Performing Department
Food Science
Non Technical Summary
The primary driver of consumer preference for foods is flavor. Light damage is well-known to degrade food flavor and decrease consumer liking in a range of foodstuffs, often generating off-aroma compounds through degradation of proteins and lipids. Existing literature has investigated the chemosensory effects of light intensity, wavelength and duration of illumination on photooxidation - particularly for the fluorescent lighting common to retail locations, and often in combination with the initial properties of the food (ie protein/fat/vitamin/antioxidant content). These studies have led to recommendations for foodstuff storage to avoid quality loss. In recent years, LED display cases and overhead lighting have begun to replace conventional fluorescence lighting in retail markets, but little research exists to determine the potential of LED lights to damage foods, and whether knowledge derived from studies of fluorescent light and foodstuffs can be extrapolated to LEDs. My group has recently observed that LED and fluorescent light damage lead to off aromas that can be differentiated sensorially from those originating from fluorescence. The central hypothesis to this proposal is that photo-induced damage caused by modern LED lighting proceeds through a different pathways than for previously studied fluorescent lighting, resulting in altered off-aroma formation, thus necessitating different intervention strategies. We propose to investigate the conditions influencing LED light-induced degradation of foods in the modern marketplace, the mechanism responsible, and evaluate possible interventions, to safeguard food quality.Due to interest in energy and cost savings, retailers are increasingly replacing fluorescent bulbs with LED bulbs, but the consequences to food quality are not yet understood. The overarching goal of the study is to examine the effects of LED light damage on foods, and to assess available interventions to alleviate this damage. Our hypothesis is that photo-induced damage caused by modern LED lighting proceeds through a different pathways than for previously studied fluorescent lighting, resulting in altered off-aroma formation, thus necessitating different intervention strategies. Empirical recommendations for LED exposure limits will be developed using human sensory testing, color measurements, and nutrient analyses. Interpreting the mechanism responsible for differences will be accomplished through evaluating change in volatile profiles. Intervention strategies previously developed for fluorescent lights, including active packaging and antioxidant supplementation, will then be appraised. Finally, consumer testing will evaluate the efficacy of interventions on improving overall liking, and perceived food quality.
Animal Health Component
0%
Research Effort Categories
Basic
25%
Applied
75%
Developmental
(N/A)
Goals / Objectives
Objective 1: Characterization of the onset of damage from LED light: Time-intensity thresholds for the effects of fluorescent light have been determined for several foods, with consumers detecting differences in certain foods resulting from photo-oxidation after less than 2 hours of illumination. Modern point-of-sale locations are switching to LED light due to lower operational costs, but recommendations for exposure limits to avoid LED light-induced changes in flavor, color, or loss of photosensitive compounds (e.g. riboflavin, vitamin E) is still lacking.Hypothesis: Due to their inherent difference, a safe exposure time for food in LED lights exists but cannot be predicted from previous research on fluorescent lights.Objective 2: Diagnosis of the associated sensory and chemical products formed by LED light exposure, when compared to fluorescent: Understanding the differences between LED and fluorescent light damage to foods requires quantitative study in both sensory and chemical domains. We will assay soybean oil and skim milk samples following light exposure by sensory, volatile, and nutritional analyses, to rationalize changes induced by differing light sources.Hypothesis: Volatile production patterns differ among light treatments (LED vs. fluorescent), and can be correlated to sensory off-aromas in exposed samples.Objective 3: Intervention to determine conditions capable of preventing damage from LED illumination: In recent years, several advanced packaging materials have been demonstrated to protect in varying degrees from fluorescent light degradation. Likewise, antioxidant supplementation has proven somewhat effective in protecting against light damage in various foods. We will investigate the efficacy of active packaging, and antioxidant enrichment, in protecting both soybean oil and skim milk from LED light damage.Hypothesis: Optimal strategies for protecting food from LED photo-oxidation through the use of additives or active packaging will differ from optimal strategies previously developed for fluorescent light due to spectral differences between LED and fluorescent lighting.
Project Methods
Threshold testing of LED light-induced damage in skim milk and soybean oil.The threshold of detection of LED light damage will be assayed in both skim milk and soybean oil, with and without antioxidant protection. As part of the preliminary data for this project, the threshold of skim milk was attained, as detailed below.Fluid milk samples were obtained from the Cornell Dairy plant (as with all future dairy samples), from the same production run, processed 7 days before sample testing. Control samples were stored protected from light to prevent further exposure of control samples beyond the production run. Samples were stored at 4°C in half-gallon HDPE containers. During exposure, LED lights generated an intensity of 2000 lux ± 100 lux on the surface of the containers. Samples were placed with the label rotated 90° clockwise from facing forward to maximize the surface area exposed to the light.Colorimetry.Light exposure is also capable of altering the visual aspect of foods. Milk exposed to direct sunlight can turn brown due to the breakdown of milk proteins (Toba et al, 1980). A study by Mestdagh et al (2005) found that milk samples exposed to 2500 lux fluorescent lighting, and stored to simulate the conditions in a supermarket or consumer's home change color dramatically, becoming less yellow and more red. It was hypothesized that the color change was caused by the degradation of riboflavin, which is yellow-green colored, β-carotene and vitamin A molecules (Mestdagh et al, 2005).Samples will be evaluated using a Macbeth Color-eye with Hunter Lab scaling. Before testing the samples will be heated to 25°C in a water bath. All samples will be measured in duplicate, and the resultant L*, a* and b* values calculated from the mean of the two trials. In preliminary experiments, an almost linear scaling of a* and b* values followed exposure time.Descriptive analysis of skim milk and soybean oil following LED and fluorescent light exposure Our lab has performed many descriptive analysis projects using sensory data, such as that in preliminary data above. In preliminary studies, we assayed the comparative effects of fluorescent and LED light exposure, when compared to non-exposed controls (see Figure 2) to demonstrate that these classes of illumination produced a different sensory profile, and to establish the feasibility of this approach. Descriptive analysis was conducted with skim milk, sourced from the Cornell dairy plant and stored at 3°C in half-gallon HDPE containers. Exposure duration was 8 hours, at an intensity of 2000 lux ± 100 lux for both light categories. Samples were evaluated under low-level lighting. Trained panelists were recruited from Cornell University. Future studies would use a standard panel size of 10, trained for 40 hours.Panelists in the 2 planned descriptive analysis studies will be trained on food specific attributes before focusing on attributes related to light-exposed flavor, such as hay/grain, old oil, mushroom, plastic and nutty aromas; and burnt and cabbage tastes. Training is conducted using Compusense At-Hand feedback calibration, on iPad minis (Findlay et al, 2007), with constant tracking of progress, and individual training for any panelist who displays inconsistencies. Panelists evaluate 6 samples per session, in partitioned booths in multiple sessions over several days (one morning and one afternoon session). Thus the 12 samples for soybean oil studies would require 4 sessions to allow for replicated evaluations of each sample from each panelist. In milk samples, there will be a total of 32 samples, thus 11 sessions will be planned, with re-training in between sessions. Panelists will rate the visual, aromatic, taste, mouthfeel, aftertaste and residual qualities of milk samples, and the visual, and aromatic properties of soybean oils. Each category includes a write-in attribute to prevent dumping of positive or negative percepts into incorrect categories. After each evaluation participants are given a mandatory break where advancing the test is not possible and instructed to cleanse their palate with water and unsalted crackers. Sample orders are randomized for each panelist and repetition, in a complete block design, with samples served at 4-6°C. The data will be analyzed using repeated measures 2-way ANOVAs, and with a mixed model with correction for multiple comparisons, in IBM SPSS.Nutritional analyses of milk samples: Vitamin and mineral analyses in milk samples will be performed by an external food testing lab (Eurofins) using AOAC methods. Vitamin A (AOAC 974.29) and riboflavin (AOAC 974.65) will be measured colorimetrically. Vitamin C will be analyzed by fluorimetry (AOAC 984.26). Copper and iron will be measured by ICP-AES (AOAC 2011.14) at limits of quantification (0.2 mg/L) appropriate for milk. Quotations for this service have been finalized with Eurofins, and are fully budgeted (attached).Volatile analysis of skim milk and soybean oil. The key off-aroma compounds associated photo-oxidation of milk are formed through oxidation of polyunsaturated fatty acids, and include aldehydes, ketones, alcohols, and heterocyclic compounds, 5 to 10 carbons in length. Degradation products of methionine - dimethyldisulfide (DMDS) and methional - have also been implicated. The key volatile compounds associated with photo-oxidation will be measured by the Sacks lab using a novel, recently described strategy utilizing headspace solid phase microextraction (HS-SPME) coupled to gas chromatography time of flight mass spectrometry (GC-TOF-MS) (Gomez-Cortes et al, 2012). While HS-SPME is convenient, it is often challenging to use because it suffers from severe matrix effects, i.e. changes in a food matrix following oxidation can alter SPME recovery. In the proposed work, milk or oil samples will be spiked with broad spectrum isotopically labeled standards derived from oxidized [U-13C]-linolenic or [U-13C] linoleic acid to facilitate accurate quantitative analyses (Gomez-Cortes et al, 2012). This method has previously been used by the Sacks lab for quantification of 25 lipid oxidation products (e.g. pentanal, hexanal, ethylfuran, heptadienal) with detection limits of 0.01-1 ng/g in various edible oils (Gomez-Cortes et al, 2015). DMDS and methional will also be measured by HS-SPME-GC-TOF-MS using their commercially available isotopically labeled analogues as standards. If necessary, the GC-TOF-MS can be run in two-dimensional comprehensive mode, GCxGC-TOF-MS to enhance selectivity and sensitivity, as has been demonstrated previously by the Sacks lab (Ryona et al, 2009).Consumer analysisWhile human sensory ratings are a close reflection of food quality, an even closer one arises from consumer testing. We will recruit a minimum of 150 regular consumers of fat free milk and soybean oil (in 2 separate tests) from the Cornell community, and collect a series of demographic questions, before sampling. Testing will occur in Cornell University's sensory evaluation facility, with data collected on 9-pt hedonic scales for overall and aroma liking, with JAR ratings of aroma and appearance. Data will be analyzed with IBM SPSS using a linear mixed model approach, with penalty analysis using Addinsoft's XLStat package, to rate the severity of disliking of odor, appearance, and overall quality ratings of the samples.