worst water quality) to 1, respectively, while the scale parameters are highly variable. Average and standard deviation estimation models show a very good fit for washing only (R > 73%) and washing with processing (R > 79%). The models and ranks highlight the degree of treatment required to address protection of surface and ground water and make the water quality conform to regulatory standards, benefiting watershed managers, government agencies, consultants, farmers, producers, processors and technology providers.

On average, it is estimated that up to 5 liters of wastewater is generated per kg of produce in postharvest processing of fruit, leafy greens and root vegetables. The typical wastewater parameters vary in concentration (solids content, COD, BOD, nitrogen, phosphorus) based on the produce being processed. The challenge for producers and regulators is that the selection of the appropriate treatment technology is challenging, so decision matrices were developed to narrow down the treatment selections. Wash-waters for different types of fruit and vegetables from two different operation types, washing only vs. washing and processing. Bench-scale treatments selected for testing included settling, coagulation and flocculation with settling, centrifuge, dissolved air flotation, electrocoagulation, screening, and hydrocyclone. The developed decision matrices summarize the removal effectiveness of the different treatments for typical wastewater parameters and serve as a reference tool in understanding wash-water treatment technologies and their effectiveness in treating various wash-waters.

On average, it is estimated that up to 5 liters of wastewater is generated per kg of produce in post-harvest processing of fruit, leafy greens and root vegetables. The typical wastewater parameters vary in concentration (solids content, COD, BOD, nitrogen, phosphorus) based on the produce being processed. The challenge for producers and regulators is that the selection of the appropriate treatment technology is challenging, so decision matrices were developed to narrow down the treatment selections. Wash-waters for different types of fruit and vegetables from two different operation types, washing only vs. washing and processing. Bench-scale treatments selected for testing included settling, coagulation and flocculation with settling, centrifuge, dissolved air flotation, electrocoagulation, screening, and hydrocyclone. The developed decision matrices summarize the removal effectiveness of the different treatments for typical wastewater parameters and serve as a reference tool in understanding wash-water treatment technologies and their effectiveness in treating various wash-waters.

Wash-waters and wastewaters from the fruit and vegetable processing industry are characterized in terms of solids and organic content that requires treatment to meet regulatory standards for purpose-of-use. In the following, the efficacy of 13 different water remediation methods (coagulation, filtration, bioreactors, and ultraviolet-based methods) to treat fourteen types of wastewater derived from fruit and vegetable processing (fruit, root vegetables, leafy greens) were examined. Each treatment was assessed in terms of reducing suspended solids, total phosphorus, nitrogen, biochemical and chemical oxygen demand. From the data generated, it was possible to develop predictive modeling for each of the water treatments tested. Models to predict post-treatment water quality were studied and developed using multiple linear regression (coefficient of determination (R2) of 30 to 83%), which were improved by the generalized structure of group method of data handling models (R2 of 73–99%). The selection of multiple linear regression and the generalized structure of group method of data handling models was due to the ability of the models to produce robust equations for ease of use and practicality. The large variability and complex nature of wastewater quality parameters were challenging to represent in linear models; however, they were better suited for group method of data handling technique as shown in the study. The model provides an important tool to end users in selecting the appropriate treatment based on the original wastewater characteristics and required standards for the treated water.