Farm Methodology

Scope Boundary

This diagram communicates the scope boundary as aligned with the Food Loss and Waste Accounting and Reporting Standard[17]. Note that ReFED’s analysis also includes food sent to donations, although donations are not considered a destination within the Standard.

NOTES

• “Food Donation” has been added as a Destination

• “Biomaterial Processing is referred to as “Industrial Uses” in our model

• “Co/anaerobic digestion” is referred to as “Anaerobic digestion” in our model

• “Controlled Combustion” is referred to as “Incineration” in our model

• “Refuse/discards” is referred to as “Dumping” in our model

Calculations

Surplus Food Calculations

Master Surplus Equation:

Tons Never Harvested (Walk-by Fields)

+ Tons Left Behind After Harvest

+ Tons Packhouse Losses

+ Tons Unsold Buyer Rejections

-———————————————————–

= Tons Farm Surplus

In ReFED’s data model, the following calculations are repeated for every state, year, and farm produce commodity before any aggregation is done.

Table 1. Calculations Performed to Quantify U.S. Farm Surplus Food

DATA ITEM	DATA SOURCE OR CALCULATION	EXAMPLE
Acres Planted	USDA Surveys	9,500 acres of Asparagus planted in Michigan in 2021
Acres Harvested	USDA Surveys	8,900 acres of Asparagus harvested in Michigan in 2021
Acres Unharvested	= Acres Planted - Acres Harvested	= 9,500 - 8,900 = 600 acres unharvested
US Dollars Harvested	USDA Surveys[53]	$22,060,000 of Asparagus harvested in Michigan in 2021
Tons Harvested	USDA Surveys[53]	12,460 tons of Asparagus produced in Michigan in 2021
Yield Tons per Acre	= Tons Harvested / Acres Harvested	= 12,460 tons produced / 8,900 acres harvested = 1.40 tons per acre
% Maturity of Fields Never Harvested	ReFED assumption	In lieu of available data, ReFED assumed that only 50% of produce fields that are planted but never harvested reach maturity (yield produce that could be eaten) as opposed to fields that are planted but discontinued before the crop bears fruit.
Tons Never Harvested (Walk-by Fields)	= Acres Unharvested * Yield Tons per Acre * % Maturity of Fields Never Harvested	= 600 acres unharvested * 1.40 tons per acre * 50 = 420 tons never harvested
% Yield Left Behind After Harvest Farm	Case Studies[26],[25],[1],[29]	Proxy commodity: Cabbage Study: 2019 Santa Clara University 11.96% marketed yield of cabbage left behind after harvest (See Appendix A)
Tons Left Behind After Harvest	= Acres Harvested * Yield Tons per Acre * % Yield Left Behind After Harvest	= 8,900 acres harvested * 1.40 tons per acre * 11.96% left behind after harvest = 1,490 tons left behind after harvest
Tons Unharvested Total	= Tons Never Harvested + Tons Left Behind After Harvest	= 420 tons never harvested + 1,490 tons left behind after harvest = 1,910 total tons unharvested
% Processing (as opposedto Fresh Market)	USDA Surveys[53]	53.20% of Asparagus grown in Michigan in 2019 went to the processing market
% Field Packed	Public Agriculture Websites[54],[46],[6],[__citation_UC_Davis_Asparagus__],[47],[56]	According to the University of California Division of Agriculture and Natural Resources, 0.00% of Asparagus is field packed
% Packhouse Loss Rate	WWF Specialty Crop Loss Report[29]	Proxy commodity: Potatoes 14.80% losses by weight at the packhouse
Tons Sent to Packhouses	= Tons Harvested * ( 100% - % Processing ) * ( 100% - % Field Packed )	= 12,460 tons harvested * ( 100% - 53.20% processing ) * ( 100% - 0.00% field packed ) = 5,831 tons sent to packhouses
Tons Packhouse Losses	= Tons Sent to Packhouses * % Packhouse Loss Rate	= 5,831 tons sent to packhouses * 14.80% packhouse losses = 862 tons packhouse losses
% Buyer Rejection Rate	Expert Interviews	According to experts, about 2.00% of produce deliveries are rejected by the quality assurance team at buyer receiving (See Appendix C)
Tons Shipped from Packhouse	= Tons Sent to Packhouse - Tons Packhouse Losses	= 5,831 tons sent to packhouse - 862 tons packhouse losses = 4,968 tons shipped from packhouse
% of Buyer Rejections Sold via Discount Outlets	Expert interviews	Based on expert interviews, ReFED assumed that 25.00% of produce rejected by buyer quality assurance teams ends up being sold via other channels and does not get wasted.
Tons Unsold Buyer Rejections	= Tons Shipped from Packhouse * % Buyer Rejection Rate * ( 100% - % of Buyer Rejections Sold via Discount Outlets )	= 4,968 tons shipped from packhouse * 2.00% buyer rejections * (100% - 25.00% sold via discount outlets) = 74 tons unsold buyer rejections
Price per Ton	= US Dollars Harvested / Tons Harvested	= $22,060,000 harvested / 12,460 tons harvested = $1,770 per ton
US Dollars Never harvested	= Tons Never Harvested * Price per Ton	= 420 tons never harvested * $1,770 per ton = $743,595 never harvested
US Dollars Left Behind After Harvest	= Tons Left Behind After Harvest * Price per Ton	= 1,490 tons left behind after harvest * $1,770 per ton = $2,638,375 left behind after harvest
US Dollars Unharvested Total	= US Dollars Never Harvested + US Dollars Left Behind After Harvest	= $743,595 never harvested + $2,638,375 left behind after harvest = $3,381,971 total unharvested
US Dollars Packhouse Losses	= Tons Packhouse Losses * Price per Ton	= 862 tons packhouse losses * $1,770 per ton = $1,527,898 packhouse losses
US Dollars Unsold Buyer Rejections	= Tons Unsold Buyer Rejections * Price per Ton	= 74 tons unsold buyer rejections * $1,770 per ton = $131,936 unsold buyer rejections
Tons Surplus	= Tons Never Harvested + Tons Left Behind After Harvest + Tons Packhouse Losses + Tons Unsold Buyer Rejections	= 420 tons never harvested + 1,490 tons left behind after harvest + 862 tons packhouse losses + 74 tons unsold buyer rejections = 2,847 tons surplus
Tons Supply	= Tons Unharvested + Tons Harvested	= 1,910 total tons unharvested + 12,460 tons harvested = 14,370 tons supply
% Surplus	= Tons Surplus / Tons Supply	= 2,847 tons surplus / 14,370 tons supply = 19.82% surplus
US Dollars Surplus	= US Dollars Never Harvested + US Dollars Left Behind After Harvest + US Dollars Packhouse Losses + US Unsold Dollars Unsold Buyer Rejections	= $743,595 never harvested + $2,638,375 left behind after harvest + $1,527,898 packhouse losses + $131,936 unsold buyer rejections = $5,041,806 surplus
US Dollars Supply	= US Dollars Unharvested + US Dollars Harvested	= $3,381,971 total unharvested + $22,060,000 harvested = $25,441,971 supply

Cause Calculations

Master Cause Equation:

Tons Surplus due to Cause = Tons Surplus * % Loss due to Cause

Table 2. Calculations Performed to Quantify the Causes of U.S. Farm Surplus Food

DATA ITEM	DATA SOURCE OR CALCULATION	EXAMPLE
NEVER HARVESTED CAUSES
% Loss due to Cause	USDA RMA Crop Insurance[49]	Proxy commodity: “All Other Crops” was used because Asparagus acreage was relatively smaller than other commodities and was aggregated into the All Other Crops category in the USDA RMA data. See example data in Appendix D Fields never harvested (bad weather): 97.39% Fields never harvested (food safety): 0.00% Fields never harvested (market dynamics): 2.43% Fields never harvested (pests/disease): 0.00% Fields never harvested (other): 0.18%
Tons Surplus due to Cause	= Tons Never Harvested * % Loss due to Cause	Fields never harvested (bad weather): = 420 tons never harvested * 97.39% = 409 tons Fields never harvested (food safety): = 420 tons never harvested * 0.00% = 0 tons Fields never harvested (market dynamics): = 420 tons never harvested * 2.43% = 10 tons Fields never harvested (pests/disease): = 420 tons never harvested * 0.00% = 0 tons Fields never harvested (other): = 420 tons never harvested * 0.00% = 0 tons
US Dollars Surplus due to Cause	= US Dollars Never Harvested * % Loss due to Cause	Fields never harvested (bad weather): = $743,595 never harvested * 97.39% = $724,187 Fields never harvested (food safety): = $743,595 never harvested * 0.00% = $0 Fields never harvested (market dynamics): = $743,595 never harvested * 2.43% = $18,076 Fields never harvested (pests/disease): = $743,595 never harvested * 0.00% = $0 Fields never harvested (other): = $743,595 never harvested * 0.18% = $1,331
LEFT BEHIND AFTER HARVEST CAUSES
% Loss due to Cause	Farm Case Studies[26],[25]	Proxy commodity: Cabbage See example data in Appendix E Study: 2018 NC State 34.77% Left behind after harvest (inedible) 2.28% Left behind after harvest (marketable) 62.94% Left behind after harvest (not marketable) Total = 100%
Tons Surplus due to Cause	= Tons Left Behind After Harvest * % Loss due to Cause	Left behind after harvest (inedible): = 1,490 tons left behind after harvest * 34.77% = 518 tons Left behind after harvest (marketable): = 1,490 tons left behind after harvest * 2.28% = 34 tons Left behind after harvest (not marketable): = 1,490 tons left behind after harvest * 62.94% = 937 tons
US Dollars Surplus due to Cause	= US Dollars Left Behind After Harvest * % Loss due to Cause	Left behind after harvest (inedible): = $2,638,375 left behind after harvest * 34.77% = $917,482 Left behind after harvest (marketable): = $2,638,375 left behind after harvest * 2.28% = $60,275 Left behind after harvest (not marketable): = $2,638,375 left behind after harvest * 62.94% = $1,660,617
PACKHOUSE LOSS CAUSES
% Loss due to Cause	WWF Specialty Crop Loss Report[29]	Proxy commodity: Tomatoes See example data in Appendix F 77.00% Packhouse losses (inedible) 23.00% Packhouse losses (not marketable) Total = 100%
Tons Surplus due to Cause	= Tons Harvested but Not Sold * % Loss due to Cause	Packhouse losses (inedible): = 862 tons packhouse losses * 77.00% = 664 tons Packhouse losses (not marketable): = 862 tons packhouse losses * 23.00% = 198 tons
US Dollars Surplus due to Cause	= US Dollars Harvested but Not Sold * % Loss due to Cause	Packhouse losses (inedible): = $1,527,898 packhouse losses * 77.00% = $1,176,481 Packhouse losses (not marketable): = $1,527,898 packhouse losses * 23.00% = $351,416
BUYER REJECTIONS
Tons Unsold Buyer Rejections	See calculation above for Tons Unsold Buyer Rejections	= 74 tons unsold buyer rejections
US Dollars Unsold Buyer Rejections	See calculation above for US Dollars Unsold Buyer Rejections	= $131,936 unsold buyer rejections

Destination Calculations

Master Destination Equation:

Tons Surplus sent to Destination = Tons Surplus * % Sent to Destination

Table 3. Calculations Performed to Quantify the Destinations of U.S. Farm Surplus Food

DATA ITEM	DATA SOURCE OR CALCULATION	EXAMPLE
Destination Breakdown of Packhouse Losses	WWF Specialty Crop Loss Report[29]	This was the destinations breakdown for the packhouses included in the WWF report (See Appendix G): donations: __farm_example_packhouse_loss_destinations_percent_donations__% Animal feed: 69.67% Refuse/discards: __farm_example_packhouse_loss_destinations_percent_dumping__% ———————————————— Total: 100%
Destination Breakdown of Unsold Buyer Rejections	Expert Interviews	According to expert interviews, this is what happens to buyer rejections that don’t get sold via secondary outlets: donations: __farm_example_farm_unsold_buyer_rejections_percent_donations__% Animal feed: 33.33% Refuse/discards: __farm_example_farm_unsold_buyer_rejections_percent_dumping__% Trash: 33.33% ———————————————— Total: 100%
	% of Trash that is landfill vs incineration in Michigan (Biocycle/Columbia University Survey[41]) (See Appendix Z)	% of Trash that is landfill = 92.30% % of Trash that is incineration = 7.70%
	Breaking “Trash” into Landfill vs Incineration: % landfill = % Trash * % of Trash that is landfill % incineration = % Trash * % of Trash that is incineration	% landfill: = 33.33% * 92.30% = __farm_example_farm_unsold_buyer_rejections_percent_landfill__% % incineration: = 33.33% * 7.70% = __farm_example_farm_unsold_buyer_rejections_percent_incineration__%
Tons Not Harvested	= Total Tons Fields Never Harvested + Total Tons Left Behind After Harvest	= 420 tons fields never harvested + 1,490 tons left behind after harvest	= 1,910 total tons unharvested
US Dollars Not Harvested	= Total US Dollars Fields Never Harvested + Total US Dollars Left Behind After Harvest	= $743,595 fields never harvested + $2,638,375 left behind after harvest	= $3,381,971 total unharvested
Tons donations	Tons Packhouse Losses * % Donations for Packhouse Losses + Tons Unsold Buyer Rejections * % Donations for Unsold Buyer Rejections	= 862 tons packhouse losses * __farm_example_packhouse_loss_destinations_percent_donations__% donations + 74 tons unsold buyer rejections * __farm_example_farm_unsold_buyer_rejections_percent_donations__% donations = __farm_example_tons_donations__ tons donations
US Dollars donations	US Dollars Packhouse Losses * % Donations for Packhouse Losses + US Dollars Unsold Buyer Rejections * % Donations for Unsold Buyer Rejections	= $1,527,898 packhouse losses * __farm_example_packhouse_loss_destinations_percent_donations__% donations + $131,936 unsold buyer rejections * __farm_example_farm_unsold_buyer_rejections_percent_donations__% donations = $__farm_example_us_dollars_donations__ donations
Tons Animal Feed	Tons Packhouse Losses * % Animal feed for Packhouse Losses + Tons Unsold Buyer Rejections * % Animal feed for Unsold Buyer Rejections	= 862 tons packhouse losses * 69.67% Animal feed + 74 tons unsold buyer rejections * 33.33% Animal feed = 626 tons Animal feed
US Dollars Animal Feed	US Dollars Packhouse Losses * % Animal feed for Packhouse Losses + US Dollars Unsold Buyer Rejections * % Animal feed for Unsold Buyer Rejections	= $1,527,898 packhouse losses * 69.67% Animal feed + $131,936 unsold buyer rejections * 33.33% Animal feed = $1,108,476 Animal feed
Tons Refuse / Discards	Tons Packhouse Losses * % Refuse/Discards for Packhouse Losses + Tons Unsold Buyer Rejections * % Refuse/Discards for Unsold Buyer Rejections	= 862 tons packhouse losses * __farm_example_packhouse_loss_destinations_percent_dumping__% Refuse/Discards + 74 tons unsold buyer rejections * __farm_example_farm_unsold_buyer_rejections_percent_dumping__% Refuse/Discards = __farm_example_tons_dumping__ tons Refuse/Discards
US Dollars Refuse/Discards	US Dollars Packhouse Losses * % Refuse/Discards for Packhouse Losses + US Dollars Unsold Buyer Rejections * % Refuse/Discards for Unsold Buyer Rejections	= $1,527,898 packhouse losses * __farm_example_packhouse_loss_destinations_percent_dumping__% Refuse/Discards + $131,936 unsold buyer rejections * __farm_example_farm_unsold_buyer_rejections_percent_dumping__% Refuse/Discards = $__farm_example_us_dollars_dumping__ Refuse/Discards
Tons landfill	Tons Packhouse Losses * % landfill for Packhouse Losses + Tons Unsold Buyer Rejections * % landfill for Unsold Buyer Rejections	= 862 tons packhouse losses * 0% landfill + 74 tons unsold buyer rejections * 92.30% landfill = __farm_example_tons_landfill__ tons landfill
US Dollars landfill	US Dollars Packhouse Losses * % landfill for Packhouse Losses + US Dollars Unsold Buyer Rejections * % landfill for Unsold Buyer Rejections	= $1,527,898 packhouse losses * 0% landfill + $131,936 unsold buyer rejections * 92.30% landfill = $__farm_example_us_dollars_landfill__ landfill
Tons Incineration	Tons Packhouse Losses * % Incineration for Packhouse Losses + Tons Unsold Buyer Rejections * % Incineration for Unsold Buyer Rejections	= 862 tons packhouse losses * 0% Incineration + 74 tons unsold buyer rejections * 7.70% Incineration = __farm_example_tons_incineration__ tons Incineration
US Dollars Incineration	US Dollars Packhouse Losses * % Incineration for Packhouse Losses + US Dollars Unsold Buyer Rejections * % Incineration for Unsold Buyer Rejections	= $1,527,898 packhouse losses * 0% Incineration + $131,936 unsold buyer rejections * 7.70% Incineration = $__farm_example_us_dollars_incineration__ Incineration

Data Sources and Limitations

Planted and Harvested Acreage, Yield, and Market Price

Raw Data and Documentation:

- https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_USDASurveys_Fruit-TreeCrops.xlsx

- https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_USDASurveys_Vegetables-FieldCrops.xlsx

Each year the USDA National Agricultural Statistics Service conducts grower sampling surveys to estimate acreage, production, market price, and other data for dozens of domestically grown U.S. farm commodities. These surveys include about 60 fruit, vegetable, and nuts commodities[53]. ReFED used the data from these surveys to quantify the planted acreage (bearing acreage for tree crops), harvested acreage, market price, and yield for fruits, vegetables, and nuts by commodity, state, and year back to 2010. States that produce a minor amount of a given commodity are not included in the USDA surveys. For this reason, low-producing states are estimated to have zero food loss and waste on farms for a given commodity even though they may produce and waste a small volume. Once every four years the USDA conducts a more thorough CENSUS, which captures more acreage. ReFED compared USDA Survey and USDA CENSUS data for 2017 and 2012 and found a discrepancy of only ~5% of total national acreage for the fruits, vegetables, and nuts commodities included in this analysis.

Never Harvested (Walk-by) Causes

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_NeverHarvestedCauses.xlsx

The USDA Risk Management Agency (RMA) crop insurance claim dataset from the Federal Crop Insurance Corporation (FCIC) [49] details the total number of acres claimed as loss due to various causes by state, commodity, and year. ReFED used this data to estimate the causal breakdown of why fields are left unharvested each year by commodity and by state (see Appendix D for example data). Although market surplus or demand variation has led to spikes in “Decline in price” claims for specific commodities in certain years (e.g. cherries in 2018), the vast majority of claims are due to bad weather or natural disasters. “Decline in price” claims are much more common for lower value row crops such soybeans and corn, which were out of scope for this analysis and are therefore not reflected in the data. There is some concern that this data source may not be a representative way to quantify the percentage of produce walk-by fields that occur due to market dynamics (e.g., Decline in price claims), because many growers do not place insurance claims when this happens. However, because walk-by fields already represent such a small portion of surplus (~3%) and weather events are the dominant driver of walk-by losses, any underestimation of market dynamics that may occur becomes negligible. One important limitation of this dataset, though, is that it groups together most lower volume crops into an “All Other Crops” category. ReFED used this data and assumed that the causal breakdown of walk-by losses is the same across these lower volume crop types.

Maturity of Fields Never Harvested

ReFED was unable to identify any publicly available data sources that quantify the percentage of walk-by fields (fields that are planted and never harvested) that reach maturity or start bearing edible fruit, so this number was assumed to be 50. This number is needed to quantify the amount of yield left unharvested in these fields. ReFED used USDA Survey[53] data to quantify the number of walk-by acres by subtracting the number of acres harvested from the number of acres planted. In order to estimate the amount of yield left unharvested, average yield per acre from harvested acreage was multiplied by the estimated percent maturity and then multiplied by the number of walk-by acres.

Yield Left Behind After Harvest

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_YieldLeftBehindAfterHarvest.xlsx

Multiple university case studies from NC State[26],[25], UC Santa Clara[1], and WWF[29] were used to quantify the amount of yield that is left behind after harvest crews have finished harvesting the field. Because these were one-time studies conducted in specific geographies (e.g., California, North Carolina, Florida, New Jersey, and Idaho) for a limited number of commodities, ReFED had to use extensive proxy commodity and geography assignments to model yield left behind for all crops in all states. These estimates also had to be reused year over year for the modeling

Processing Rates Versus Fresh Market

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_PackhouseLossRates.xlsx

ReFED used data from USDA surveys[53] on processing versus fresh market tons harvested to quantify the percentage of a given commodity that was produced for the processing market in a particular state and year. ReFED used this data along with other datasets to estimate the amount of each commodity that gets sent to produce packhouses as opposed to being sent for processing in the processing market.

Field Packing Rates

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_PackhouseLossRates.xlsx

ReFED researched several prominent agriculture websites[54],[46],[6],[__citation_UC_Davis_Asparagus__],[47],[56] and consulted experts at the University of California Davis to estimate the percentage of each fresh market commodity that is packed in the field as opposed to being sent to a packhouse. Most commodities were estimated to be 0% or 100% field packed, although a few commodities were estimated to be 50-75% field packed. See Appendix B or the documentation for a detailed list. ReFED combined this data with harvest tonnages from the USDA Surveys to estimate the amount of each commodity that gets sent to produce packhouses for packing.

Packhouse Loss Rates

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_PackhouseLossRates.xlsx

ReFED used data from the WWF Specialty Crop Losses Report[29] to quantify the percent of produce packhouse volumes that are not utilized (e.g., culls or throws). For the packhouses included in the study, 14.8%, 14.2%, and 2.6% of incoming produce was culled for tomatoes, peaches, and potatoes respectively. Because this was a one-time study conducted for a limited number of commodities, ReFED had to use extensive proxy commodity assignments and reused these estimates for every U.S. state year over year for the modeling.

Before deciding on this data source for estimating packhouse losses, ReFED explored data available from USDA surveys[53] on weight of commodities not sold. This was recently added to the USDA Survey data collection process in 2016. We were unable to use this data source for the time being because this newly collected information is sparsely reported by growers to date. However, when and if growers start reporting these numbers in larger quantities, ReFED recommends using the USDA Survey data to track the amount of produce harvested but not sold (e.g., packhouse losses), because the infrastructure is already in place to get updated numbers for specific commodities and states on an annual basis for statistically significant sample sizes.

Buyer Rejection Rates

Based on expert interviews, ReFED assumed that 2.00% of all produce and nuts shipments are rejected by the quality assurance teams of produce buyers. ReFED used USDA Survey[53] production tonnages of domestically grown produce and nuts to estimate the weight of each commodity delivered to domestic buyers. In reality this overestimates buyer rejections for commodities that are heavily exported (e.g., almonds) and underestimates buyer rejections for commodities that are grown outside of the U.S (e.g., bananas). Future iterations of this model should address this issue by accounting for the impact that imports and exports have on total domestic delivery tonnages. Based on the USDA Food Availability Dataset[52] which lists production, import, and export tonnages, ReFED estimates that the current buyer rejection tonnages of Farm product in the Food Waste Monitor are about 20% underestimated for fruits and vegetables and about 180% overestimated for nuts. This issue is exacerbated for specific commodities with significant trade deficits (e.g., bananas are grown almost exclusively outside of the U.S.). However, since the current model estimates that buyer rejections only represent about 3% of total farm surplus, this issue is unlikely to have a significant impact on the overall Farm surplus numbers.

Left Behind After Harvest Causes

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_LeftBeindAfterHarvestCauses.xlsx

Only two public case studies are available that quantify the reasons why produce is left behind after harvest, both from NC State[26],[25]. More research is needed in this area, especially among tree crops as the NC State studies only looked at field crops. Because these were one-time studies conducted in North Carolina for a limited number of commodities, ReFED had to use extensive proxy commodity assignments and reuse these estimates for every U.S. state year over year for the modeling. More sustainable, continuously updated data collection methods are needed to track these causes over time going forward.

Packhouse Loss Causes

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_PackhouseLossCauses.xlsx

ReFED used data from the WWF Specialty Crop Losses Report[29] to quantify the reasons why post-harvest produce is culled. For the two commodities that included cause data in the report (peaches and tomatoes), over 75% of the produce culled in the packing houses was because it was deemed inedible (e.g., cracks, bruises, deterioration) and the remaining portion was culled because it did not meet buyer specifications (e.g., second grades). ReFED believes these numbers to be directionally correct, but more research is needed to confirm that this data is consistent across a larger sample size, different commodity types, different packhouses, geographies, and different times of the year.

Packhouse Loss Destinations

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_PackhouseLossDestinations.xlsx

ReFED used data from the WWF Specialty Crop Losses Report[29] to quantify the percentage breakdown of destinations for produce that gets culled at packhouses. ReFED believes these numbers to be directionally correct, but more research is needed to confirm that this data is consistent across a larger sample size, different commodity types, different packhouses, geographies, and different times of the year.

The portion sent to “trash” was further broken down into landfill versus incineration on a state-by-state basis using data from BioCycle’s 2010 “State of Garbage in America” survey[41], which was conducted in partnership with the Earth Engineering Center of Columbia University[8]. Because these surveys were discontinued in 2010 and no other state-level data sources exist, ReFED reused these estimates year over year to estimate the percentage of “trash” that is sent to incineration versus landfill facilities in each state

Buyer Rejection Destinations

Raw Data and Documentation:

https://refed-roadmap.s3-us-west-2.amazonaws.com/public_documentation/Documentation_Farm_BuyerRejectionDestinations.xlsx

Based on expert interviews, ReFED assumed the following destinations breakdown for produce that gets rejected by buyers: 25% sold to discount outlets, 25% trash, 25% donations, and 25% animal feed. The portion sold to discount outlets was subtracted from the surplus total. Better data is needed in this area to replace these anecdotal estimates.

The portion sent to “trash” was further broken down into landfill versus incineration on a state-by-state basis using data from BioCycle’s 2010 “State of Garbage in America” survey[41], which was conducted in partnership with the Earth Engineering Center of Columbia University[8]. Because these surveys were discontinued in 2010 and no other state-level data sources exist, ReFED reused these estimates year over year to estimate the percentage of “trash” that is sent to incineration versus landfill facilities in each state.

Data Quality Evaluation

This rubric is designed to evaluate the quality of how each data source was utilized by ReFED to estimate food loss and waste. It is not meant to rate the quality of the study itself. See Appendix AA for more information about the ReFED Data Quality Rubric.

Table 4. Data Quality Evaluation for Food Waste Monitor Farm Sector

DATA	SOURCE	DATA QUALITY SCORE
		CREDIBILITY	UPDATE FREQUENCY	COVERAGE	FOOD TYPE	GEOGRAPHY	SCORE	WEIGHT
FARM SURPLUS DATA
Acres Planted	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	2%
Acres Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	13%
US Dollars Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	13%
Tons Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	13%
% Maturity of Fields Never Harvested	ReFED Assumption	1	1	1	1	1	Very Low 5/5 = 1.0	1%
% Yield Left Behind After Harvest	Farm Case Studies	5	1	1	3	2	Low 12/5 = 2.4	40%
Processing Rates Versus Fresh Market	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	5%
Field Packing Rates for Fresh Market	Public Agriculture Websites	2	1	1	5	3	Low 12/5 = 2.4	5%
% Packhouse Loss Rates	WWF Specialty Crop Losses Report	5	1	1	2	1	Low 10/5 = 2.0	5%
% Buyer Rejections	Expert Interviews	1	1	1	1	1	Very Low 5/5 = 1.0	3%
5.0 * 2% + 5.0 * 13% + 5.0 * 13% + 5.0 * 13% + 1.0 * 1% + 2.4 * 40% + 5.0 * 5% + 2.4 * 5% + 2.0 * 5% + 1.0 * 3% = 3.52							Medium
FARM CAUSES DATA
% Loss Due to Cause for Walk-by Fields	USDA RMA Crop Insurance	5	5	5	3	5	High 23/5 = 4.6	3%
% Loss Due to Cause for Yield Left Behind After Harvest	Farm Case Studies	5	1	1	2	1	Low 10/5 = 2.0	87%
% Loss Due to Cause for Packhouse Losses	WWF Speciality Crop Losses Report	5	1	1	1	1	Very Low 9/5 = 1.8	10%
4.6 * 3% + 2.0 * 87% + 1.8 * 10% = 2.06							Low
FARM DESTINATIONS DATA
Acres Planted	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	2%
Acres Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	14%
US Dollars Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	14%
Tons Harvested	USDA Surveys	5	5	5	5	5	Very High 25/5 = 5.0	14%
% Maturity of Fields Never Harvested	ReFED Assumption	1	1	1	1	1	Very Low 5/5 = 1.0	1%
% Yield Left Behind After Harvest	Farm Case Studies	5	1	1	3	2	Low 12/5 = 2.4	42%
% of Packhouse Losses Sent to Each Destination	WWF Specialty Crop Losses Report	5	1	1	1	1	Very Low 9/5 = 1.8	9%
% of Trash landfill vs incineration	Biocycle/Columbia University Study	5	2	4	1	5	Medium 17/5 = 3.4	1%
% Unsold Buyer Rejections Sent to Each Destination	Expert Interviews	1	1	1	1	1	Very Low 5/5 = 1.0	3%
5.0 * 2% + 5.0 * 14% + 5.0 * 14% + 5.0 * 14% + 1.0 * 1% + 2.4 * 42% + 1.8 * 9% + 3.4 * 1% + 1.0 * 3% = 3.44							Medium