USING THE FOOD VARIETY SCORE TO ASSESS FOOD AND NUTRIENT WASTE IN MOROCCAN RURAL MARKETS: IMPLICATIONS FOR SUSTAINABILITY AND CIRCULAR ECONOMY

DOI: https://doi.org/10.26758/16.1.24

(1) Chouaib Doukkali University, Faculty of Sciences, Department of Biology, Research Unit on Nutrition & Food Sciences, Laboratory of Anthropogenetic, Biotechnologies and Health Road. Ben Maachou, 24 000. Morocco.

E-mails and ORCID iDs:

jamiladoc666@gmail.com, https://orcid.org/0009-0009-9546-7888

aboukhalaf.a@ucd.ac.ma, http://orcid.org/0000-0003-2654-130X

frikifirdaous@gmail.com, https://orcid.org/0000-0003-0535-2841

halimabelaoufi@gmail.com, https://orcid.org/0009-0009-5899-2122

somayaatouife@gmail.com, https://orcid.org/0009-0005-7466-8542

essaih.saloua@gmail.com, https://orcid.org/0000-0003-4530-6671

elhabazi@gmail.com

rekiabelahsen@gmail.com, https://orcid.org/0000-0002-5641-5809

(2) Ibn Tofail University, Faculty of Sciences, Department of Biology, Kenitra, Morocco.

(3) Ibn Zohr University, Faculty Polydisciplinary of Taroudant, Department of Biology, Laboratory of Biotechnology, Materials, and environment Road. Ben Maachou, 83 000. Morocco. E-mail: elamraouibelkassem@yahoo.fr, https://orcid.org/0000-0001-5864-9564

 Address correspondence to: Rekia BELAHSEN, Faculty of Sciences, Chouaib Doukkali University, Training and Research Unit on Nutrition & Food Sciences, LABS, El Jadida 24000, Morocco. Phone: 212 523 34 2325/212 664 97 16 16 Fax: 212 523 34 21 87/449 Email: rekiabelahsen@gmail.com/ rbelahsen@yahoo.com

 Abstract

 Background: Food waste in Moroccan rural markets represents a major challenge, resulting in losses not only in quantity but also in dietary and nutritional diversity. This study extends the analyses of a previous one that quantified these losses (Elbiyad et al., 2024), applying the Food Variety Score (FVS) to capture the diversity dimension of food waste and examine its potential implications for sustainable development and the circular economy.

Objective: This study aimed to assess the diversity of food and nutrients wasted in Moroccan rural markets using the Food Variety Score, and to estimate the associated nutritional, environmental, and economic implications.

Material and methods: A survey was conducted between February 2022 and March 2023 with 600 retailers in five rural markets located in the provinces of El Jadida and Sidi Bennour. At the retail level, food waste was defined as unsold items remaining at the end of the market day and considered discarded. Wasted food was identified and classified by food group and variety. Nutrient losses were estimated using Bilnut software and Ciqual food composition data, based solely on edible portions. The Food Variety Score was calculated at three levels: food group, food variety, and nutrient. Environmental impacts were estimated using coefficients published by the FAO and by Poore and Nemecek, while reduction scenarios were explored through hypothetical simulations.

Results: A total of 123 varieties of wasted food were identified and classified into six groups. Vegetables (45.7%) and fruits (27.4%) accounted for the largest share of total food waste. The Food Variety Score (FVS) reached 100% at both the group and variety levels, indicating that all identified groups and varieties were represented in the waste. Nutritionally, all nutrients studied exceeded the binary threshold used for the analysis, reflecting the diversity of nutrients present in the waste. Although the obtained values represent aggregate losses, the estimated nutrient losses were substantial but should not be interpreted as direct equivalents of individual daily intakes. The simulated reduction scenarios suggest potential environmental and economic benefits, although these projections have not been empirically tested.

Conclusion: Food waste in Moroccan rural markets is characterized by significant quantities and a wide diversity of food groups, varieties, and nutrients. Measuring the Food Variety Score provides a dimension of diversity in wasted food resources that complements conventional quantitative assessments. These results should be interpreted with caution, particularly regarding their nutritional and policy implications. Reducing food waste contributes to sustainable development and resource valorization, but requires the implementation of feasible and context-appropriate interventions.

Keywords: food waste; Food Variety Score; nutritional losses; circular economy; sustainable development; rural markets; Morocco

Suggested citation (APA):

Elbiyad, J., Aboukhalaf, A., Kalili, A., Friki, F., Belaoufi, H., Atouife, S., Essaih, S., El Amraoui, B., El Habazi, A., & Belahsen, R. (2026). Using the food variety score to assess food and nutrient waste in Moroccan rural markets: Implications for sustainability and circular economy. Anthropological Researches and Studies, 16, 354-375. https://doi.org/10.26758/16.1.24

Introduction

According to the Food and Agriculture Organization of the United Nations (FAO), approximately 14% of food produced globally is lost between harvest and retail stages (FAO, 2021). It is important to distinguish between food loss and food waste: food loss generally occurs during production, post-harvest, and processing stages, whereas food waste mainly takes place at the retail and consumption levels. Food waste is a major global concern (FAO, 2019), including in Morocco, where it has considerable implications for food security, nutrition, and sustainability. A significant proportion of food is lost or wasted at points of sale and in markets, both in urban and rural areas (HLPE, 2014).

In Morocco, particularly in rural markets locally called souks, this issue is of special concern because it results not only in losses of food quantity, but also in losses of nutritional resources embedded in wasted foods. Previous work by our group quantified the absolute amounts of food and nutrient losses in these markets (Elbiyad et al., 2024). However, that analysis did not specifically address the diversity dimension of wasted foods and nutrients. This represents an important gap, as food waste may also reflect a loss of dietary diversity, nutritional potential, and economic value.

Indeed, the composition of nutrients and bioactive compounds varies from one food to another, both quantitatively and qualitatively. Therefore, food waste is not limited to the loss of food mass, but also involves the loss of essential nutrients and potentially valuable functional compounds. According to the United Nations Food Waste Index Report, quantifying the extent of food waste is essential for catalyzing actions to reduce waste and to contribute to Sustainable Development Goal (SDG) 12.3 (Sachs et al., 2024; UNEP, 2024). Furthermore, measuring food waste helps to understand its magnitude, identify areas for reduction, and establish a baseline for monitoring progress. However, most existing assessments focus primarily on quantities of wasted food, while giving less attention to the diversity of foods and nutrients affected by these losses.

Quantifying food waste could also help assess the nutritional value lost through wasted food, taking into account the variety and diversity of the foods involved. Even within the same food group, foods differ in their nutritional composition. It is therefore essential to distinguish between food variety and nutritional quality. Indeed, food variety refers to the number of different foods represented, while nutritional quality refers to the adequacy and density of the nutrients provided. In this study, the emphasis is on diversity rather than adequacy. This distinction is essential to avoid interpreting diversity indicators as direct measures of nutritional adequacy.

The concept of food diversity is commonly assessed using indicators such as the Food Diversity Score (DDS) and the Food Variety Score (FVS). Because the manuscript previously alternated between DDS, FVS, and DVS, a consistent terminology is required. In this study, the term Food Variety Score (FVS) is used throughout to refer to the count-based indicator reflecting the diversity of distinct foods, food groups, or nutrients represented in waste and not in a diet. The FVS corresponds to the arithmetic sum of distinct items counted once, regardless of the food group to which they belong. Accordingly, the FVS is used here as an indicator of diversity and should not be interpreted as a direct measure of nutritional adequacy or dietary quality.

This score has been widely used in household and individual dietary studies, particularly in work conducted by FAO and the FANTA project (FAO, 2011). It has also been used to evaluate access to diversified diets (El-Jamal et al., 2021; Elfane et al., 2024; Moustakim et al., 2022). Although the FVS was originally developed to assess consumed diets, its application to food waste in the present study is based on the assumption that the diversity of wasted foods reflects the diversity of potentially recoverable nutritional resources. This methodological adaptation provides an additional analytical perspective beyond simple quantitative assessment; however, it should be interpreted with caution, as it represents a non-standard use of the indicator.

The objective of the present study was therefore to extend our previous quantitative assessment of food waste in Moroccan rural markets by applying the Food Variety Score to food groups, food varieties, and nutrients. More specifically, the study aimed to assess the diversity of wasted foods and nutrients in rural souks and to analyze their potential implications for nutritional resource loss, sustainability, and circular economy strategies. By integrating a diversity-based perspective, this study seeks to provide added analytical value compared with conventional weight-based assessments of food waste.

Material and methods 

1. Study Design

This study was conducted between February 2022 and March 2023 in five rural markets (souks) located in the provinces of El Jadida and Sidi Bennour, namely Tlat Sidi Bennour, Khmiss Zemamra, Had Ouled Frej, Tnin Lgharbia, and Sebt Douib. These markets were selected from 33 souks in the two provinces based on their size, location, function, and economic relevance (EESC, 2020). These criteria were used to capture major rural commercial hubs within the study area. However, the selected souks should not be considered statistically representative of all Moroccan rural markets, and the findings should therefore be interpreted within the geographical scope of the study.

The study was conducted in two phases. The first phase consisted of observational assessments aimed at identifying food waste and the types of food wasted. The second phase involved a questionnaire survey of souk traders to collect data on daily purchases, remaining quantities, and the nature and disposal of food waste. The survey was conducted over a full year, from February 2022 to March 2023, in order to account for seasonal variations in purchases, sales, and food waste patterns. This year-round design was intended to improve the temporal coverage of the data and to provide a broader picture of food waste practices in the studied souks.

2. Data Source

The questionnaire was developed based on existing literature on food waste assessment and expert consultations. It was administered face-to-face and designed to collect information on quantities purchased, quantities unsold, the fate of leftovers, and the types of food wasted. To improve clarity and content validity, the questionnaire was pre-tested with a sample of retailers, and feedback was incorporated into the final version.

Because this study adopted a comprehensive market-level approach, all food products sold in the surveyed souks were considered, rather than focusing on a single commodity category. Composite or processed foods were classified according to the product category under which they were sold by retailers and recorded in the questionnaire.

3. Data Collection

The survey involved 600 retailers and collected quantitative information on food products intended for sale across the following categories: vegetables, fruits, meat and offal, fish and seafood, bakery and cereal products, and aromatic plants. Information was collected on quantities purchased, quantities remaining unsold, the type of food wasted, and the destination of leftovers.

The questionnaire was administered in Moroccan Arabic dialect, and each interview lasted approximately 45 minutes on average. The quantities of wasted foods were primarily based on trader self-reports and expressed in the units commonly used in market practice, which were then converted into kilograms when necessary for analysis.

As a result, the dataset may be affected by recall bias and reporting bias, which could lead to either underestimation or overestimation of actual waste quantities. This limitation is acknowledged in the interpretation of the findings.

The nutritional composition of each wasted food item was estimated using Bilnut software, supplemented by values from the Ciqual food composition database, in order to estimate nutrient losses at the retail level in the rural souks studied. Only edible portions were considered. In the present study, food waste was defined as unsold food remaining at the end of the market day and considered discarded at the retail level. Nutrient losses were compared with Dietary Reference Intakes (DRIs) established by international reference sources, including World Health Organization guidelines (WHO, 2004).

4. Statistical Analyses

The identified foods were classified by food category, including vegetables, fruits, meat and offal, fish and seafood, bakery and cereal products, and aromatic plants. Quantitative data were entered into Excel files. Descriptive statistics were expressed as means ± standard deviation for continuous variables, while categorical variables were reported as frequencies and/or percentages.

Student’s t-test was used to compare the means of independent samples, while the chi-square test or Fisher’s exact test was applied to assess the distribution of categorical variables, where appropriate. All statistical analyses were performed using SPSS version 25 (IBM Corp., Armonk, NY, USA), with a significance level set at 5%.

As the primary objective of the study was to characterize the extent and diversity of food waste in the surveyed souks rather than to develop predictive models, the main statistical analyses were descriptive, and no advanced modeling approaches were employed. However, inferential tests were used only where relevant to compare distributions or group-level differences. Also, when inferential tests were conducted, the underlying assumptions of normality and independence were considered according to variable type and sample structure.

5. Calculation of Food Losses and Waste

The objective was to determine the extent of food losses and waste, corresponding to the total quantity of different categories of unsold food products considered waste in the studied souks. For each food category, the quantity of each variety within the category was estimated.

The nutritional value lost or wasted was determined based on the composition of foods present in the waste stream at the market level. The quantity of each nutrient present in these wasted foods was calculated using Bilnut software. These quantities were summed by nutrient to estimate the nutritional loss resulting from the waste of all 123 identified foods in the studied souks.

6. Food Variety Score (FVS) Calculation

To assess the diversity of food and nutrient losses in rural markets, the Food Variety Score (FVS) was calculated at three levels: food group, food variety, and nutrient. For consistency throughout the manuscript, the term FVS was used in all sections, replacing any inconsistent use of alternative terminology. This approach was intended to quantify the diversity dimension of food waste and to complement the quantitative assessment of wasted mass.

A comprehensive list of the 123 food varieties wasted during souk days was established and classified into six food groups: vegetables, fruits, fish and seafood, meat and offal, aromatic plants, and bakery and cereal products. This list served as the basis for the calculation of the FVS at the three analytical levels.

A FVS value of 100% indicates complete representation of categories within the waste stream but does not provide information on the relative importance, balance, or nutritional contribution of each component.

a. Food Variety Score at the Food Group Level (FVS_FG)

The FVS_FG was calculated using a binary indicator assigned to each food group according to the presence or absence of at least one wasted food item.

Binary indicator by group = 1 if one or more foods in the group were wasted, and 0 if no foods in the group were wasted.

Calculation:

FVS_FG (%) = (∑ FG indicators / total number of food groups) × 100

This binary approach captures whether a food group is represented in the waste stream, but it does not account for the magnitude of waste within each group.

b. Food Variety Score at the Food Variety Level (FVS_FV)

The FVS at the food-variety level measures the diversity of specific food varieties represented in waste. It corresponds to the conventional use of a variety score by summing binary indicators assigned to each distinct food variety, regardless of food group.

Calculation:

Binary indicator by variety = 1 if the variety was wasted, and 0 if not.

FVS_FV (%) = (∑ FV indicators / total number of food varieties) × 100

Although this adaptation follows the logic of traditional dietary variety assessment, its use in a food-waste context constitutes a methodological extension and should be interpreted as an indicator of diversity presence rather than of quantity or adequacy.

c. Food Variety Score at the Nutrient Level (FVS_N) and Nutrient Loss Rate

In this study, nutrient-related diversity losses were assessed using a nutrient-level Food Variety Score (FVS_N). This score reflects the proportion of essential nutrients significantly represented in the waste stream based on a binary classification approach.

The binary approach was selected to ensure comparability across heterogeneous food categories and to facilitate the interpretation of diversity patterns. However, it does not capture quantitative differences in nutrient losses and may therefore overestimate the apparent breadth of nutrient representation. The method was inspired by the criterion proposed by Kennedy et al. (2011), according to which a food may be considered a source of a nutrient if it provides at least 15% of the relevant dietary reference intake (DRI). Applied to food waste in this study, a nutrient was considered significantly represented when the total amount lost reached at least 15% of its DRI.

Each nutrient was assessed individually as follows:

– if wasted quantity ≥ 15% of the DRI, score = 1

– if wasted quantity < 15% of the DRI, score = 0

The final FVS_N was calculated as follows:

FVS_N (%) = (∑ nutrient indicators / total number of nutrients considered) × 100

This score highlights how many essential nutrients are represented in food waste. However, because it is based on a binary threshold, it reflects nutrient diversity rather than nutritional adequacy and may overestimate the apparent breadth of nutritional loss.

In addition, the extent of nutrient losses was expressed relative to DRIs using the following formula:

Nutrient loss rate or FVS_N (%) = (amount of nutrient wasted / DRI) × 100

This calculation was used as an auxiliary indicator to express the relative scale of aggregated nutrient losses. It was not used to calculate FVS_N itself. The resulting values should be interpreted cautiously, because they reflect aggregated losses and do not correspond to actual daily intakes at the individual level.

d. Environmental Impact Assessment

Greenhouse gas emissions, expressed as kg CO₂-eq/kg, were estimated using emission factors adopted for each food commodity by FAO (2013) and Poore and Nemecek (2018), as follows:

0.5 kg CO₂-eq per kilogram for vegetables;

1.1 kg CO₂-eq per kilogram for fruits;

27 kg CO₂-eq per kilogram for meat;

6 kg CO₂-eq per kilogram for fish.

The water footprint was estimated as the amount of water used for the production of each food category, using category-level coefficients based on FAO data (2011), as follows:

200 liters of water per kilogram for fruits and vegetables;

15,000 liters of water per kilogram for meat;

9,000 liters of water per kilogram for fish.

These coefficients were applied at category level rather than product-specific level. Consequently, variability within categories, such as differences among meat or fish types, was not captured and may affect the precision of the environmental estimates.

e. Economic Analysis

Food losses for vegetables, fruits, meat and offal, and fish were expressed in kilograms and valued using average local market prices per kilogram. The economic value of avoided losses was estimated by multiplying quantities saved by the corresponding average prices.

The average local prices used were:

5 MAD per kilogram for vegetables;

7 MAD per kilogram for fruits;

50 MAD per kilogram for meat and offal;

70 MAD per kilogram for fish.

In addition, the transformation of unsold foods into value-added products was considered only as a conceptual circular-economy perspective and not as an empirically tested intervention within the present study. Food loss reduction scenarios were simulated at 25%, 50%, and 75% reduction levels. These scenarios were developed as hypothetical projections to illustrate the potential environmental and economic implications of food waste reduction and should not be interpreted as observed outcomes.

Results

The study results show that all food groups contribute to food waste, reflecting a high diversity of foods within the waste stream.

As shown in Table 1, a total of 123 food varieties were identified as wasted across six food categories. The most affected category was vegetables (45.7%), followed by fruits (27.4%), meat and offal (10.9%), bakery products (6.7%), fish and seafood (5.8%), and aromatic plants (3.5%). The total quantity of food waste reached 4,366.8 kg, highlighting both the magnitude and diversity of discarded food items in rural markets (Elbiyad et al., 2024).

Table 1

Food Categories, Wasted Food Varieties, Unsold Quantities, and Percentage of Total Waste (to see Table 1, please click here)

1. Food Variety Score by Food Group (FVS_FG)

The FVS_FG was calculated based on the six food groups identified in the field. All groups were assigned a value of 1, resulting in:

FVS_FG (%) = (6/6) × 100 = 100%

This result indicates that all food groups are represented in the waste stream. It reflects the presence of diversity rather than the magnitude or distribution of waste across categories.

As illustrated in Figure 1, the distribution of wasted food quantities shows that vegetables contributed 45.7% (1,995.6 kg), fruits 27.4% (1,196.5 kg), fish and seafood 5.8% (252 kg), meat and offal 10.9% (475.1 kg), aromatic plants 3.5% (155.8 kg), and bakery and cereal products 6.7% (291.6 kg).

Figure 1

Distribution of food quantities wasted according to the groups of food categories identified (to see Figure 1, please click here)

These results highlight the predominance of perishable products, particularly vegetables and fruits, in the total volume of food waste. However, all food groups contribute to the diversity of the waste stream.

2. Food Variety Score by Food Variety (FVS_FV)

Out of the 123 identified food varieties presented in Table 1, all were observed to be wasted in the surveyed souks. Therefore:

FVS_FV (%) = (123/123) × 100 = 100%

This result reflects the presence of all food varieties in the waste stream during the study period. It should not be interpreted as indicating equal distribution or similar quantities of waste across varieties.

3 Food Variety Score at the Nutrient Level (FVS_N) and Nutrient Loss Rate

In this study, nutrient-related diversity losses were assessed using a nutrient-level Food Variety Score (FVS_N). This score reflects the proportion of essential nutrients significantly represented in the waste stream according to a binary approach. The method was inspired by the criterion proposed by Kennedy et al. (2011), according to which a food may be considered a source of a nutrient if it provides at least 15% of the relevant Dietary Reference Intake (DRI). Applied here to food waste, a nutrient was considered significantly represented if the total amount lost reached at least 15% of its DRI.

Each nutrient was assessed individually as follows:

– if wasted quantity ≥ 15% of the DRI, score = 1;

– if wasted quantity < 15% of the DRI, score = 0.

The final FVS_N score was then calculated as the proportion of nutrients that obtained a score of 1:

FVS_N (%) = (∑ Nutrient Indicators / Total number of nutrients considered) × 100

As presented in Table 2, all 25 nutrients studied reached or exceeded the 15% DRI threshold. Therefore, the final FVS_N score was 100%:

FVS_N (%) = (25/25) × 100 = 100%

This result indicates that all essential nutrients considered in the analysis were represented in the food waste stream. However, because this score is based on a binary threshold, it reflects nutrient diversity rather than nutritional adequacy or balanced dietary intake, and it may overestimate the apparent breadth of nutritional loss.

In addition to the FVS_N, the extent of nutrient losses was expressed relative to DRIs using the following auxiliary formula:

Nutrient loss rate (%) = (Amount of nutrient wasted / DRI) × 100

This calculation was not used to calculate FVS_N itself, but only to express the relative scale of aggregated nutrient losses. As shown in Table 2, particularly high values were observed for several nutrients, including vitamin B12, vitamin A, vitamin D, and protein. For example, vitamin A losses corresponded theoretically to approximately 477 times the daily reference intake, based on a wasted quantity of 334.09 mg and a DRI of 0.7 mg. Similarly, protein losses corresponded theoretically to approximately 120 adult daily reference intakes.

These estimates should be interpreted with caution. They represent theoretical equivalents based on aggregated nutrient losses and do not correspond to actual dietary intake or realistic consumption conditions at the individual level. Any potential nutritional benefit from recovering these resources would depend on the implementation of effective recovery systems, including food safety compliance, appropriate infrastructure, and equitable redistribution mechanisms.

Table 2

Estimated Nutrient Losses and Food Variety Score (FVS_N) Based on Daily Reference Intakes (DRIs) (to see Table 2, please click here)

The Table 2 data show that the estimated quantities of macronutrients and micronutrients wasted in rural markets were compared with Dietary Reference Intakes (DRIs). The values expressed as “times DRI” represent theoretical equivalents based on aggregated nutrient losses and should not be interpreted as actual dietary coverage or intake.

These results highlight the magnitude of nutrient losses embedded in wasted food resources, particularly for nutrients of public health interest such as protein, iron, calcium, vitamin A, and vitamin B12 (EFSA, 2011; WHO, 2020).

Regarding macronutrients, protein, carbohydrate, and lipid losses were substantial in absolute terms. For example, protein losses corresponded theoretically to approximately 120 adult daily reference intakes, while energy losses corresponded to nearly 60 adult daily reference intakes. These values indicate the scale of aggregated nutrient losses and should not be interpreted as realistic consumption scenarios.

Regarding micronutrients, high theoretical equivalents were observed for several minerals, including calcium, iron, phosphorus, and potassium. Similarly, vitamin losses were particularly notable for vitamin B12, vitamin A, vitamin C, and vitamin D. Vitamin B12 losses corresponded theoretically to 5,396 times the daily reference intake, while vitamin D losses corresponded to approximately 320 times the daily reference intake. However, these estimates remain theoretical and depend on the assumptions used to calculate nutrient losses from unsold food quantities.

4. Nutritional Implications of Food Waste

The estimated nutrient losses indicate that wasted food contains substantial amounts of nutrients of nutritional interest. Nutrients such as protein, iron, vitamin A, vitamin D, and vitamin B12 were present at high aggregated levels relative to Dietary Reference Intakes (DRIs). However, these values should be interpreted as theoretical equivalents and should not be considered as direct evidence that these losses could meet the nutritional needs of vulnerable populations. As indicated by the Table 2, all nutrients were represented in the waste stream. The Table 3 provides a selection of key nutrients extracted from Table 2 to illustrate the theoretical magnitude of these losses. For example, protein losses corresponded theoretically to approximately 120 adult daily reference intakes, while iron losses corresponded to approximately 67 daily reference intakes. Similarly, vitamin A losses corresponded to approximately 477 daily reference intakes, and vitamin B12 losses exceeded 5,000 times the daily reference intake.

These values highlight the magnitude of aggregated nutrient losses embedded in wasted food resources, which could theoretically correspond to the daily requirements of a number of adults.

Overall, these findings suggest that wasted food may represent a potential reservoir of recoverable nutritional resources. Nevertheless, any contribution to improving nutrition and public health would depend on the implementation of safe and effective recovery systems, including food safety control, adequate storage and transport infrastructure, and equitable redistribution mechanisms.

Table 3

Selected Nutrient Losses and Theoretical Equivalents Based on Dietary Reference Intakes (DRIs) (to see Table 3, please click here)

5. Economic Value of Wasted Food

As shown in Table 4, the total economic loss associated with wasted vegetables, fruits, meat and offal, and fish and seafood was estimated at 59,748.5 MAD, based on category-specific average local prices per kilogram. This estimate reflects the full value of the quantities wasted in the evaluated food categories.

It is important to clarify that the value of over 29,000 MAD reported in the simulated scenarios corresponds to the projected economic benefit of a 50% reduction in food losses, and not to the total economic loss. The total economic loss therefore refers to the complete quantity of wasted food valued using category-specific prices, whereas the 29,000 MAD estimate reflects a hypothetical partial reduction scenario.

These results suggest that food waste may represent an economic burden for vendors and a missed opportunity for income preservation, particularly in rural market contexts. However, these estimates should be interpreted as indicative values based on average local prices and not as direct measurements of individual vendor losses.

Table 4

Economic Impacts of Food Waste in the Studied Rural Markets (to see Table 4, please click here)

6. Environmental Impact of Food Waste

As presented in Table 5, the environmental analysis estimated that food waste in the evaluated categories generated approximately 16,653.65 kg CO₂-eq, corresponding to nearly 17 tons of CO₂-equivalent emissions, and 2,906,420 liters of wasted water. Most greenhouse gas emissions were associated with meat and offal waste, while fish and seafood, together with fruits and vegetables, contributed substantially to the estimated water footprint.

The environmental assessment was limited to the food categories for which emission and water footprint coefficients were available and applied in this study, namely vegetables, fruits, meat and offal, and fish and seafood. Bakery and cereal products, as well as aromatic plants, were not included in this estimation because no specific coefficients were assigned to these categories in the analytical framework used.

These estimates highlight the potential environmental burden associated with food waste in the studied rural markets. However, they should be interpreted with caution, as the calculations were based on category-level coefficients rather than product-specific life-cycle assessments.

Table 5

Environmental Impacts of Food Waste in the Evaluated Food Categories (to see Table 5, please click here)

7. Food Waste Reduction Scenarios

As presented in Table 6, hypothetical food waste reduction scenarios of 25%, 50%, and 75% were simulated to illustrate the potential quantitative implications of reducing food waste in the studied rural markets. These scenarios were exploratory and were not based on observed intervention outcomes. The simulations were intended to estimate the potential effects of food waste reduction on resource management, including possible environmental, nutritional, and economic implications.

For example, a simulated 50% reduction in vegetable waste would correspond to approximately 997.8 kg of vegetables saved, which could theoretically avoid nearly 199,560 liters of water use and about 498.9 kg CO₂-eq emissions. Similar projected gains were estimated for fruits, meat and offal, and fish and seafood.

These results should be interpreted with caution, as they are based on hypothetical reduction rates and category-level coefficients. They do not represent measured impacts of implemented recovery strategies.

Table 6

Simulated Food Loss Reduction Scenarios and Projected Quantitative Impacts by Food Category (to see Table 6, please click here)

Among the simulated scenarios presented in the Table 6, improving the Cold Chain was considered as a hypothetical scenario to reduce losses of highly perishable food products, particularly fruits, vegetables, and fish, during the souk day. Under a simulated 50% reduction scenario, losses could theoretically decrease by approximately 997.8 kg for vegetables, 598.3 kg for fruits, and 126.0 kg for fish and seafood.

These estimates are projections intended to illustrate potential reductions under improved storage and handling conditions that should not be interpreted as observed outcomes, since the feasibility of such reductions would depend on the availability of cold storage infrastructure, financial resources, technical capacity, and organizational conditions in rural markets.

Also, the redistribution of unsold food involves redirecting food that remains edible toward vulnerable families or local associations. Under a simulated 25% redistribution scenario, the recoverable nutrient quantities would theoretically correspond to approximately 1,500 g of protein and 83,500 µg of vitamin A. These values represent theoretical equivalents based on aggregated nutrient losses and should not be interpreted as actual dietary intake or effective nutritional coverage. The practical impact of redistribution would depend on food safety conditions, storage and transport infrastructure, organizational capacity, and equitable distribution mechanisms.

In addition to nutritional considerations, food waste reduction may also have environmental implications. As presented in Table 7, a hypothetical 50% reduction in food losses would correspond to reductions in greenhouse gas emissions and water use across the evaluated food categories. These estimates illustrate the potential scale of environmental benefits that could be achieved through food waste reduction. However, they are based on simulated reductions and category-level coefficients, and therefore should be interpreted carefully. Given that the water footprint associated with food losses is widely recognized as substantial (FAO, 2013), these findings further emphasize the importance of sustainable food resource management practices.

Table 7

Environmental Impacts of a Simulated 50% Reduction in Food Waste (to see Table 7, please click here)

In this study, the environmental burden associated with food losses in the evaluated categories was estimated at 2,906,420 liters of wasted water and approximately 16,653.65 kg CO₂-eq, corresponding to nearly 17 tons of CO₂-equivalent emissions. Under a simulated 50% reduction scenario, fruit losses would correspond to approximately 119,660 liters of water saved, while vegetable losses would correspond to approximately 199,560 liters of water saved and 498.9 kg CO₂-eq emissions avoided.

The highest potential reduction in greenhouse gas emissions was observed for meat and offal, with more than 6 tons CO₂-eq potentially avoided under a simulated 50% reduction scenario. These estimates are based on category-level coefficients and hypothetical reduction rates and should therefore be interpreted as indicative projections rather than observed environmental outcomes (Poore & Nemecek, 2018).

As presented in Table 8, the projected economic implications of a hypothetical 50% reduction in food losses were estimated for the main food categories, including vegetables, fruits, meat and offal, and fish and seafood. The economic value was calculated by multiplying the quantity of food potentially saved (kg) by the corresponding average local price per kilogram (MAD).

These projections suggest that improved management of unsold food could generate economic benefits. However, they should be interpreted as indicative estimates based on simulated reductions and average market prices, rather than as observed financial gains.

Reducing food losses could represent a potential economic opportunity, with an estimated value of 29,877 MAD under a simulated 50% reduction scenario in the studied markets. This value should be interpreted as a projected estimate based on average local prices rather than as an observed financial gain. From a circular economy perspective, unsold food could potentially be transformed into value-added products, such as soups, juices, or canned preparations. However, the feasibility of such valorization would depend on food safety requirements, technical capacity, market demand, and local infrastructure.

Table 8

Projected Economic Value of a Simulated 50% Reduction in Food Waste by Food Category (to see Table 8, please click here)

Discussion

The results of this study indicate that rural markets (souks) represent a significant source of food waste in both quantity and diversity, with implications at multiple levels. This work made it possible to quantify, for the first time, both the magnitude of food waste and the diversity of food groups and varieties discarded in five souks in the provinces of Sidi Bennour and El Jadida.

The estimated losses correspond to aggregated values over the study period and should not be interpreted as actual dietary intake at the individual level. Rather, they reflect the scale of food and nutrient resources embedded in the waste stream. In this context, food waste may be considered as a potential reservoir of recoverable resources, although its effective utilization would depend on appropriate recovery, safety, and redistribution systems.

1. Nutritional and Public Health Implications

The findings highlight important inefficiencies in food resource management in Morocco, a context where nutritional challenges persist. According to FAO estimates, undernourishment affects approximately 5.6% of the population, while stunting remains prevalent among children under five (FAO, 2021). These data emphasize the need for improved food system efficiency and resource utilization.

The analysis of nutrient losses revealed substantial quantities of nutrients embedded in wasted food, including iron, vitamin A, iodine, and protein. These values, however, represent aggregated estimates and should be interpreted as theoretical equivalents rather than direct nutritional coverage.

For instance, the estimated daily iron losses correspond to approximately 945.9 mg, which is equivalent to several times the daily requirement of an adult woman. Similarly, iodine losses were estimated at 4.56 mg, corresponding to values exceeding daily reference intakes. However, these figures do not reflect actual intake conditions and should be interpreted as indicators of magnitude.

In Morocco, national strategies such as food fortification programs (e.g., wheat flour enrichment with iron and B vitamins, and universal salt iodization) have been implemented to address micronutrient deficiencies (GAIN, 2014; UNICEF, 2024). In this context, the presence of nutrient-rich foods within the waste stream may represent a missed opportunity for resource utilization rather than a direct cause of nutritional deficiencies.

The relationship between food waste and nutritional outcomes remains indirect and should be interpreted with caution, as dietary intake is influenced by multiple socio-economic, cultural, and logistical factors. Therefore, while the results highlight the potential availability of nutrients within wasted food, any contribution to improving nutritional status would depend on the implementation of effective systems, including food safety compliance, adequate infrastructure, and equitable redistribution mechanisms.

2. Economic Consequences and Recovery Strategies

Food waste represents a potential economic burden in rural markets, as it corresponds to lost products that could otherwise contribute to income generation. Under a simulated 50% reduction scenario, the estimated economic value of recoverable food was approximately 29,877 MAD. These values should be interpreted as projected estimates based on average prices, rather than as observed financial gains.

Beyond direct losses, food waste also reflects inefficiencies in resource utilization. At the global level, it is estimated that 8–10% of greenhouse gas emissions are associated with food waste (FAO, 2021), while billions of people are affected by poverty and land degradation (UN, 2024). In this context, reducing food waste may contribute to improving resource efficiency, although it should be considered as one component among broader socio-economic interventions.

Several potential strategies may be considered to reduce food waste in rural markets:

• Improving the cold chain: This could reduce the deterioration of perishable foods, particularly fruits and vegetables, which represent a major share of total losses. However, its implementation may be constrained by financial, logistical, and infrastructural limitations.
• Redistribution of unsold food: Redirecting edible food to local organizations or vulnerable populations may help reduce waste and improve access to food. However, this approach requires strict compliance with food safety regulations, governance frameworks, and logistical coordination.
• Valorization of unsold food: Transforming surplus food into value-added products (e.g., processed foods) could support circular economy approaches. Nevertheless, the feasibility of such initiatives depends on technical capacity, market demand, and regulatory conditions.

3. Environmental Challenges and Sustainability Perspectives

The environmental assessment showed that food waste contributes to greenhouse gas emissions and water resource depletion. These impacts highlight the environmental burden associated with inefficient food systems.

Reducing food waste could potentially contribute to improving resource efficiency and reducing environmental pressure, although this remains dependent on the implementation of effective interventions.

These findings may support the relevance of food waste reduction strategies in the context of SDG 12. Their actual contribution, however, would depend on local implementation conditions, including feasibility, governance, infrastructure, and the effectiveness of the interventions developed.

At the local level, reducing food waste may contribute to improving resource efficiency and supporting circular economy initiatives. Nevertheless, its broader socio-economic impact should be interpreted cautiously and considered dependent on context-specific operational conditions.

Conclusion

The application of the Food Variety Score (FVS) in this study provided insight into the diversity of food resources represented within the waste stream, rather than their nutritional adequacy or quality. The results show that food waste in Moroccan rural markets encompasses a wide diversity of food groups and varieties. This reflects the presence of diverse food resources and should be interpreted as an indicator of diversity rather than nutritional balance.

These findings highlight the potential value embedded in wasted food and the importance of developing targeted recovery strategies. However, options such as composting or processing into by-products were not empirically assessed in this study and should be considered as potential avenues for future application rather than evidence-based outcomes.

The results suggest that improved management of food losses could complement existing initiatives, including food fortification programs, and support sustainability and circular economy approaches. Nevertheless, these contributions remain exploratory and depend on the implementation of effective systems, including food safety compliance, infrastructure, and governance mechanisms.

In line with Sustainable Development Goals (SDGs) 2, 8, and 12, food waste reduction in Moroccan rural markets may represent one contributing lever among broader interventions aimed at improving food security and system resilience, rather than a standalone solution.

Overall, this study provides an initial application of the FVS to food waste in rural markets, highlighting the diversity dimension of losses and their potential implications. The findings are based on aggregated estimates and should not be interpreted as actual dietary intake or direct public health outcomes.

This study provides an original contribution by extending conventional food waste assessments through the integration of a diversity-based indicator. While previous research focused on quantities, this approach highlights the qualitative dimension of food waste, particularly in terms of nutrient diversity and potential resource recovery within a circular economy framework.

Limitations and Future Research

This study provides original data on food waste in rural Moroccan markets and introduces an innovative approach by integrating diversity indicators. However, several limitations should be acknowledged.

First, the study is geographically limited to two provinces, which may affect the generalizability of the findings. Second, the data are based on self-reported information from traders, which may introduce recall and reporting biases. Third, the use of a binary scoring system for the Food Variety Score may overestimate diversity, as it does not account for the magnitude of waste.

Furthermore, the application of the FVS to food waste represents a methodological adaptation, which may limit direct comparison with dietary studies.

Future research should aim to strengthen these findings through longitudinal designs, seasonal analyses, direct measurement methods (e.g., weighing), and comparative studies between rural and urban markets. In addition, further work is needed to assess the feasibility and effectiveness of food waste reduction strategies in real-world conditions.

Competing interests

The authors declare no competing interests.

Ethical Approval

Although formal ethical approval from an Institutional Review Board (IRB) was not required for this study, prior permission was obtained from local authorities.

Consent to participate

Verbal informed consent was obtained from all participating retailers, who were informed about the objectives of the study and their right to withdraw at any time if they wished.

References

1. Ardaillou, R., & Bourel, M. (2004). Contenu en sel de l’alimentation et hypertension artérielle. Bulletin de l’Académie Nationale de Médecine, 188(2), 317–329. https://doi.org/10.1016/S0001-4079(19)33805-1
2. Aujourd’hui Le Maroc. (2023, May 4). Génération Green, une stratégie efficace pour parer à l’insécurité alimentaire. https://aujourdhui.ma/economie/generation-green-une-strategie-efficace-pour-parer-a-linsecurite-alimentaire
3. Cobb, L. K., Appel, L. J., & Anderson, C. A. M. (2012). Strategies to reduce dietary sodium intake. Current Treatment Options in Cardiovascular Medicine, 14(4), 425–434. https://doi.org/10.1007/s11936-012-0182-9
4. (2020). Pour une politique de rénovation et de développement des souks hebdomadaires en milieu rural. https://www.cese.ma/media/2020/12/Souks-hebdomadaire-VF-2.pdf
5. (2017). Dietary reference values for nutrients: Summary report. https://www.efsa.europa.eu/sites/default/files/2017_09_DRVs_summary_report.pdf
6. Elbiyad et al., 2024. Quantitative and qualitative assessment of food waste in rural markets in Morocco. North African Journal of Food and Nutrition Research, 8(18), 130–139. https://najfnr.com/home/article/view/481
7. El Fane, H., Sahel, K., El-Jamal, S., Barakat, I., El Ayachi, M., & Belahsen, R. (2024). Association of newborn low birth weight and maternal diet quality during pregnancy: A case-control study in El Jadida province. Mediterranean Journal of Nutrition and Metabolism, 17, 93–105. https://doi.org/10.3233/MNM-230040
8. El-Jamal, S., Mziwira, M., Elfane, H., Sahel, K., Barakat, I., Kalili, A., Naciri, K., Mahri, N., Moustakim, R., El Ouafi, R., Arkoubi Idrissi, L., & Belahsen, R. (2021). Association between food insecurity and obesity in an agricultural community of women from El Jadida, Morocco. AIMS Medical Science, 8(3), 175–188. https://doi.org/10.3934/medsci.2021016
9. (2011). Guidelines for measuring household and individual dietary diversity. https://www.fao.org/fileadmin/user_upload/wa_workshop/docs/FAO-guidelines-dietary-diversity2011.pdf
10. (2012). Global food losses and food waste: Extent, causes and prevention. https://www.fao.org/3/i2697e/i2697e.pdf
11. (2013). Food wastage footprint: Impacts on natural resources. https://www.fao.org/3/i3347e/i3347e.pdf
12. (2019). The State of Food and Agriculture 2019: Moving forward on food loss and waste reduction. https://www.fao.org/3/ca6030en/ca6030en.pdf
13. (2020). Fortification of foods. https://faolex.fao.org/docs/pdf/gam233064.pdf
14. (2021). Food Loss and Waste Database. https://www.fao.org/platform-food-loss-waste/en/
15. (2022). The State of Food Security and Nutrition in the World. https://www.fao.org/3/cc0639en/cc0639en.pdf
16. FAO, IFAD, UNICEF, WFP, & WHO. (2021). The State of Food Security and Nutrition in the World 2021. https://doi.org/10.4060/cb4474en
17. (2014). Statistical yearbook 2014: Near East and North Africa. https://www.fao.org/3/i3591e/i3591e.pdf
18. FANTA Project. (2011). Guidelines for measuring household and individual dietary diversity. https://www.fantaproject.org/sites/default/files/resources/HDDS_v2_Sep06_0.pdf
19. (2015). Daily values for nutrients. https://www.fda.gov/food/nutrition-facts-label/daily-value-nutrition-and-supplement-facts-labels
20. (2014). Annual report 2014–2015. https://www.gainhealth.org/sites/default/files/financial_statements/financial-statements-2014-2015.pdf
21. (2014). Food losses and waste in the context of sustainable food systems. https://www.fao.org/3/i3901e/i3901e.pdf
22. (1997). Dietary reference intakes for calcium, phosphorus, magnesium, vitamin D, and fluoride. National Academies Press.
23. Kennedy, G., Ballard, T., & Dop, M. (2010). Guidelines for measuring household and individual dietary diversity. FAO.
24. Moustakim, R., El Ayachi, M., Mziwira, M., & Belahsen, R. (2022). Dietary diversity score and chronic kidney disease in Moroccan adults. Annals of the National Institute of Hygiene, 73(3), 1–9. https://doi.org/10.32394/rpzh.2022.0221
25. (2020). Vitamin D: Fact sheet for health professionals. https://ods.od.nih.gov/factsheets/VitaminD-HealthProfessional/
26. (2021). Dynamiques des niveaux de vie et de la pauvreté au Maroc. https://www.ondh.ma
27. (2023). Office National Interprofessionnel des Céréales et des Légumineuses.
28. Poore, J., & Nemecek, T. (2018). Reducing food’s environmental impacts through producers and consumers. Science, 360(6392), 987–992. https://doi.org/10.1126/science.aaq0216
29. (2024). National multisectoral nutrition strategy 2024–2030. https://www.unicef.org/morocco/media/4201/file/RAPPORT_UNICEFMAROC_2024.pdf.
30. Ruel, M. T. (2003). Operationalizing dietary diversity. The Journal of Nutrition, 133(11), 3911S–3926S. https://doi.org/10.1093/jn/133.11.3911S
31. Sachs, J. D., Lafortune, G., & Fuller, G. (2024). Sustainable Development Report 2024. https://doi.org/10.25546/108572
32. (2024). Food waste index report 2024. https://www.unep.org/resources/publication/food-waste-index-report-2024
33. United Nations. (2024). Global poverty and land degradation report. https://news.un.org
34. (2001). Iron deficiency anaemia: Assessment, prevention and control. https://www.who.int/publications/i/item/WHO-NHD-01.3
35. (2004). Vitamin and mineral requirements in human nutrition (2nd ed.). https://www.who.int/publications/i/item/9241546123