Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Well-written and detailed article (sometimes too detailed, especially in the introduction) describing an interesting and innovative study on Kenyan school meals. 

The study is well-supported, and the discussion is engaging. 

I have a few comments, mainly on formatting and style.

Abstract :

1. Please precise the age range of the children (2-18).

Introduction:

2. Your introduction is well-written and well-documented. Although it is interesting, it should be more concise for a research paper. For example, I suggest simplifying the historical background from lines 47 to 82 or 118 to 129 and prioritizing  what is currently in place. From by point of view, lines 130 to 148 would be more appropriate in the discussion section to address the limitations implementation of local foods in the school meals.

3. Line 150 “this study used a linear programming tool to calculate” - please precise the name of the tool (I assume it is World Food Programme's School Meal Planner (SMP) PLUS software?)

4. Lines 151-154 I’m not familiar with the practice of revealing results in the introduction. Typically, the introduction should state the objective and briefly outline the method. However, if the other reviewers have not raised this issue, I am open to accepting it.

Materials and Methods :

5. Line 191-192: “Selecting the study school was considerably more complicated than the NUS selection” - This type of subjective assertion might not be suitable in a scientific context. Clarifying the specific challenges faced in the school selection process is sufficient.

6. Lines 243-244 : “The ration per person was then calculated by dividing the total quantity of ingredients by the number of beneficiaries”- Is the ration served per person always the same, or did you simply calculate an “average” ration per person?

7. Line 246: How was the 30% threshold established ? Is it also part of the national guidelines ?

8. Line 257-259: “In automatic mode, the software's algorithm generates the most cost-effective and nutrient-dense meals based on several configurable parameters, as used in the three optimization scenarios” - do you know the name of the algorithm used by the tool ? Is it the simplex algorithm used for linear programming ?

9. Line 259-260: Do you have the details of the nutrient targets (which nutrients are considered?), as well as the food groups and item rules ?

10. Line 262-266: in the second and third optimization, does this mean that “plant-based foods” and “all food items” comes from food items already available to VFA + food items included in the SMP PLUS software ? Please clarify it. Also, ensure consistency in terminology by replacing “plant-based foods” with “plant-based food items.”

Results:

11. Line 279 “the results are presented below.” and line 317 “as shown below”- please specify the table or figure number instead of  suing“below”

12. Lines 281-304: The baseline menu should not be included of the result section but rather moved to the Materials and Method section.

13. Figure 4 and 5: The charts would be more understandable if the legend for light green were replaced with “NUS” contribution” and dark green with “other foods contribution”, as stated in the figure caption. Additionally, the charts shows only optimized daily requirements : would it be possible to also display the mean baseline menu (BL average) ?

Discussion :

14. Did you consider the acceptability of such changes ? For example, spinach increased by 160% in BL sub-optimal +. Or is it restricted by a potential practical constraints on the maximum allowable quantity of food items in the SMP PLUS software ?

15. You could add a limitation regarding bioavailability. The bioavailability of nutrients such as iron or zinc, which may be lower in the first and second optimizations compared to the third optimization, which includes ASF.

Conclusion :

16. I'm not sure how Annex 3 fits into the conclusion. Wouldn't it be more appropriate to mention it in the discussion section?

17. Line 567-569 : This should be in the Materials and Method section, as it also addresses the question I raised in point 7.

18. Line : 570-571 : This should also be placed in the discussion section.

Author Response

Comment 0: Well-written and detailed article (sometimes too detailed, especially in the introduction) describing an interesting and innovative study on Kenyan school meals.
The study is well-supported, and the discussion is engaging.
I have a few comments, mainly on formatting and style.
Response 0: Thank you very much for your kind words and suggestions. Please see our responses to your comments below. 

Abstract:
Comment 1: Please precise the age range of the children (2-18).
Response1 : The school children’s age has been specified and added to the Abstract.

Introduction:
Comment 2: Your introduction is well-written and well-documented. Although it is interesting, it should be more concise for a research paper. For example, I suggest simplifying the historical background from lines 47 to 82 or 118 to 129 and prioritizing what is currently in place. From my point of view, lines 130 to 148 would be more appropriate in the discussion section to address the limitations implementation of local foods in the school meals.
Response 2: Thank you for your comment. Following your suggestion, lines 47-82 and 118-129  have been summarized, shortened and simplified, but left in the respective sections as they add context to the neglect of NUS over time.

Comment 3: Line 150 “this study used a linear programming tool to calculate” - please precise the name of the tool (I assume it is World Food Programme's School Meal Planner (SMP) PLUS software?)
Response 3: Thank you. We have specified the name of the tool (now lines 231-232).

Comment 4: Lines 151-154 I’m not familiar with the practice of revealing results in the introduction. Typically, the introduction should state the objective and briefly outline the method. However, if the other reviewers have not raised this issue, I am open to accepting it.
Response 4: We appreciate your comment and have removed an overview of the results from the Introduction.

Materials and Methods:
Comment 5: Lines 191-192: “Selecting the study school was considerably more complicated than the NUS selection” - This type of subjective assertion might not be suitable in a scientific context. Clarifying the specific challenges faced in the school selection process is sufficient.
Response 5: We agree that this was a subjective perspective. We have revised the sentence (now lines 178-180 ) as follows: “The school selection criteria were limited to identifying a school that: a) had fully resumed operations following the COVID-19 pandemic; b) provided daily school meals; and c) was willing to participate by sharing its menu plans.” 

Comment 6: Lines 243-244 : “The ration per person was then calculated by dividing the total quantity of ingredients by the number of beneficiaries”- Is the ration served per person always the same, or did you simply calculate an “average” ration per person?
Response 6: For simplicity, we calculated an average ration per person irrespective of age. This remains consistent, based on the total provision of ingredients and the number of beneficiaries. We have amended the text, which now reads: “The per-person ration was determined by dividing the total quantity of ingredients by the number of beneficiaries, regardless of age” (lines 229-230).

Comment 7: Line 246: How was the 30% threshold established? Is it also part of the national guidelines?
Response 7: Yes, the 30% threshold was established by the national school feeding guidelines. We thus amended the sentence to include the following information: “established by the national school feeding guidelines” (line 233). Why and how the Ministry of Health of Kenya determined this threshold is not known.

Comment 8: Lines 257-259: “In automatic mode, the software's algorithm generates the most cost-effective and nutrient-dense meals based on several configurable parameters, as used in the three optimization scenarios” - do you know the name of the algorithm used by the tool? Is it the simplex algorithm used for linear programming?
Response 8: Thank you for this question. Unfortunately, the tool’s algorithm is not known to the authors nor is it described in the publicly available descriptions about the tool. We have thus revised the text and remained more general, including this as a study limitation and referencing the study by Padovan et al. (2023) [62] and World Food Programme [63]

Padovan, M.; de Senna, F.R.; Kimura, J.K.; Nascimento, S.T.; Moretti, A.C.; Capitani, C.D. Optimized Menu Formulation to Enhance Nutritional Goals: Design of a Mixed Integer Programming Model for the Workers’ Food Program in Brazil. BMC Nutr. 2023, 9, 51, doi:10.1186/s40795-023-00705-0.
World Food Programme (WFP) PLUS One for School Meals: Enhancing WFP’s School Feeding Programme in the Dominican Republic. Available online: https://wfpinnovation.medium.com/plus-one-for-school-meals-enhancing-wfps-school-feeding-programme-in-the-dominican-republic-699b7c0ff007 (accessed on 12 February 2025).

Comment 9: Line 259-260: Do you have the details of the nutrient targets (which nutrients are considered?), as well as the food groups and item rules?
Response 9: Thank you for your pertinent query. We have added text to explain this. The new sentence reads: “All the optimizations used consistent parameters for menu duration (5 days per week) and basic nutritional recommendations. However, the food groups and item rules assigned by the software varied based on the specific optimization performed. The nutrition rules prioritize meeting the basic nutrient requirements for non-anemic children, while the item rules govern the selection of specific items within each food group” (lines 249-250 and 252-254).

Comment 10: Lines 262-266: in the second and third optimization, does this mean that “plant-based foods” and “all food items” comes from food items already available to VFA + food items included in the SMP PLUS software? Please clarify it. Also, ensure consistency in terminology by replacing “plant-based foods” with “plant-based food items.”
Response 10: We recognize that our previous explanation in the manuscript may not have been consistent and sufficiently clear. We have replaced plant-based foods with plant-based food items. Regarding which foods were available where, two key aspects need to be considered:
1. The plant-based food items used in the baseline school menus were available at the school and were being supplied from various sources (e.g., school garden, local market, the Farm to Feed Foundation).
2. The software relies on an “ingredients list” or database that includes nutrient and cost information for plant-based food items in Kenya. The optimization procedures use this information to propose new menu plans. Any food item not included in the database cannot be considered during the optimization process.
In this study, animal-source foods (ASFs) were already present in the ingredients’ list, whereas NUS (except for amaranth) were initially absent and had to be added manually. Any “new” food items proposed during the optimization could either be cultivated in the school garden, purchased from local markets, or sourced through the Farm to Feed Foundation. Some text has been added to explain this in Lines 260-263.

Results:
Comment 11: Line 279 “the results are presented below.” and line 317 “as shown below”- please specify the table or figure number instead of using “below”
Response 11: Thank you for noting this. The figures have now been appropriately cited and the text modified.

Comment 12: Lines 281-304: The baseline menu should not be included of the result section but rather moved to the Materials and Method section.
Response 12: Thank you for this proposal. We discussed this suggestion and felt that the baseline menu description should remain in the Results section as it is the first step in our analysis, being different from any other school, and closely linked to Figure 2. We hope you can agree with our justification.

Comment 13: Figure 4 and 5: The charts would be more understandable if the legend for light green were replaced with “NUS” contribution” and dark green with “other foods contribution”, as stated in the figure caption. Additionally, the charts shows only optimized daily requirements: would it be possible to also display the mean baseline menu (BL average)?
Response 13: Thank you for this suggestion. We have added the information on the mean baseline values in Figures 4 and 5.

Discussion:
Comment 14: Did you consider the acceptability of such changes? For example, spinach increased by 160% in BL sub-optimal +. Or is it restricted by potential practical constraints on the maximum allowable quantity of food items in the SMP PLUS software?
Response 14: Yes, the acceptability of the proposed changes was considered. The SMP PLUS software enables users to set minimum and maximum portion sizes for each food item as needed. In many school meals, vegetable portions are typically small, so a 160% increase simply translates to a larger serving size that remains acceptable and within the recommendations outlined by the national guidelines.  We have revised the text accordingly and included an example of the updated portion size, which is also detailed in the Supplementary Material S3.

Comment 15: You could add a limitation regarding bioavailability. The bioavailability of nutrients such as iron or zinc, which may be lower in the first and second optimizations compared to the third optimization, which includes ASF.
Response 15: Thank you for your observation. Indeed, the second optimization may overestimate nutrient availability. We had initially referenced bioavailability in general terms within the limitations section at the end of the discussion. In response to your feedback, we have now expanded the explanation to specifically address the potential estimation bias associated with the two optimizations [see lines 494-498]. This addition clarifies how these biases could impact the accuracy of nutrient availability estimates and provides further context for the study's findings.

Conclusion:
Comment 16: I'm not sure how Annex 3 fits into the conclusion. Wouldn't it be more appropriate to mention it in the discussion section?
Response 16: Thank you for your feedback. Reference to Annex 3 has been moved to the introductory part of the Discussion.

Comment 17: Line 567-569: This should be in the Materials and Method section, as it also addresses the question I raised in point 7.
Response 17: In response to comment 7, we have revised the manuscript to mention the 30% threshold established by the national school feeding guidelines in the Materials and Methods section. Since no information is available on how this threshold was determined, we considered this a study constraint and discussed it in the Limitations section. We trust adequately responds to the comment.

Comment 18: Line : 570-571 : This should also be placed in the discussion section.
Response 18: Thank you for this suggestion. We have moved the respective section to the Discussion section (see lines 423-427). 

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for your manuscript. Here are some comments:

1.       You stated that 8 out 10 Kenyans were unable to afford a healthy diet. Can you state what they then eat?

2.       the introduction is too long, shorten it

Author Response

Comment 1: You stated that 8 out 10 Kenyans were unable to afford a healthy diet. Can you state what they then eat?
Response 1: Thank you for your query. We revised the section to emphasize the low dietary diversity commonly observed in Kenya. We follow the approach of Herforth et al., [7] who developed the Diet Quality Questionnaire to assess both dietary diversity and risk factors for diet-related non-communicable diseases (NCDs). In Kenya, diets are predominantly centered around ugali—typically made from refined maize flour—accompanied by a small portion of kale or beans and, when affordable, a small piece of meat. The diversity of these diets is influenced not only by nutritional knowledge but also by the wealth status of households. These factors underscore the limited variety and nutrient adequacy in typical Kenyan meals [4,5].

Herforth, A. (2023, November). Diet Quality Questionnaire (DQQ) Indicator Guide. Global Diet Quality Project. https://www.dietquality.org/tools

4. Liu, T.; Broverman, S.; Puffer, E.S.; Zaltz, D.A.; Thorne-Lyman, A.L.; Benjamin-Neelon, S.E. Dietary Diversity and Dietary Patterns in School-Aged Children in Western Kenya: A Latent Class Analysis. Int. J. Environ. Res. Public Health 2022, 19, 9130, doi:10.3390/ijerph19159130.
5. Gichohi‐Wainaina, W.N.; Kee‐Tui, S.H.; Zoethout, M.; Talsma, E.F.; Edel, I.; Hauser, M. Determinants of Dietary Diversity and Drivers of Food Choice among Low‐income Consumers in Urban Kenya, Malawi and Zimbabwe. J. Hum. Nutr. Diet. 2023, 36, 2180–2200, doi:10.1111/jhn.13244.

Comment 2: The introduction is too long, shorten it
Response 2: Thank you for the comment. This is noted. Following your suggestion, lines 47-82 and 118-129 have been summarized, shortened, and simplified.

Reviewer 3 Report

Comments and Suggestions for Authors

1. The manuscript studies the problem of malnutrition and food safety among school children in Kenya, which has important practical significance. Given the current global concern about sustainable development and food safety, this study is very timely in the current context and touches on an important issue that needs to be addressed.

2. The study only selected a single school that relies on charitable donations, which may affect the generalizability of the research results. In Kenya, especially in poor areas, many schools rely on government funding or other public resources to implement school meal programs. Selecting a single type of school as a sample may not fully reflect the actual situation of other schools. The authors can expand the sample range by conducting comparative analysis among schools with different funding sources to more fully understand the effects of school meal optimization in different settings.

3. To address the limitations in question 2, it is recommended that the authors consider more types of schools (e.g., public schools, private schools, rural schools, and urban schools) and conduct multi-school and multi-regional studies to ensure that the research results have broad applicability. By comparing the implementation of school meals in different contexts, we can better understand the actual impact of optimized menus and provide more reliable data support for the formulation of more targeted policies.

4. The manuscript mentioned that after the menu was optimized, the intake of certain trace elements exceeded the recommended values, especially vitamin C and magnesium. This reflects that although the supply of nutrients was improved during the optimization process, it may also bring about the problem of excessive intake of certain nutrients. The study mentioned that these values ​​do not reflect the actual dietary intake, so they may pose unnecessary risks to children's health, especially excessive intake of vitamin C, which may lead to problems such as indigestion. This part can be further discussed, for example, what effects long-term excessive intake of certain nutrients (such as vitamin C, magnesium, etc.) may have on children's health. The study can explore how to avoid excessive intake while maintaining adequate nutrition. For example, increase the diversity of the menu and avoid relying on a single food source to balance the intake of various nutrients and ensure the diversity of nutrients.

5. Although the author mentioned the potential of NUS in school meals, he did not explore the obstacles to the actual promotion of NUS in depth. As a representative of traditional food, the low utilization rate of NUS may be affected by many factors, including cultural identity, economic affordability, and challenges in logistics and distribution. For example, some NUS may be culturally considered low-end foods, and many families and schools may prefer to choose more common staple crops, which leads to low acceptance of NUS. In addition, some NUS have a long growth cycle and unstable yields, which may cause difficulties in the supply chain.

6. It is recommended that the author consider tracking children's health and academic performance in future research work to evaluate the impact of optimized menus on their long-term health and academic performance. By comparing the nutritional status, weight, academic performance and other data of students before and after the implementation of the optimized menu, the long-term effect of the optimized menu can be more comprehensively evaluated. In addition, future research can consider the factors of climate change, such as evaluating the production and supply of NUS under different climate scenarios, and the impact of these changes on school meal optimization.

7. Appropriate supplementation of the application of linear programming tools, SMP PLUS software, and the introduction of some charts will make readers more aware of the author's research work, especially the interpretation of the charts.

Comments on the Quality of English Language

The quality of English can be appropriately improved.

Author Response

Comment 1: The manuscript studies the problem of malnutrition and food safety among school children in Kenya, which has important practical significance. Given the current global concern about sustainable development and food safety, this study is very timely in the current context and touches on an important issue that needs to be addressed.
Response 1: Thank you. Your comment is greatly appreciated.

Comment 2: The study only selected a single school that relies on charitable donations, which may affect the generalizability of the research results. In Kenya, especially in poor areas, many schools rely on government funding or other public resources to implement school meal programs. Selecting a single type of school as a sample may not fully reflect the actual situation of other schools. The authors can expand the sample range by conducting comparative analysis among schools with different funding sources to more fully understand the effects of school meal optimization in different settings.
Response 2: Many thanks for this important comment. We realize that this is indeed a study limitation and, as such, has been listed in Section 4.1 Study limitations. Indeed, in our concluding remarks we add that comparative analysis is key and that “Future research should build on this foundation by testing these optimized menus in a broader range of real-world school settings, ensuring that they are not only nutritionally and economically viable, but also practically implementable”. (Lines 580-582). Nonetheless, the cost estimates for diets and their implications for schools remain unchanged. Therefore, we still consider this pilot study to still be relevant. Once published, it can serve as a foundation for guiding larger studies that will allow for the inclusion of different NUS, schools and settings, enabling more comprehensive comparisons and broader insights.

Comment 3: To address the limitations in question 2, it is recommended that the authors consider more types of schools (e.g., public schools, private schools, rural schools, and urban schools) and conduct multi-school and multi-regional studies to ensure that the research results have broad applicability. By comparing the implementation of school meals in different contexts, we can better understand the actual impact of optimized menus and provide more reliable data support for the formulation of more targeted policies.
Response 3: Indeed, this paper stems from a pilot study, which was limited in both scope and scale. However, as noted, the results highlight the potential of NUS as an essential nutrient source for school meals and demonstrate how the SMP PLUS software could be used by decision-makers. Moving forward, we aim to secure additional funding to expand this pilot research to further test the applicability of our findings across a wider range of schools and geographic contexts.

Comment 4: The manuscript mentioned that after the menu was optimized, the intake of certain trace elements exceeded the recommended values, especially vitamin C and magnesium. This reflects that although the supply of nutrients was improved during the optimization process, it may also bring about the problem of excessive intake of certain nutrients. The study mentioned that these values do not reflect the actual dietary intake, so they may pose unnecessary risks to children's health, especially excessive intake of vitamin C, which may lead to problems such as indigestion. This part can be further discussed, for example, what effects long-term excessive intake of certain nutrients (such as vitamin C, magnesium, etc.) may have on children's health. The study can explore how to avoid excessive intake while maintaining adequate nutrition. For example, increase the diversity of the menu and avoid relying on a single food source to balance the intake of various nutrients and ensure the diversity of nutrients.
Response 4: Thank you for your feedback. We agree that the optimization did not allow for the balancing of all nutrients. To improve clarity, we have included the mean nutrient values from the baseline menu in Figures 4 and 5, which illustrate the areas where the optimization was effective. For example, vitamins A, B3, B6, B9, and C were lower after the optimization. While vitamin C remained above 100% of the Recommended Daily Allowance (RDA), it is important to note that these values were based on raw products, and the cooking process would likely reduce the vitamin C content, as it is not heat-stable. This aspect has been added to the limitations section.
We also acknowledge that plant-based foods can interact with magnesium absorption, reducing its bioavailability due to the presence of compounds like lignin, phytates, and oxalates. Incorporating whole-grain maize for the ugali could potentially support magnesium absorption, as noted by Cazzola et al. (2020). However, the interaction between home-based food consumption and school-meal nutrient intake was outside the scope of this study. We have expanded the limitations section to address these points. 
Cazzola, R., Della Porta, M., Manoni, M., Iotti, S., Pinotti, L., & Maier, J. A. (2020). Going to the roots of reduced magnesium dietary intake: A tradeoff between climate change and sources. Heliyon, 6(11), e05390. https://doi.org/10.1016/j.heliyon.2020.e05390

Comment 5: Although the authors mentioned the potential of NUS in school meals, he did not explore the obstacles to the actual promotion of NUS in depth. As a representative of traditional food, the low utilization rate of NUS may be affected by many factors, including cultural identity, economic affordability, and challenges in logistics and distribution. For example, some NUS may be culturally considered low-end foods, and many families and schools may prefer to choose more common staple crops, which leads to low acceptance of NUS. In addition, some NUS have a long growth cycle and unstable yields, which may cause difficulties in the supply chain.
Response 5: Indeed, the promotion of NUS is a separate theme, and exploring this topic in depth was beyond the scope of this paper. In the Introduction, we highlighted previous work undertaken in Western Kenya showing that linking farmers to schools for the sale of NUS is feasible in home-grown school feeding programs albeit at a pilot scale. The authors feel that a large obstacle to “selling” NUS to school administrations is that they are not considered as a valid nutrition alternative at “affordable” prices, and therefore we consider this study as an important element of the ongoing discussion.

Comment 6: It is recommended that the author consider tracking children's health and academic performance in future research work to evaluate the impact of optimized menus on their long-term health and academic performance. By comparing the nutritional status, weight, academic performance and other data of students before and after the implementation of the optimized menu, the long-term effect of the optimized menu can be more comprehensively evaluated. In addition, future research can consider the factors of climate change, such as evaluating the production and supply of NUS under different climate scenarios, and the impact of these changes on school meal optimization.
Response 6: Indeed, thank you for these important considerations. There is considerable information already available on the positive correlation between providing school meals and health and academic performance outcomes. See the most recent GCNF report: https://gcnf.org/wp-content/uploads/2025/02/GCNF-Global-Survey-Report-2024-V1.8.pdf . What is less documented is the effect of including NUS in school feeding programs and the correlated economic, social, and environmental upstream and downstream effects on the actors included in the school food value chain. With adequate funding, these research questions can of course be explored.

Comment 7: Appropriate supplementation of the application of linear programming tools, SMP PLUS software, and the introduction of some charts will make readers more aware of the author's research work, especially the interpretation of the charts.
Response 7: Thank you. We have now included references to detailed descriptions of the tool, along with screenshots as Supplementary materials. This should provide interested readers with a deeper understanding of how the software functions and how it can be applied in similar studies. We believe this addition will help clarify the tool’s application and functionality for those interested in exploring it further.

Reviewer 4 Report

Comments and Suggestions for Authors

Dear Authors,

Thank you for the opportunity to revise and read this article. This study offers a promising solution to improve school meal programs by incorporating neglected and underutilized species (NUS), demonstrating their potential to enhance nutrition, reduce costs, and promote sustainability. However, some issues need to be addressed:

·       The introduction should be more concise and focused, summarizing the background and clearly stating the study's rationale.

·        In the methods, details on NUS and school selection should be streamlined, with NUS summarized in the introduction or presented in a table for clarity.

·       The conclusion needs refinement, as it currently includes results and discussion elements that should be reorganized into their appropriate sections.

Author Response

Comment 1: The introduction should be more concise and focused, summarizing the background and clearly stating the study's rationale.
Response 1: Thanks for the comment. This is noted. Following your suggestion, sections 47-82 and 118-129 have been summarized, shortened and simplified.

Comment 2: In the methods, details on NUS and school selection should be streamlined, with NUS summarized in the introduction or presented in a table for clarity.
Response 2: Thank you. We fully agree with this observation. The details of the NUS included in the study were included in the abstract and their nutritional properties have been summarized and are now included in the paper in Table 1.

Comment 3: The conclusion needs refinement, as it currently includes results and discussion elements that should be reorganized into their appropriate sections.
Response 3: Thank you for this observation. The Conclusions have been refined and reorganized, addressing your comment.

Reviewer 5 Report

Comments and Suggestions for Authors

It is recommended that the following measures be taken in order to increase the scientific relevance of the study:

Expansion of the sample: conducting a comparable study in multiple schools or regions to illustrate the extensive applicability of the proposed solution.

The integration of a post-implementation evaluation is also recommended. The incorporation of data pertaining to the practical testing of optimised menus is also recommended, with particular attention to the impact on children's health, the reduction of waste, and the real costs incurred.

In addition, comparative and contextual analyses should be conducted. A comparison of the proposed solution with other models of school meals, both from a nutritional and financial point of view, should be made to demonstrate the superiority of the proposed solution.

Finally, the study will highlight the policy relevance of the proposed solution. The study should also discuss how it can contribute to the formulation of national or regional policies on school meals.

Comments for author File: Comments.pdf

Author Response

Comment 1: Expansion of the sample: conducting a comparable study in multiple schools or regions to illustrate the extensive applicability of the proposed solution.
Response 1: Thank you for this important comment. We realize that this is indeed a study limitation and, as such, has been added to Section 4.1 Study limitations. Indeed, in our concluding remarks, we add that comparative analysis is key (see lines 580-582) and that “future research should evaluate the additional costs associated with increasing the nutrient provision threshold to 50%, with 30% allocated to lunch and 20–25% to snacks and breakfast—common practice in many other national programs. Testing optimized menus in diverse school settings is essential to ensure their nutritional and economic feasibility, as well as their practical implementation” (lines 577-582).”

Comment 2: The integration of a post-implementation evaluation is also recommended. The incorporation of data pertaining to the practical testing of optimised menus is also recommended, with particular attention to the impact on children's health, the reduction of waste, and the real costs incurred.
Response 2: Thank you for your insightful comment. We completely agree. This study was focused solely on the affordability aspect and, as mentioned in the Discussion and Conclusions, the next step will be to test the applicability and health impact of incorporating NUS into school meals. However, these aspects were beyond the scope of this pilot study.
That said, we emphasize that NUS have previously been neglected in the planning tool, and we had to manually add them for the purpose of conducting this study. As demonstrated, including NUS in the meal planning process can lead to cost reductions. Achieving this, however, may require a shift in the food procurement paradigm. We have revised the Discussion to ensure that these points are clearer and more explicitly addressed.

Comment 3: In addition, comparative and contextual analyses should be conducted. A comparison of the proposed solution with other models of school meals, both from a nutritional and financial point of view, should be made to demonstrate the superiority of the proposed solution.
Response 3: Many thanks for this important comment. We realize that this is indeed a study limitation and, as such, has been added to Section 4.1 Study limitations. Indeed, in our concluding remarks, we add that comparative analysis is key (see lines 580-582) and that “future research should evaluate the additional costs associated with increasing the nutrient provision threshold to 50%, with 30% allocated to lunch and 20–25% to snacks and breakfast—common practice in many other national programs. Testing optimized menus in diverse school settings is essential to ensure their nutritional and economic feasibility, as well as their practical implementation” (lines 577-582)”. 

Comment 4: Finally, the study will highlight the policy relevance of the proposed solution. The study should also discuss how it can contribute to the formulation of national or regional policies on school meals.
Response 4: Thank you for your insightful comment. Developing regional recommendations for school meals is inherently challenging due to the context-specific nature of school feeding programs. These programs vary significantly based on local dietary habits, agricultural production systems, policy frameworks, infrastructure, and socio-economic conditions. For example, factors such as food availability, procurement mechanisms, cultural preferences, and government capacity to implement and sustain programs differ widely between regions.
Additionally, funding models and governance structures play a crucial role in shaping school feeding initiatives. While some programs are nationally funded and integrated into broader social protection schemes, others rely heavily on donor support, making their sustainability uncertain. Climate and environmental considerations further complicate standardization, as regions face different constraints and opportunities in sourcing sustainable, nutritious ingredients.
Given these complexities, our approach prioritizes adaptable, evidence-based frameworks that allow for localized customization rather than prescriptive, one-size-fits-all recommendations. We aim to highlight key principles—such as nutritional adequacy, affordability, and sustainability—that can be tailored to specific regional contexts while ensuring effective and equitable implementation.

Round 2

Reviewer 5 Report

Comments and Suggestions for Authors

The manuscript underwent a thorough revision process to ensure that the observations and recommendations were thoroughly addressed.