Using the FoodImageTM App to Assess Smart Interventions Designed to Improve Nutrition & Reduce Food Waste
Phase: NA
Conditions: Diet, Healthy
Sponsor: Pennington Biomedical Research Center

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Protocol Title: USING THE FOODIMAGETM APP TO ASSESS SMART 
INTERVENTIONS DESIGNED TO IMPROVE NUTRITION & REDUCE FOOD WASTE
PI Name: 
Corby K. Martin, Ph.D.; John W. Apolzan, Ph.D.; Pennington 
Biomedical Research Center
Co-Investigators:   Brian Roe, Ph.D., PI of the parent award at Ohio State University 
Danyi Qi, Ph.D., Louisiana State University (LSU)
Shengping Yang, Ph. D., Pennington Biomedical Research Center
Protocol Version Date:  10/27/2021
IRB Review History
This is a subcontract project with Ohio State University as the lead institution and 
Pennington Biomedical Research Center (PBRC), part of the Louisiana State University 
system, as the subcontractor who will conduct the human subjects research. PBRC will 
pursue the research outlined herein and share the resulting data with Dr. Roe at OSU 
and Dr. Qi at LSU.   
Objectives
Long-term Goals and Specific Objectives  
Our long-term goal is to simultaneously improve global sustainability, enhance national 
food security, and improve U.S. productivity through improved nutritional intake while 
improving the competitiveness of the U.S. food system by reducing U.S. household food 
waste. To reduce household food waste and improve individual nutrition, we leverage 
the FoodImageTM smartphone app 1, a novel method for measuring household food 
acquisition, food intake, and food waste decisions, to assess the efficacy of a smart 
intervention that targets food waste reduction and diet quality improvement. The 
intervention is designed to improve nutrition by offsetting intake of less nutritious foods 
with increased fresh fruit and vegetable (FV) intake while simultaneously reducing 
household food waste via strategies tailored to participating households.   
Specific objectives include using the FoodImage app in a randomized controlled trial 
(RCT), in which we will use the data collected to:
Enroll and Baseline Data Collection
N=46
Randomly Assign within Matched Pairs 
Control (N=23)
Treatment (N=23)
Info on Benefits of FV Consumption
No
Yes
Provision of Free FV Box
Yes
Yes
 
Intervention
 
Stress Management
Food Waste Reduction 
+ Replace Less Healthy 
Foods with FV
We will use the data collected to:
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(1) Test the effects of free FV provision on: (a) household food waste levels (mass/grams 
and energy/kilocalories), (b) total FV acquisition (free FV provision plus purchases post-
intervention vs. pre-intervention FV purchases), and (c) the consumption of FV (Food 
Patterns Equivalents Database, FPED). We hypothesize that free FV provision will 
increase food waste, total FV acquisition, and diet quality (increase the Healthy Eating 
Index [HEI]). We will test these hypotheses by comparing baseline and follow-up data 
from participants randomly assigned to the control condition, which features free FV 
provision and a placebo (stress management) intervention not focused on food waste. 
Exploratory analyses will examine the effects on dietary energy intake and if the freely 
provided FV replace non-FV foods in the baseline diet.
(2) Test if a smart intervention to reduce food waste and replace less healthy foods with 
FV significantly reduces post-intervention food waste compared to the control group while 
increasing FV acquisition and consumption compared to pre-intervention baseline. We 
hypothesize that this smart intervention will increase total FV acquisition and FV 
consumption compared to baseline, and these increases are not expected to differ 
significantly from control. It is further hypothesized that those receiving the smart 
intervention will significantly reduce food waste compared to controls. Exploratory 
analyses will examine the extent to which the smart intervention had the intended effect 
of replacing less healthy foods with FV consumption.
Background
The most recent Dietary Guidelines (Dietary Guidelines Advisory Committee 2015; at 
time of grant submission) 2 recommend a dietary pattern featuring greater consumption 
of FV to reduce the risk of cardiovascular disease, type-2 diabetes, some cancers, and 
obesity, whose prevention would yield numerous health and economic benefits 3. 
Despite extensive public messaging and well-documented evidence of health and 
economic benefits, only about 10% of Americans eat the recommended amounts of FV 
4 with the high cost of FV identified as one barrier to increasing FV intake 5 6.
Given that FV are the most wasted food category and that FV subsidies have regularly 
been shown to increase FV expenditures but not consistently been shown to increase 
FV intake 7 8, additional research is needed to:
·
Assess whether FV subsidies are efficiently translating program dollars into 
improved nutrition rather than into increased FV waste and
·
Develop interventions that ensure funds targeted to increase household FV 
acquisition are efficiently translated into improved diet quality.
The assembled investigative team has undertaken key activities that support our 
objectives. First, the team has used past USDA funding (2017-6702326268) to create 
and validate FoodImage, a smartphone application (app, available at the Apple App 
Store) that assists users in collecting and sending data about food acquisition and 
intake behaviors, including food waste data 1. The FoodImage app collects data for 
eating, shopping, food preparation (prep), and refrigerator/cabinet clean-out (toss) 
occasions. For each of these occasions, a photo and description is included along with 
supplemental information, including how or why an item is being thrown away and how 
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that item is being disposed of (e.g., sink disposal, compost, landfill, fed to a pet, etc.). 
This data is packaged and sent by the FoodImage app to Pennington Biomedical 
Research Center’s secure server for analysis.
The FoodImage app quantifies and efficiently captures the stream of food through a 
household, from purchase, through prep and eating occasions, to when food is 
ultimately tossed/discarded. This streamlined ‘all-in-one’ platform for data collection 
allows our team to collect and quantify household level waste while minimizing 
participant burden and leveraging the advantages of approaches that rely on food 
photography 9 10. All data collected by the FoodImage app are securely transferred to 
PBRC’s servers for analysis using existing methodology 9 10, which analyzes food 
images and estimates the quantity, energy, and nutrient content of food consumed and 
wasted, including delineation of the edible and inedible food waste proportions.
Finally, the FoodImage app, and its data collection methodology, integrates 
customizable notifications and reminders to remotely prompt participants to record data, 
resolve data collection problems, etc. These notifications and reminders utilize 
Ecological Momentary Assessment (EMA) methodology 11 to maximize data collection 
protocol adherence by reminding participants to capture and send food information at 
relevant times. This notification functionality of FoodImage can also be leveraged to 
communicate information about ongoing interventions and can facilitate adherence to 
dietary changes and strategies to reduce food waste.
Increasing household FV consumption while reducing food waste requires behavior to 
change in two overlapping domains, each of which has been the focus of considerable 
work 7 12. Current efforts to change household level behavior are often 
compartmentalized, focusing either on increasing FV consumption or reducing food 
waste, but not on the behaviors together. In doing so, existing interventions fail to 
consider the linkages between behaviors that occur in households and may affect 
positive change in one domain with negative or neutral impacts on the other domain 
(e.g., increase FV consumption but increase food waste or reducing food waste by 
limiting fresh FV consumption). Hence, it is essential to articulate any unintended 
consequences that existing programs present across these two domains and create 
interventions that simultaneously promote behavior change that advance both goals.
Methods
Study Design
We will conduct a randomized controlled trial (RCT) featuring two groups that both 
receive free boxes of FV. The box of fresh FV will contain about 40% fruit and 60% 
vegetables and be sufficient to meet 60 +5% of the household’s FV needs as 
recommended by USDA’s MyPlate. The amount of FV provision will scale in proportion 
to the size of the household as is done with SNAP benefits (as noted earlier, it is 
estimated that ~20% of participants will actually be eligible for SNAP). The groups differ 
in the intervention provided, with the treatment group receiving a smart intervention to 
reduce food waste and replace consumption of less healthy foods with FV and the 
control group receiving an intensity-matched intervention focused on an unrelated topic 
(stress management).
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Participants 
A sample of up to 46 participants from the Baton Rouge, LA area will be enrolled. Due 
to the prolonged baseline assessment, enrollment is defined as having successfully 
completed the baseline assessments and having been randomized. Thus, more than 46 
participants may begin the baseline period. We will enroll 46 participants. We anticipate 
~10% attrition post-enrollment for about 20-21 completers per group and we are 
adequately powered  with anticipated attrition.
Inclusion and Exclusion Criteria
·
Inclusion criteria include:
o
Male or female, age 18-62 years
o
Body mass index (BMI) 18.5 – 50 kg/m2, based on self-reported height 
and weight
o
Ownership of an iPhone, which the participant is willing to use for the 
study
o
Access to Apple ID, password, and email address and willing to use them
in the course of the study
o
Performs a majority of household food shopping and preparation
o
If children are present in household, all children are between 6-18 years
o
Able to meet the schedule demands for the study 
·
Exclusion criteria include:
o
Not able to use an iPhone
o
Refusal or unable to use the smartphone app to collect data in free-living 
conditions
o
Households that purchase groceries less than 1 time per week
o
More than 2 children living in the household
o
Pennington Biomedical Research Center employee
o
Unwilling to sign consent to use web screener questions for data set and 
analysis.
Recruitment
Participant recruitment will be completed by Pennington Biomedical’s recruitment core. 
Because most FV subsidy policies and programs target populations receiving SNAP, we 
will include recruitment at local food pantries to ensure an oversampling of participants 
who are likely SNAP eligible or recipients (target ~20% of participants). During the 
recruitment Web Screener, we will ask the participants the following 6 Food Insecurity 
screening questions:
1. In the last 12 months, did you ever eat less than you felt you should because there wasn’t enough 
money for food? 
2. In the last 12 months, were you ever hungry but didn’t eat because you couldn’t afford enough 
food? 
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3. In the last 12 months, did you ever cut the size of your meals or skip meals because there wasn’t 
enough money for food? 
4. In the last 12 months have you or other members of your household made a statement like, “The 
food that I bought just didn’t last, and I didn’t have money to get more.”
5. In the last 12 months have you or other members of your household made a statement like, “I 
couldn’t afford to eat balanced meals.”
If our 20% SNAP eligibility benchmark is not on target to be met, these questions will become a 
screening requirement to increase the likelihood of enrolling SNAP eligible participants. Data 
from web screener questions will be used for data analysis. 
Procedures
Prior to enrollment, participants will respond to recruitment, qualify for the study, and 
schedule a phone call with study staff. The purpose of the phone call with study staff is 
to ensure that the study is a good fit for the participant in regard to inclusion/ exclusion 
criteria, participant schedule, and other factors that may affect participant ability to 
complete the study and collect necessary data. 
At Visit 1, participants will come to PBRC and will provide informed consent. Post 
consent, the participant’s height, weight, and BMI will be measured and recorded. 
Participants will install and learn how to use the FoodImage app. They will complete a 
baseline questionnaire including questions about demographics, SNAP eligibility, and 
socioeconomic variables. They will also complete a Household Needs Survey to obtain 
the height, age, activity level and weight of household members as well as any allergies, 
intolerances, and food related restrictions in the household. They will also complete a 
Fruit and Vegetable Preference Survey (FV Preference Survey) to let researchers know 
which fruits and vegetables can be included in each household’s box. If the participant 
begins to express fatigue or the PBRC employing preforming the visit deems it 
necessary, the surveys can be sent to the participant via email through REDCap 13. 
Participants should complete the surveys within 24 hours of Visit 1 and a PBRC 
employee will follow-up with the participant if the surveys are not completed during this 
time. If a mistake is made or questions are unintentionally omitted, a PBRC employee 
will call the participant within 24 hours to collect the remaining data and/or participants 
will fill out surveys at Visit 2. Participants will also receive instruction on how to conduct 
a fridge and cabinet cleanout and how to conduct a household Fruit Vegetable 
inventory. Following Visit 1, participants will collect data in a free-living environment 
over the course of approximately 1 week. To prepare for home data collection, 
participants will be asked to clean out their fridge, freezer and cabinets of any items that 
need to be discarded. After the cleanout is conducted, the participant will complete a 
video home inventory of all fruits and vegetables including fresh, frozen, & those 
otherwise preserved. This fruit and vegetable inventory will be conducted via a Microsoft 
Teams video call with a study staff member. This video call will be recorded and stored 
for data analysis purposes. During the call, the participant will perform the home Fruit 
and Vegetable Inventory guided by the study staff member; the study staff member will 
ask probing questions to ensure all fruits and vegetables have been show. Following the 
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call, the study staff member will complete data entry for the fruits and vegetables 
inventoried on the call. Participants will also complete baseline data collection using the 
FoodImage app to record food acquisition (Shop), food prep (Prep), intake (Eat) and 
waste (Toss) for approximately 3 (24 hour) days; ideally including 1 weekend date. 
At Visit 2, participants will be randomized, as described in the analysis section, to one of 
two groups:  A Food Waste & Substitution Group (Treatment Group) or a Stress 
Management Group (Control Group). Both Groups will receive their first fruit and 
vegetable box, will complete a lifestyle interview, and will receive their first group 
specific intervention visit. 
Participants in the treatment group will meet individually with a trained coach who 
presents a set of materials that includes an introduction of food waste, ways that food 
waste can be reduced over time, and how to increase FV consumption by replacing 
consumption of less healthy foods with FV. The coach and participant then discuss the 
participant’s lifestyle, including things like typical eating, shopping, prepping, storage, 
and meal habits. They also may discuss things like the number of people in the 
household, number of shopping trips, meal planning (or lack thereof), etc. The coach 
and participant will then tailor actions to most effectively reduce food waste and 
increase FV intake. In ensuing sessions, steps are made to follow up on plans and to 
introduce new plans to reduce food waste and increase fruit and vegetable intake. 
Between these in-person sessions, the interventionist will check in with the participant to 
follow-up on their progress. These check-ins can occur via phone, video chat, etc. To 
identify ways in which such interventions can be improved and to facilitate intervention 
fidelity and internal validity, some sessions with participants will be recorded. These 
recordings will be reviewed by the study team, namely Drs. Martin, Apolzan, and Roe. 
During the first session, the coach and participant review the Survival TIPPS 
(Thriftiness, Inventory, Plan, Prepare, and Store). The coach and participant use 
specific goal setting techniques to make a plan that reduces food waste and increase 
FV intake in the immediate future (i.e., daily in the next week). The coach and 
participant will collaborate to find a technique that the participant finds logistically and 
financially feasible and efficacious (high self-efficacy) with coach support. Specific goal 
setting techniques such as SMART (Specific, Measurable, Attainable, Reward, 
Timebound) goals will be tailored to ensure that the participant has a concrete idea of 
what to do to enact the plan in their daily life. The participant then receives regular (e.g., 
three to four per week) semi-structured tips via text, email or call (based on participant 
preference); these will be modified based on gathered data and delivered to assist the 
participant in following through with plans to reduce food waste. A mid-week check-in 
will also be performed in between study visits. 
Similar to the treatment group, the control group will receive free FV boxes weekly and 
will meet with a trained coach who will present materials and coaching pertaining to 
stress management. To identify ways in which such studies can be improved and to 
facilitate intervention fidelity and internal validity, some sessions with participants will be 
recorded. These recordings will be reviewed by the study team, namely Drs. Martin, 
Apolzan, and Roe. 
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The control group’s intervention will be intensity matched to the treatment group. 
Intensity matching will be achieved by matching: the number of intervention sessions, 
the structure of the intervention, amount of amount of content in intervention sessions, 
intervention use of SMART goal setting, session length, number and type of follow up 
contacts. These intensity matching outcomes will be tracked by coaches via excel 
tracking and treatment notes to ensure treatment and control group participants receive 
a time and intensity matched intervention. 
Following randomization, coaches will check in with participants in the above outlined 
intensity matched fashion and participants in both groups will continue interactions with 
their coach on their respective interventions and will use the Food Image app to record 
food acquisition (Shop) and food waste from storage clean outs (Toss). 
Participants will return weekly for Visits 3 & 4 where they will receive FV boxes and will 
continue with intervention. 
Fruit and vegetables for visits 2-4 will be procured on Tuesday afternoons. Ideally the 
participants will come in on Wednesdays to pick up their box and receive intervention. If 
needed, the participants can come to the center on Thursday to receive their box and 
intervention. In extenuating circumstances, the box and intervention may be delivered at 
the participant’s home. If none of the previous options work, the participant may receive 
their box or intervention on Friday, but the fruit and vegetables will need to be checked 
for deterioration and replaced as needed. 
In the week following Visit 4 participants will continue intervention, consume their last 
box of fruit and veg, and will collect their follow up time point of data collection where 
they will use the FoodImage app to record food acquisition (Shop), food prep (Prep), 
intake (Eat) and waste (Toss) for approximately 3 (24 hour) days; ideally including 1 
weekend date.
The day before Visit 5, the participant will again complete a video home inventory of all 
fruits and vegetables including fresh, frozen, & those otherwise preserved. This fruit and 
vegetable inventory will be conducted via a Microsoft Teams video call with a study staff 
member. This video call will be recorded and stored for data analysis purposes. During 
the call, the participant will perform the home Fruit and Vegetable Inventory guided by 
the study staff member; the study staff member will ask probing questions to ensure all 
fruits and vegetables have been show. Following the call, the study staff member will 
complete data entry for the fruits and vegetables inventoried on the call. 
At Visit 5, participants will complete either the Food Waste Exit Survey or the Stress 
Management Exit Survey, based on their randomized group  and a final height, weight 
and BMI will be measured.
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 Schedule of Procedures  
Figure 1: The schedule of procedures is outlined below: 
Study 
Day
Visit & 
Timing
Participant Activity  
Prior to 
D -15*
 
Respond to recruitment, qualify for study and schedule study staff 
phone call. 
-15*
Study Call 
(~0.5 hours)
Call with study staff to determine if study is a good fit.
 -8*
Visit 1
(~3 hours)
Attend training @ PBRC to:  
· Provide informed consent. 
· Measure height weight and BMI.
· Complete Baseline Survey (demographics, including SNAP 
eligibility assessment, socioeconomic variables), FV Preferences 
Survey, and Household Needs Survey (self-reported 
demographics, allergies, intolerances, and restrictions for 
household members). If desired or deemed necessary by the 
participant or the PBRC employee conducting the lab visit, 
surveys may be done after the appointment via REDCap. 
· Learn how to conduct household FV inventory. 
· Install and learn how to use the FoodImage app.   
-8*
Day of* V1
Conduct a video home inventory of all Fruits & Vegetables (fresh, 
frozen, or otherwise preserved) via Microsoft Teams Call with study 
staff member.
-7 - -1*
Week* 
following 
V1
Baseline Data Collection
Use FoodImage to record food acquisition (Shop), food prep (Prep), 
intake (Eat) and waste (Toss).  
· For approximately 3 (24 hour) days (ideally including 1 weekend 
date) use FoodImage to record all food acquisition (Shop), food 
prep (Prep), intake (Eat) and waste (Toss).
Randomization within matched pairs to one of two groups:  
0
 
Visit 2 
~ +7* days 
from V1
(~ 3 hours)
Treatment Group  
Food Waste & Substitution
· Receive fruit and vegetable 
box.
· Lifestyle Interview
· Begin Intervention
Control Group 
Stress Management
· Receive fruit and vegetable box.
· Lifestyle Interview 
· Begin Intervention   
0-7*
Week* 
following 
V2
 Interventionist will check in with ppt goals and will send group 
specific nudges via participant’s preferred form of communication 
between V2 and V3. 
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 0-35*
Ongoing 
until end of 
study
Use FoodImage to record food acquisition (Shop) & food waste 
from storage clean outs (Toss); continue interacting with PBRC staff 
on respective interventions.
8*
 
Visit 3 
~ +7* days 
from V2
(~ 2 hours)
Visit PBRC to receive free box of FV and receive follow up 
intervention/reinforcement.
8-15*
Week*
 following 
V3
Interventionist will check in with ppt goals and will send group 
specific nudges via participant's preferred form of communication 
between V3 and V4.
16*
Visit 4  
~ +7* days 
from V3
(~ 2 hours)
Visit PBRC to receive free box of FV and receive follow up 
intervention/reinforcement.
16-23*
Week* 
following 
V4
Interventionist will check in with ppt goals and will send group 
specific nudges via participant's preferred form of communication 
between V4 and V5.
16-23*
Week* 
following 
V4
Follow Up Data Collection
Use FoodImage to record food acquisition (Shop), food prep (Prep), 
intake (Eat) and waste (Toss).  
· For approximately 3 (24 hour) days (ideally including 1 weekend 
date) use FoodImage to record all food acquisition (Shop), food 
prep (Prep), intake (Eat) and waste (Toss).
24*
Day before*
 V5
 Conduct a home inventory of all Fruits & Vegetables (fresh, frozen, 
or otherwise preserved)  via Microsoft Teams Call with a study staff 
member.
25*
Visit 5 
~ +7* days 
from V4
(~ 1 hour)
Visit PBRC to:
·
Complete exit survey and review ending home Fruit & 
Vegetable inventory.
·
Measure Height, Weight &BMI.
*All Study Days and Visit Timing are approximate. The exact day of a study procedure or appointment 
may vary slightly due to changes in subject or research facility schedule.
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Analysis
Data from the FoodImage app will be prepared for analysis using methods detailed in 
Roe et al. (2020) 1. Briefly, images captured through the app are viewed by PBRC’s 
nutrition staff who identify nutrient matches using Standard Reference (SR) 28 and the 
Food and Nutrient Database for Dietary Studies (FNDDS) 6.0 14 (USDA 2020b) 15 and 
estimate the mass of portions of food acquired, prepared, selected, consumed, 
returned, and discarded at each stage. Specifically, we will obtain mass (grams), energy 
(kilocalories), and macronutrients for shop, prep, eat, and toss occasions. The SR 
database provides inedible percentages. Furthermore, for all foods except raw meats 
where the SR database is used, we will obtain highly granular data. The FNDDS 
database translates whole food items into FPED values which converts each consumed 
food and beverage into the 37 USDA Food Patterns components 16. The FPED values 
are used to assist in the quantification of diet quality (HEI) and to guide healthy food 
intake patterns (e.g., the ‘five a day’ campaign to promote FV consumption). The Food 
Patterns are measured as cup equivalents for fruits and vegetables. Thus, we can 
examine the number of servings of fruits, vegetables, dairy, grains, and proteins (each 
of the food groups) consumed. Also, we will examine diet quality in relation to the USDA 
Dietary Guidelines for Americans with the HEI 17. During the two >3-day intensive 
collection windows, participants record the source, reason and destination of all food 
waste on the app, which is attached to each data point. Receipts associated with food 
acquisition, which are collected for all 28 days, are processed via Optical Character 
Reader (OCR) with resulting price data checked for accuracy by human raters.
The method proposed by Pocock and Simon 18 will be used for intervention assignment 
to minimize imbalance among factors that might be associated with outcomes of 
interest. Specifically, randomization will be adaptive according to the values of the 
Aitchison distance calculated using the following prioritized drivers of FV consumption 
and food waste: 1) the presence of children in the home vs. no children, 2) SNAP 
eligibility vs. being ineligible, and 3) the presence of a fruit tree and or garden at the 
home vs. the absence of these amenities. Greevy et al. 19the sample size required for 
achieving the same power is often reduced if factors associated with the outcomes are 
balanced among the intervention groups.
All named personnel are current in their human subject training and have significant 
experience with the IRB approval process and field experiment designs. The staff 
involved in communicating with participants are nutrition professionals who have 
Registered Dietitian Nutritionist credentials and/or a Bachelor or Masters degrees in 
nutrition.
Theory Driven Hypotheses
Our hypotheses are driven by results from Hamilton and Richards (2019) 20 analysis of 
household food waste in a stylized model featuring two categories of food that differ in 
their perishability (e.g., fresh and processed). They postulate that households choose 
Q,Y, and z to maximize utility:
u(γQ,Y) – h(γ;θ) + z, subject to I = PQ + RY 
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where Q is fresh food purchased, Y is processed food purchased, z is a numeraire 
good, 0<γ< 1 is the fraction of fresh food that is consumed (let consumed fresh food 
be X = γQ), food waste equals (1-γ)Q, θ is a food waste reduction knowledge 
variable, P is the price of fresh food, R is the price of processed food, I is 
income, and u(.) is a continuously differentiable concave utility function this is increasing 
in both fresh and processed food. It is assumed that processed food is wasted less than 
fresh food and, for simplicity, we assume processed food is fully consumed (no 
waste). h(.) is the disutility experienced reducing food waste, which is increasing in 
γ (effort expended to reduce food waste increases disutility), decreasing in θ (better 
knowledge of reducing food waste reduces disutility). 
 
Maximizing utility subject to the income constraint yields optimizing values 
of Q*, Y* and γ*. Denote the marginal cost of household food utilization 
as H = hγγ γ/hγ and the marginal utility of fresh food as F = -uxxγQ/ux > 0, where 
subscripts represent partial derivatives (e.g., hγγ = 2h(.)/γ2). Comparative statics 
conducted by Hamilton and Richards 19 reveal that reducing the price of fresh food will 
increase the demand for fresh produce and increase the amount wasted if F > γ(1 + H) 
– H, i.e., if the demand for fresh food is not too price elastic (Hamilton and Richards’ 
Proposition 2). Hamilton and Richards do not calibrate this model and also note that the 
literature features a broad array of fresh produce price elasticity 
estimates. Hence we forward: 
H1a:  FV acquisition, consumption, and diet quality will increase in the 
control group featuring a reduction in the effective price of fresh FV and 
H1b:  Food waste will increase in the control group featuring a reduction in the effective 
price of fresh FV, 
where the effective price of fresh FV is reduced via free FV provision (the pick-up site is 
centrally located with free parking and convenient for most Baton Rouge area 
residents). According to Hamilton and Richards (Proposition 1) if food waste reduction 
knowledge (θ) is increased then the amount of fresh food consumed will increase while 
the amount wasted will decline so long as F > 1 – γ, i.e., so long as demand for fresh 
food is not too price elastic.  Hence, we forward: 
H2a:  FV acquisition will increase in the treatment group featuring both a reduction in 
the effective price of fresh FV and a smart intervention to reduce food waste, 
H2b:  FV consumption will increase without increasing total energy intake and diet 
quality will also increase in relation to the control group, and 
H2c: Food waste in the treatment group will be less than food waste in the control 
group. 
Expected Outcomes 
We expect to assess whether programs that subsidized FV acquisition are efficiently 
translating program dollars into improved nutrition rather than into increased energy 
intake and increased FV waste and to develop interventions that ensure funds targeted 
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to increase household FV acquisition are efficiently translated into improved household 
nutrition. We will: 
1. Assess the impact of free FV provision on FV intake and household food 
waste production 
2. Measure the efficacy of the smart intervention 
3. Provide insights to guide future policies and interventions that target increased 
FV consumption through free or subsidized FV provision. 
We also expect to improve upon the efficiency of the FoodImage app through continual 
assessment of participant feedback and by improving the efficiency of 
image analysis and data input.   
Study Endpoints
Primary analysis objectives follow the hypotheses, which we are sufficiently powered to 
assess:
1) Quantify baseline distributions:
a. Mass (g), energy (kcals), and macronutrients (g and kcal) for 
household food waste levels, food purchasing patterns, food intake, 
and consumption of FV including beginning FV inventory, total FV 
acquisition, and total FV intake
b. FPED values, i.e. serving size, for food intake and consumption of 
FV including FV inventory, total FV acquisition, and total FV intake
c. Quantify baseline diet quality (i.e. food intake as assessed by the 
HEI)
2) Determine how the smart intervention altered:
a. Mass (grams), energy (kcals), and macronutrients (g and kcal) for 
household food waste levels, food purchasing patterns, food intake, 
and consumption of FV including FV inventory, total FV acquisition, 
and total FV intake
b. FPED values, i.e. serving size, for food intake and consumption of 
FV including FV inventory, total FV acquisition, and total FV intake
c. Quantify diet quality (i.e. food intake as assessed by the HEI)
d. Acquisition and intake of non-FV foods
e. The percent of household food waste that was FV
Secondary analysis objectives include assessing the demographic (e.g., age, 
education), household (SNAP eligibility, household size, beginning food inventories), 
and attitudinal factors (e.g., frugality, health and environmental consciousness) related 
to the primary analysis targets.
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Power analysis
Power analysis was conducted for change in the primary outcome variable (grams [g] of 
food waste) from baseline to the end of the intervention to detect significant differences 
between treatment and control groups. Following the methods of our previous study, 
waste data will be summarized and analyzed by aggregating across measurement 
days. Based on weekly data from our previous study, the participants in the group 
receiving a smart food waste reduction intervention reduced their waste at meals by 331 
g while the control group only reduced their waste by 33 g (298 g group difference), 
while the pooled standard deviation of the change in food waste between the control 
and treatment groups was 295 g, yielding an effect size of 1.01. The power to detect an 
effect size of 1.01 is 0.92 if there is no attrition (23 per group) and is 0.88 if attrition 
exceeds the 10% expectation (20 per group or 13% attrition). Given the power analysis 
is based upon an RCT that did not involve the provision of free FV, we expect effect 
sizes to be larger in the proposed study due to the presence of free FV, yielding even 
higher power than projected above.
Provisions to Monitor the Data to Ensure the Safety of Subjects 
Adverse events will be monitored at each intervention visit. The PI and his co-
investigators will review all data continuously to ensure the safety of each subject.
Withdrawal of Subjects 
Subjects may be withdrawn from the study if he/she misses study visits and will be 
notified of their withdrawal via telephone or mail. If a subject voluntarily withdraws from 
the study, no additional data will be collected and they will be considered dropouts in 
the study.
Risks to Subjects
This study involves no greater than minimal risk. The main risk is breach of 
confidentiality, and the PBRC team will work to minimize this during data collection, 
handling, and analysis.   
 
Potential Benefits to Subjects
Participants may benefit by increased awareness of their food waste behaviors.  
Setting
All research procedures will be conducted at PBRC and in participants’ natural 
environment. 
Resources Available
PBRC has all the necessary equipment needed to undertake and execute the proposed 
research project successfully.  All investigators and staff have offices or 
cubicles.  Investigator offices are each equipped with a desk, chair, filing cabinets and 
shelves, telephone with voice mail, printer, and access to a photocopier and 
fax.  Computers are equipped with software for statistics, data management, and word 
processing, and computers are connected to the PBRC mainframe with internet access 
and email access through Outlook Express.  Information Technology (IT) provides full 
technical support to all members of the faculty and staff.  PBRC has all the 
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technological equipment and staff needed to conduct the present study.  These 
information technologies assure efficient data handling and optimal communication 
among the investigators and the team.   
Compensation
Participants will be compensated $100 for successful completion of week 1 and $165 
for successful completion of the remaining 21 days (max compensation = $265). 
Participants will also receive a free fresh seasonal FV box once per week during the 
final 21 days.
Confidentiality and Provisions to Protect the Privacy Interests of Subjects 
Participants’ records will be kept confidential to the extent allowed by law. Only Drs. 
Corby Martin, John Apolzan, and Brian Roe, Danyi Qi, the Ohio State University 
research team, the Louisiana State University research team, and the PBRC research 
team will have access to the information participants provide.  Information may also be 
shared with necessary Institutional Review Boards and Offices for Human Research 
Protection (OSU Institutional Review Board, Pennington Biomedical Research Center 
IRB, LSU Institutional Review Board, and the Office for Human Research Protection 
(OHRP)). We will use an identification number rather than participants’ names on study 
records. The information participants provide will be stored on secured network drives 
and will not be identified using any personal information. 
 
Participants’ names and other facts that might identify them will not appear when we 
present this study or publish its results. The findings will be summarized and reported in 
group form. Participants will not be identified personally. All participants will have ample 
opportunity during consent and throughout the study to ask questions concerning study 
procedures. These questions will be answered promptly and fully by study staff to 
ensure participant ease. A participant may choose not to answer questions or 
participate in study procedures at any time.
Compensation for Research-Related Injury
No form of compensation for medical treatment or for other damages (i.e., lost wages, 
time lost from work, etc.) is available from the Pennington Biomedical Research 
Center.  In the event of injury or medical illness resulting from the research the 
participant will be referred to a treatment facility.  Medical treatment may be provided at 
their expense or at the expense of their health care insurer (e.g., Medicare, Medicaid, 
Blue Cross-Blue Shield, Dental Insurer, etc.) which may or may not provide 
coverage.  PBRC is a research facility and provides medical treatment only as part of 
research protocols.  Should the participant require ongoing medical treatments, they 
must be provided by community physicians and hospitals.   
Economic Burden to Subjects
There will be no study related costs to the participant with the exception of traveling to 
the PBRC for the study visits. However, use of the FoodImage app will use data from 
the participant’s cellular data plan.  Hence, it is possible that the participant would incur 
cost for this data, and this is clearly disclosed in the consent form.  
Consent Process
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All subjects participating in the study will provide written informed consent. The 
consenting process will take place in private rooms at Pennington Biomedical Research 
Center and will be conducted according to Pennington Biomedical consenting 
guidelines and practices. Participants can take the consent form home to review prior to 
deciding if they wish to enroll. All participants are free to withdraw from the study at any 
time.
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