Location: Food Quality Laboratory2022 Annual Report
Objective 1. Enhance key organoleptic and nutritional qualities of major horticultural crops using emerging production and post-harvest handling practices. Sub-obj. 1A. Improve food quality and nutrition, and harvesting efficiency for vegetables grown via controlled environment agriculture (CEA). Sub-obj. 1B. Develop novel technologies to support NASA’s mission in growing microgreens in space. Objective 2. Reduce post-harvest loss and waste and enhance marketability of fresh produce. Sub-obj. 2A. Non-destructive monitoring of produce quality and maturity via a paper sensor. Sub-obj. 2B. Improve quality and shelf life of fresh produce through collaborative breeding and cultivar selection. Sub-obj. 2C: Predicting consumers’ preferences for fruits and vegetables through advanced analyses of digital imagery and emotions. Objective 3. Improve product quality and sustainability through novel fresh-cut processing technologies and process optimization. Sub-obj. 3A. Develop novel fresh-cut produce wash and disinfection technologies for comprehensive improvement in food quality and safety. Sub-obj. 3B. Determine chemical profile of fresh-cut produce wash water in support of cost-effective water treatment and reuse. Sub-obj. 3C. Assess the potential use of nanoparticle coatings on the contact surface of equipment to optimize fresh-cut processing.
This project takes an integrated and holistic approach to tackle major food security problems by supporting efficient growth and harvesting of nutrient-dense food products and reducing post-harvest food loss and waste. This project consists three objectives. In objective 1, we will investigate the effect of light wavelength, intensity, and photoperiod on the growth, sensorial quality, and phytonutrient content of specialty vegetables. We will develop mechanical devices to facilitate harvesting of microgreens while minimizing tissue damage. We will also develop and/or evaluate soil mixes and soil-less growth media for seed fixation in microgravity. In objective 2, our team of scientists will collaborate with ARS breeders to identify lettuce cultivars resistant to enzymatic browning and having improved post-harvest quality and shelf life. We will continue collaborating with our university partner (and co-inventor) to advance our patent-pending paper sensor array for nondestructive quality evaluation. In objective 3, we will work with our industry partners to further develop, optimize, and commercialize our patented produce washing and disinfection technology. We will develop and optimize a novel in-flight washing system to improve the food quality and safety of fresh-cut products. This will be a continuation and expansion of the patented in-flight washing technology developed under a previous project. We will also investigate the major chemical components of fresh-cut produce wash water and develop approaches to support safe and cost-effective water reuse. Specifically, we will identify major compounds present in produce; their release during cutting; their reactivity with free chlorine during different washing stages; how such reaction contributes to the loss of free chlorine in wash water, and to difficulties in maintaining adequate chlorine levels; the type and amount of harmful disinfectant byproducts thus produced during washing; and effective methods to remove or mitigate the chemical oxygen demand (COD) and chlorine demand (CLD) in wash water during fresh-cut processing.
Progress was made on all 3 Objectives and their subobjectives, all of which fall under NP306, Produce Quality and New Uses. Progress on this project is focused on enhancing key organoleptic and nutritional qualities of major horticultural crops using innovative controlled environment agricultural production, novel post-harvest handling technologies and process optimization, reducing post-harvest losses and enhancing marketability of fresh produce. In support of Objective 1A, we investigated the effect of LED light wavelength, intensity, and dark/light intervals on the yield, plant growth, and phytochemical composition of red cabbage and “Ruby Streak” mustard microgreens, as well as red leaf lettuce. We established that red and magenta light treatments increase the content of ascorbic acid, anthocyanins, and glucosinolates in “Ruby Streak” mustard microgreens, as well as the pigmentation level of hydroponically grown lettuce, while blue and white light treatments yield higher fresh weight for both crops. In comparison, red light treatment increases both the yield and pigmentation of red cabbage microgreens. These findings highlight the species and cultivar-specific effect of light treatments and provide important guidance for choosing suitable growing conditions to achieve desirable crop quality. In Objective 1B, we have made progress in developing biopolymeric matrices as efficient growth substrates for microgreens. A novel composite material consisting of hydrogel backbone and organic growing mix particles was prepared with desirable water holding capacity and improved air-filled porosity. The material sustained a 12-d growth cycle for microgreens without the need for watering or human intervention, and it achieved a pronounced improvement in yield compared to traditional, pristine hydrogel formulas. In addition, the material delivered water and nutrients efficiently under simulated microgravity, which demonstrated the potential of the developed material in space farming. Furthermore, the added particles reduced the damage the porous hydrogel structure sustained during freezing and freeze-drying, improving performance after the above treatments. Follow-up studies are ongoing to integrate the freeze-dried composite material with a seeded mat consisting of biocompatible nanofiber coatings with the aim to produce a convenient kit that requires watering only once for seed germination and plant growth. In support of Objective 2A, we tested a novel chromogenic sensor array developed by our collaborator for detecting the freshness of fruits and vegetables. Twenty-one types of indicators for volatile organic compounds (VOCs) typical to fresh produce were screened with fresh-cut lettuce, cabbage, and strawberry. Nine indicators responded to the VOCs on the first day of storage, of which four showed progressing color changes over a 7-day storage period. These results will facilitate the further development and optimization of the sensor array and shed light on the opportunities and challenges of this technique in fresh produce quality monitoring. In support of Objective 2B, several approaches were undertaken to determine suitability of multiple romaine lettuce accessions as raw material for the fresh-cut industry. These included analysis of preferences for specific sensory traits, including color, aroma, freshness, and most importantly, incidence of browning. The benchmarking allowed us to rank recent introductions along with more traditional cultivars grown for the intact product market. We concluded that the presence of green color is not as influential as brown incidence can be on the consumer’s preferences. Moreover, we concluded that romaine lettuce is a product that can be effectively assessed with ad-hoc volunteer panels (rather than trained panelists and instrumentation), which can save much time and resources in commercial research settings. In support of Objective 2C, we studied the potential use of digital images for predicting in-situ consumer’s preferences and behavior. For this, machine learning-based software has been utilized, and adjusted to classify romaine lettuce according to their level of browning. The results with imagery analysis predicted the results obtained with trained panelists and instrumentation measurement. Moreover, we have started to analyze the significance of images (i.e. construction, resolution, sharpness). We are able to conclude from preliminary results of online surveys that digital images can be efficient tools for consumers to assess overall quality of different fruits. For more in-depth studies we have acquired devices to monitor emotional responses to different images and associated descriptors. In support of Objective 3A, we evaluated the second prototype of our in-flight washer (IFW) for organic matter removal and bacterial inactivation. This novel IFW canister has three layers of water nozzles (eight/layer) facing upwards/horizontally and radially inward, combined with two layers of upwards facing air nozzles, which together generate a fine water/air spray that meets the falling cut produce. The washed produce falls to an inclined conveyor belt, and discharges product to the next step in the washing process. This second IFW prototype can effectively remove tissue exudate, soil, and debris from diced cabbage, carrot, onion, and tomato, as well as chopped lettuces, with the spent wash water descending to the drain without reuse. This result shows that the second prototype IFW could be an alternative to a flume wash step. In support of Objective 3B, we investigated major sources of chemical oxygen demand (COD) and chlorine demand (CLD) in fresh-cut produce wash water. In collaboration with scientists at Georgia Institute of Technology, we also comprehensively evaluated the formation of disinfection byproducts (DBPs) during commercial washing of fresh-cut produce. Water and produce samples were collected at multiple time points and processing line locations from a collaborating fresh-cut processor. The DBPs investigated included a comprehensive suite of 33 conventional and emerging DBPs, i.e., 4 trihalomethanes (THMs), 9 haloacetic acids (HAAs), 9 nitrogenous DBPs (N-DBPs), and 11 carbonaceous DBPs (C-DBPs). The concentrations of THMs and HAAs on the washed products were further used to estimate potential exposure via consumption of fresh-cut produce. Findings advanced the understanding of the formation and removal of DBPs during wash processes and identified additional areas for further reduction in DBPs and food safety improvement. Results were directly shared with the industry and in peer-reviewed publications. In support of Objective 3C we have conducted some initial tests with materials provided by our collaborator (Texas A&M). This sub-objective was added during this year and was planned to be addressed during the next two years, taking advantage of a multi-institutional collaboration (see agreement section). In collaboration with University of Maryland, we evaluated the anthocyanin profiles of the fruits and petioles of wild-type strawberries and strawberries with different anthocyanin-regulating genes. Results demonstrated the differential regulation of anthocyanin biosynthesis in strawberry fruits and vegetative tissues, as well as under different lighting conditions. This information will benefit the produce industry in developing high-quality and nutritious strawberries for consumers.
1. Identified browning resistant lettuce cultivars to minimize post-harvest food loss and waste. Pinking and browning discoloration is a major quality problem that often renders fresh-cut lettuce products unsellable and not consumed. Current technologies including nitrogen flush and special packaging films used to mitigate this problem are costly and not reliable. Through a multi-region and cross-disciplinary collaboration, ARS researchers at Beltsville, Maryland and Salinas, California evaluated over 300 lettuce cultivars and breeding lines. The team identified several lettuce cultivars that are naturally resistant to browning discoloration. These high-quality cultivars provide environmentally friendly options for the fresh-cut produce industry to reduce post-harvest food loss and waste and minimize processing cost. They also allow consumers to enjoy browning-free lettuce longer, even after opening the packages.
2. Digital images and machine learning models supports sensory studies and online commerce. Traditionally, food quality research involves human inspection, complemented by physical (texture)-chemical analyses. This approach is ideal; however, it is time-consuming, labor-intensive, and expensive. Moreover, online shopping of fresh produce has increased during the COVID-19 pandemic, revealing that consumers may be willing to assess produce through digital images before their purchase decision. At the Food Quality Laboratory in Beltsville, Maryland, and through virtual evaluations, we have found that consumers can effectively determine the actual, physical appearance of fresh produce. This finding revealed the significance of utilizing well-constructed digital images for sensory research and online interphases in e-grocery shopping. Enabling consumers preferences for selecting produce such as lettuce, spinach, and strawberry.
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