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However, DairyPlant show two main limitations. Firstly, mechanistic relationships between payment system and farmers’ quality changes were not included in the analysis. Indeed, such relationship is difficult to establish in a specific production context, since it is technically uneasy to link feeding or milking practices to a given quality value (Fuentes et al., 2014). However, changing practices needs for the farmer that extra-costs will be compensate by better milk price (Valeeva et al., 2007), which complicates the modeling of such a relationship. Botaro el al. (2013) reported similar constraints regarding changes in milk composition after rewarding dairy producers. (ii) Calculation in the farmer’s results sheet were not related to farmers’ profits but to farmers’ gross products. The analysis does not include individual farmer’s production costs because it would assume that either the dairy processor knows this private information, or farmers agree to give it in a negotiation process with the processor.

Since information on individual production costs is a strategic resource both on farm and dairy sides in such a negotiation, it seems unnecessary to integrate it in DairyPlant.

The use of DairyPlant could favor the transparent relationship between farmers and processors, especially in areas where there are lack of sufficient knowledge about milk collection and processing aspects. Dairy processors can benefit from the use of DairyPlant by testing various strategies of product portfolio and payment systems without any economic risk. Scenarios combining alternative portfolios and payment systems could be considered since both aspects are linked. Indeed, some dairy products require better milk quality, which could be rewarded by a better payment system, which would secure profits of farmers who are ready to implement quality management strategies. Moreover, the simulations may allow processors to taking into account the diversity of farmers based on their quality performances and capacity to improve, and to implement targeted strategies towards farmers who have difficulties to reach given standards, such as specific advices or input supply programs.

The first use of DairyPlant caused a positive reaction from the small-scale dairy processors involved in the study. Indeed, managing milk manufacturing processes and planning quality incentives systems were unknown concepts by stakeholders when this study started. Implementing the support approach helped them to clarify their ideas about these concepts. Most of processors realized the need to control milk quality, since it has a direct effect on their performances and economic revenues.

However, they also objected that putting more control could push milk suppliers towards processors who are less interested by quality aspects. In such context, the implementation of simple quality-based payment systems that guarantees win-win scenarios for most of the stakeholders could be a key element. But success will depend on the clear understanding of the rules from all the stakeholders’ involved (Lejars et al., 2010), the application of attractive incentives to discourage unfavorable changes in chemical milk composition, and the confidence of both farmers and processors in the quality measurement protocol put in place to provide the individual values required for such a system.

6. Conclusions DairyPlant is a simulation tool focusing on key issues governing raw milk flow from dairy farms until processing plants. The model was designed to provide support to small-scale dairy processors in two specific aspects: (i) to analyze the plant processing management and (ii) to evaluate the possibility of applying milk quality payment systems. Attributes of this support tool include the highly participative nature of the approach, and the assessment and comparison of various alternatives. DairyPlant has been developed as a user-friendly software in order to be used by a large number of potential users in developing countries. Its structure allows the easy understanding of the manufacturing process.

Moreover, values of processing parameters can be personalized for each small-scale dairy processor circumstance for better accuracy of the results.

Tested with a small sample of dairy processors in the Peruvian Andes, DairyPlant was flexible enough to allow the simulation of a large range of scenarios in a short time. Indeed, few input data are required to run a simulation. DairyPlant was also able to provide knowledge about the impacts of quality-based payment schemes on small-scale processors’ profits and farmers’ gross products, assuming data regarding milk composition are available at plant and farmer levels. The results helped processors to develop a critical reflection about quality, his impact on dairy process yield and on profits. Although relationship between farmers’ practices and milk composition are not well established, these simulation results helped processors to build a more systemic perspective of the quality issue in the dairy chain.

Acknowledgements The authors would like to acknowledge the EU’s AgTrain Erasmus Mundus programme and the TFESSD of the World Bank for financially supporting this research. The authors are also grateful for the fieldwork assistance provided by Carolina de La Sota.

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ANNEXES ANNEX 1: Questionnaire for small-scale dairy farmers

–  –  –

When did you install your farm in this area?

What are the main characteristics of your farm (surface, livestock, crops, family work, etc.)?

What are your main reasons to raise cattle?

–  –  –

a.- Reproduction:

What type of breed do you have in your herd?. Do you have a system of genetic improvement at farm level? YES or NO. If is YES, Which one?

b.- Sanitary aspects:

How often do you clean the animal housing?

Do you have a vaccination calendar in your farm? If is YES, which one?

Your herd has faced one of these problems during the last 12 months? YES or NO. Do you have a notebook of treatment records in your farm?

–  –  –

Your availability of forage or concentrate is affected due to a seasonality variation?. How do you manage it?

Do you have a current feeding strategy to increase your milk production or your % of milk components (fat, total solids, etc.)?

d.- Milk production:

How many lactating cows do you have in your farm? Is it a constant number?

How many times per day do you milk your cows?

Total volume produced (per month):

–  –  –

How many kilograms of milk are produced in TOTAL by your farm per day (in average)?

How many kilograms of milk do you use for auto-consumption (per day)?

How many kilograms of milk are used to feed calves (per day)?

Do you have a milking parlour in your farm? If is YES, could you explain how it is designed? If is NO, where do you milk your cows?

Describe what type of facilities and equipment do you have? (Include the material: PVC, stainless steel, etc.) How is your milking system: Manual or automatic? Could you explain how the milking process is done every day?

Do you have a potable (drinkable) water supply system in your farm? If is NO, how do you obtain it?

And what source of water do you use to clean your milking equipment and the parlour?.

Do you follow any hygienical practices in your dairy plant before and during the milking process?.

Which ones?

How do you refrigerate the milk after the milking process? Do you control the temperature?

Do you send directly your raw milk to a collecting point or a processor? Or they collect the milk from your farm? If the processor is the one who collects the milk, how many hours take till they arrive?

–  –  –



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