Don’t cry over spoiled milk, incentivize supply chain for longer shelf life

Too much milk gets pitched, something that was an issue long before these pandemic times of global food insecurity. One of every three gallons of milk was estimated to go to waste in America, according to U.S. Department of Agriculture data from the previous decade. A group of scientists, including one now at Washington University in St. Louis, used mathematical models to integrate knowledge from multiple disciplines — milk production and processing, microbiology and supply chain — thereby striving to attack a centuries-old problem: spoiled milk.

Their research, in particular, found two main strategies that could be used at the beginning of the milk supply chain – on the farm and in the processing plant — to prevent psychrotolerant (cold-growing,) spore-forming bacteria from contaminating and prematurely spoiling milk:

Their study, concluding that enacting both strategies could improve some milk shelf life anywhere between a half-day to 13 days, was published July 8 in one of the Frontiers journals, Frontiers in Sustainable Food Systems.

“In general, I would say that this is not a one-prescription-for-all problem,” said Forough Enayaty Ahangar, a newly arrived lecturer in supply chain optimization at the Olin Business School. “The results of our optimization models demonstrate that optimal combination of interventions is highly dependent on characteristics of each individual dairy processor. These characteristics include the volume of processed milk and the quality of supplied raw milk. Therefore, our optimization models provide novel decision tools from which individual processors can benefit and determine the best strategy for their facility.”

At the intersection of food science, population and veterinary medicine, and supply chain sit bottles of milk, creating a worldwide problem the longer they sit. So Enayaty Ahangar teamed with researchers at her previous institution — Sarah Murphy, Nicole Martin, Martin Wiedmann and senior author Renata Ivanek at Cornell University — to test the strategies via modeling.  

This study targeted the problem of premature spoilage of milk caused by bacteria — Bacillus sp. and Paenibacillus sp. ­— which enter raw milk on farms and whose hardy spores can survive pasteurization. (There is an alternative pasteurization, but it costs more and consumers complain about the milk taste after undergoing the higher temperatures utilized.)

Comparing their findings with Agriculture Department data from 24 states and based on a cow producing 64 pounds or 15 half-gallons of milk per day, the team ran 24 case studies — or generated instances, as they called them — looking at processor size, the number of milk producers in the supply chain and the planning horizon, meaning five and 10 years down the road.

Premium payments, or production-level interventions: Farmers should be encouraged to implement fixes and improve processes from the get-go — starting with milk from the cow’s udders — if they are rewarded for consistent high-quality milk in terms of spore-forming spoilage bacteria contamination and penalized for low-quality milk.

Contracts similar to this bonus/penalty guideline already exist in U.S. livestock commodities such as eggs and chicken, the authors noted. In this paper, the researchers propose a new, flexible bonus/penalty system based solely on raw milk’s initial spore counts at production.

Spore-reduction investment, or processing-level interventions: Milk-processing companies know that technologies such as microfiltration and bactofugation are costly to acquire, install and operate. But this research illustrated how using both of those approaches, including a third, double-bactofugation method, were the most effective ways long-term to eliminate spore-forming bacteria from milk.

Their models predicted, by using such processing-level interventions and investments, shelf lives for milk would increase across the board. That improved shelf life — defined as the first day when 5% of milk packages carry a specific bacterial count — ranged from 20-26 days (for small processing plants) to 28-31 days (medium) to an average of 34 days (large).

“There is increasing attention in the dairy industry to the importance of using low spore count raw milk to produce high-quality dairy products, yet there is no blueprint for industry decision-makers on how to achieve this,” Murphy said. “Importantly, our study contributes to the conversation regarding how the industry can invest in dairy farmers and technologies and provides tools that may have the potential to support industry decision-makers.

“Our focus was mostly on how the process can better allocate their budget to achieve longer shelf life for their processed milk,” Enayaty Ahangar said.

In short, the research showed that medium and large processors could enact interventions and improve their milk’s shelf life up to 13 and 12 days, respectively.

“Working with Cornell’s Veterinary School, one of the best in the U.S., was an amazing experience for me,” said Enayaty Ahangar, trained as an industrial engineer and a specialist in optimization. “I got to work with epidemiologists, microbiologists, food scientists, people from business schools…. And because our novel optimization models integrate methods and knowledge from multiple disciplines, I believe our paper has the potential to be a good starting point for many other research projects in the food industries.”

“The ultimate goal of our research is to support the development of sustainable milk production supply chain, where milk waste is reduced in a way that is cost-effective for all players in the continuum of food production and consumption, and is socially acceptable and environmentally sound,” Ivanek said. “The decision support tools like the mathematical models of milk spoilage developed through the multidisciplinary research effort in this study are an integral part of that journey.”

Added Wiedmann: “This project continues the development of digital tools for both dairy and other food supply chains, which will play an important role as decision support tools for industries as they continue to improve productivity and sustainability of nutritious foods.”

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This work was supported by the Foundation for Food and Agriculture Research, grant number CA18-SS-0000000206.