14/10/2026

The Invisible Footprint of Pet Food: When the Lack of Market Intelligence Also Impacts the Planet

The pet food industry has made significant progress in sustainability. Manufacturers, suppliers, and retailers are investing increasing resources in improving energy efficiency, reducing waste, optimizing logistics routes, and developing packaging alternatives with lower environmental impact.

These are necessary and valuable initiatives. However, there is one question that rarely appears in industry conversations: How big is the footprint if we make wrong decisions? The question may seem unusual, but it is becoming increasingly relevant in an industry that operates in environments of growing complexity, where decisions involve multimillion-dollar investments, international supply chains, long-term industrial capabilities, and consumers whose habits are constantly evolving.

When we talk about sustainability, we tend to focus on what happens after a decision has been made, which is what happens inside the plant, during distribution, or at the point of sale. It is much less common to analyze what happens beforehand.
Many of the Costliest Footprints Are Generated in the Boardroom
There is a natural tendency to associate environmental impact with manufacturing. However, some of the decisions with the greatest consequences for the efficient use of resources are made long before a plant produces a single kilogram of food.

An oversized investment, an expansion based on unrealistic expectations, or an incorrect reading of the market can generate years of operational inefficiencies that are difficult to correct afterward. When this happens, the problem is no longer only financial. It also translates into resources mobilized, installed capacity, inventories, and commercial efforts that end up pursuing an opportunity different from the one that actually existed.

Sustainability is usually measured after production begins. Perhaps part of the conversation should start before the investment is made.

consider a company that has decided to expand production capacity for a category that is expected to grow over the next few years. The decision seems logical. However, if actual growth is concentrated in specific segments, if sufficient idle capacity already exists in the market, or if demand evolves differently than expected, the result may be an underutilized investment for years. This is very common.

The same happens with product launches. Many studies of consumer-packaged goods estimate that a significant proportion of new products fail to achieve the commercial objectives originally set for them. Behind those projects were raw materials, packaging, industrial capacity, transportation, storage, executive time, and financial resources that were mobilized to capture an opportunity that ultimately turned out to be smaller than anticipated.

We usually analyze these cases from a financial perspective. However, they also represent an inefficient use of resources that could have been avoided with a deeper understanding of the market.
There is Data, but Not Always Architecture
In this context, most companies have enough information to understand their own business: sales, costs, customers, inventories, margins, operational efficiency, and channel performance. Although that is not usually the central problem.

The challenge arises when a decision requires understanding the entire system—that is, when a company needs to know whether the growth of a category comes from greater real consumption or simply from inflation; whether additional volume is being concentrated among a few players or creating room for new competitors; whether a regional expansion justifies its own investment or can be addressed through existing capacity; whether the growing channel is also capturing value, or simply shifting volume with lower profitability. These types of answers rarely exist within a single database. They are usually fragmented across commercial teams, market reports, distributors, suppliers, plants, customers, and the knowledge accumulated by local teams. For that reason, many decisions do not fail because of an absolute lack of information, but because of a lack of an integrated reading of the market. The difference is substantial. A company may have a great deal of data but not a clear architecture for decision-making.
The Real Cost of Uncertainty
For years, the industry learned to measure tons, market share, sales, and productivity—fundamental indicators for managing any business. However, there is one cost that rarely appears on executive dashboards: uncertainty.

Uncertainty manifests itself when an organization develops more SKUs than the market actually needs. It also appears when a company invests in categories whose future profitability has been overestimated; when it takes months to identify the right manufacturing partner; when it builds capabilities that end up operating below their potential; or when it launches products whose value proposition was never sufficiently validated.

Each of these mistakes generates visible and invisible costs. The visible costs appear in financial statements. The invisible costs appear in the form of resources, time, energy, transportation, materials, and efforts that could have been allocated to opportunities with a higher chance of success.
The Next Competitive Advantage Will Be the Quality of Decisions
Throughout the history of the pet food industry, competitive advantages have been associated with better plants, better formulations, better production processes, and better distribution networks.

All these factors will continue to be important. However, the industry's next competitive advantage will probably not come from a better plant or a better formulation, but from a better understanding of the system.

Markets do not operate in isolation, and neither do decisions. Just as an industrial investment affects the competitive structure, a change in channels modifies profitability. Likewise, the availability of production capacity changes barriers to entry, while consumer evolution redefines entire categories.

The challenge is to understand how these variables interact before committing resources. In increasingly complex markets, the costliest mistakes rarely come from executing a strategy poorly; they often come from having misinterpreted the opportunity from the beginning.
Optimizing Decisions Reduces Footprint and Improves Our Business
The industry will continue innovating in ingredients, packaging, and processes. However, some of the greatest opportunities for improvement are not in the plants, but before an investment, a product launch, or an expansion is approved.

The companies that best understand the market—and not only their business—will be the ones that allocate resources more effectively, make fewer strategic mistakes, and capture more growth. By Iván Franco
Source: All Pet Food Magazine

By Iván Franco

13/10/2026

From Farm to Bowl: An Analysis to Maximize Sustainability Impacts

Multinational companies leading the industry are already leading the way and defining the standard. Nestlé has made strong public commitments to reducing greenhouse gas emissions and achieving net-zero emissions, emphasizing the advancement on regenerative agriculture. Mars Petcare aims to reduce its carbon footprint across its entire value chain by 50% and has implemented ambitious goals to transition its packaging toward circular economy models.
Why are category leaders investing so many resources in sustainability?
The answer is that consumers are demanding greater accountability. Natural resources are finite, and long-term financial viability depends on the ability to adapt.

To understand how we can maximize our impact, let us explore the production chain from a holistic perspective: from farm to bowl. As I have mentioned in previous articles, the factory may seem like a magical world where raw materials enter and value-added packaged products emerge. However, every step—both inside and outside that magic—leaves an environmental footprint that commercial teams, together with other business functions, must know how to manage and communicate.
The Farm: Sourcing Raw Material and Ingredients 
The pet food manufacturing process is complex. The quality of the final product depends largely on the quality of its ingredients. However, in today's context, quality must also take origin and environmental impact into account. Agriculture and livestock production undeniably account for the largest share of our industry's carbon footprint.
  Regenerative agriculture and livestock: We must transition toward suppliers that implement practices aimed at improving soil health, optimizing water use, and capturing atmospheric carbon.
  Protein sustainability: Supply chains should be redesigned to eliminate deforestation risks associated with critical raw materials while prioritizing 100% certified sources and evaluating alternative proteins with lower environmental impact.
  The Process: Operations and Manufacturing
Every stage presents significant opportunities within the production plant. In many cases, the best ideas emerge from careful observation and a deep understanding of the manufacturing process. Best of all, sustainable innovation does not always require multimillion-dollar investments.
  Energy and water management: The gradual transition to renewable energy sources and the optimization of industrial water use are essential steps toward decarbonizing production.
  Low-effort, high-impact innovation: Improving food digestibility can help reduce biological waste generated by pets. Likewise, in dry pet food production, monitoring and optimizing pressure and temperature parameters during extrusion is not only vital for product quality but can also significantly reduce energy consumption.   Packaging: The Product's Face 
Packaging protects pet food from moisture, light, and oxygen while providing consumers with essential information. However, the industry's historical dependence on multilayer plastics represents a major environmental liability.
  Material circularity: Using more sustainable packaging materials, such as recyclable mono-material solutions or compostable packaging, reduces environmental impact and appeals to increasingly eco-conscious consumers. This does not require changes to the food formulation, yet it can have a highly positive effect on brand perception.
  Logistics efficiency: From a logistical standpoint, improving fill rates and redesigning packaging dimensions for greater efficiency can generate large-scale operational savings. Optimized boxes and pallets translate into fewer trucks on the road, reducing fossil fuel consumption and emissions. Likewise, embracing the e-mobility revolution can further contribute to broader sustainability goals.
  The Bowl: Commercialization and Marketing
The commercial area must serve as an honest ambassador of a brand's sustainability efforts. Packaging material selection and label design are strategic decisions, as they represent the first communication touchpoint consumers encounter on store shelves before the product reaches the pet's bowl.
  Marketing with substance: It is essential for commercial teams to understand the environmental impact of key ingredients and the sustainability initiatives implemented within manufacturing operations. Communicating these efforts with real data strengthens the company's position in the marketplace.
  Transparency as a competitive advantage: Understanding the entire 'farm-to-bowl' process enables sales teams to answer questions accurately regarding manufacturing methods, ingredient origin, and quality controls. This transparency builds credibility, fosters long-term relationships, and distances brands from the significant reputational risks associated with greenwashing.   A Call to Action Across the Entire Value Chain
Sustainability-driven innovation is a winning long-term strategy for the pet food industry. By gaining a comprehensive understanding of the value chain, commercial teams can unlock a wave of creative ideas that improve products, optimize costs, and meet evolving market demands.

However, achieving the goal of a truly responsible business model is not a task confined to quality assurance or environmental departments. It is a systemic effort that spans the entire chain, from agricultural sourcing to the neighborhood pet store.

I would like to conclude this article with a genuine invitation to all stakeholders within the ecosystem—manufacturers, raw material suppliers, veterinarians, and retailers. Let us take a moment to examine our own operations: Where can we generate less waste? What silent innovation can we implement today?

The sustained success of our industry will depend on our ability to nourish pets with the same passion with which we preserve the only planet we have to share with them. By Felipe Martínez R.
Source: All Pet Food Magazine

By Felipe Martínez R.

07/09/2026

AI & Digital Transformation Seminar to Help Manufacturers Turn AI Strategy into Practical Action

SABETHA, Kan. — Manufacturers looking to move beyond the AI hype and implement practical digital transformation strategies will have the opportunity to do just that at the AI & Digital Transformation Seminar, taking place September 16–18, 2026, at Prairie Band Casino & Resort and NorthWind Technical Services Headquarters in Sabetha, Kansas.

Designed for manufacturing professionals across the food, beverage, animal feed, pet food, grain, plastics, and related process industries, the seminar focuses on actionable education rather than product demonstrations. Attendees will hear directly from industry experts, technology partners, and manufacturers who are applying artificial intelligence and digital technologies to improve operations, reduce downtime, and increase productivity.

This year's event features a distinguished lineup of speakers and organizations at the forefront of industrial innovation, including Rockwell Automation, Palantir, and the Clean Energy Smart Manufacturing Innovation Institute (CESMII), alongside real-world case studies from manufacturers actively executing digital transformation initiatives.

Featured Session Highlights Include: Unified Namespace — John Dyck, CESMII
A deep dive into connected plant architectures and the role of the Unified Namespace in enabling smart manufacturing at scale.
  Digital Transformation Starts Small — In this panel, three manufacturers share their account of the single step that started their digital transformation journey, what it delivered for their business, and what they're tackling next. 
  Digital Transformation Journey Case Study — Stephen Dubatowka, Saint-Gobain Life Sciences & Robert Lee, NorthWind Technical Services
A real-world implementation story from Saint-Gobain Life Sciences, sharing lessons learned and measurable outcomes from their digital transformation journey.
  Machine Learning for Preventative Maintenance — Udaya Kumar, Rockwell Automation An exploration of how machine learning is being applied today to predict equipment failures, reduce unplanned downtime, and extend asset life.
  AI Guided Troubleshooting — Ben Bosworth, NorthWind Technical Services
 practical session on how AI-assisted tools are transforming how maintenance and operations teams diagnose and resolve issues on the plant floor.
  Building Robust AI for the Future — Will Rees, Palantir
Insights from Palantir on building scalable, enterprise-grade AI systems that deliver lasting value in manufacturing environments.
  The AI & Digital Transformation Seminar is designed to provide attendees with practical knowledge they can apply within their own facilities.

"Manufacturers are no longer asking if AI belongs in their operations, they're asking where to start and how to achieve measurable results," said Matt Lueger, Executive Vice President of NorthWind Technical Services. "This seminar was created to provide practical guidance, real-world examples, and meaningful conversations that help manufacturing leaders make informed decisions about their digital transformation journey."

In addition to classroom-style educational sessions, attendees will participate in networking events, technology demonstrations, and an open house at NorthWind's headquarters, offering an inside look at modern automation, controls engineering, and digital manufacturing solutions.

The seminar is intended for plant managers, operations leaders, engineering managers, maintenance professionals, IT and OT leaders, executives, and others responsible for improving manufacturing performance through technology.

For additional event information and registration, visit events.northwindts.com. Source: Northwind Technical Services

About the company
NorthWind Technical Services is a system integrator specializing in industrial automation, process controls, Manufacturing Execution Systems (MES), and AI-enabled manufacturing solutions. The company partners with manufacturers worldwide to improve operational performance through innovative technology and engineering expertise.

03/04/2026

Eyes That Never Blink: How AI Is Transforming Food Inspection and Safety  

AI has been a firestorm, sweeping through almost every aspect of our day-to-day, and the same can be said for food manufacturing. AI may be the new tool that will allow almost any product to finally achieve 100% inspection, reducing defects and failures at the consumer level. So too, we are seeing incredible advancements in AI-driven food manufacturing, which, when fully developed and capitalized, will most certainly reset the bar for what consumers consider a 'high-quality' product.
  Advancements are infiltrating many aspects of daily life for food safety and quality professionals. This is leading to some very exciting initiatives to prevent deviations from specification and enhance manufacturers' ability to ward off potential food safety problems.
  There are many advancements hitting the marketplace, but some worth mentioning are in the following areas.   Vision Systems
Some of the most common quality complaints include missing labels, misaligned labels, missing or illegible code dates, the wrong label for the product, seal failures, and other packaging defects. New optical cameras with AI technology can automatically detect and remove these types of defects well before the consumer purchases them. Many systems use multipoint inspection, like the one pictured below, and can view a package from a 360° perspective. When defined parameters are exceeded, the product is automatically removed from the line. 
  Photo courtesy of ANTARES VISION S.p.A   These systems can even detect various foreign materials, such as hard and soft plastics, wood, and other materials, based on their optical signatures.   Metal Detection and X-Ray Systems
Metal detectors are common in most food operations where knives and blades are used for protein harvest or when grinding protein-based products. They are used as a food safety measure for foreign materials that can cause harm when ingested. X-ray systems are often used for harder types of foreign materials, such as bones, cartilage, glass, and metal. In the past, this equipment was only as useful as the number of false positives it would produce during a production shift.
  Now, with advances in AI algorithms, these smart detectors can discern multiple types of materials in pieces, much like the technology used to screen luggage at the airport does, in multiple layers or overlapping placement. This ensures foreign material is detected accurately and distinguishes between various types and the number of foreign objects in a product.  This will allow for early detection and root cause prevention   Hyperspectral Technology
This is a fascinating new field that will likely revolutionize food safety. These systems utilize spectroscopic measurements and ultra-sensitive cameras to detect images at the pixel level, across very narrow wavelength ranges within spectral bands, providing a 3D view of the test sample. It's like incorporating a microscope and a microbiologist at the same time. This type of testing is very rapid and does not use any chemicals, making it very environmentally friendly. The system is literally looking for live organisms in a sample and can even quantify them, so it is very accurate.   Source: Pandey AK, Samota MK, Kumar A, Silva AS and Dubey NK (2023). Fungal mycotoxins in food commodities: present status and future concerns. Frontiers in Sustainable Food Systems, 7:1162595. doi: 10.3389/fsufs.2023.1162595.   Predictive Microbial Risk Modeling
AI systems analyze historical data, such as environmental monitoring results, sanitation logs, and process data, to predict where microbial contamination is most likely to occur in a facility. These predictive systems help companies prevent contamination rather than simply responding to it. By being predictive rather than reactive, food safety and sanitation professionals can reduce sanitation failures, line downtime, and prevent recalls. These models could also be used to validate environmental testing programs and food safety plans.
One additional integration for predictive modeling and food safety inspection is that it monitors employees' adherence to good manufacturing practices. AI is now being used to ensure employees do not use utensils that fall on the floor, use soiled equipment, or forget to wash their hands when working with food.   Enhanced Grading and Sorting Systems
By using optical cameras integrated with smart AI, machines can now be taught to recognize correct shapes and colors, and previously subjective quality grades can be measured objectively. If you have a baked kibble product, for example, how dark is too dark?
  As quality professionals, we used to create picture-based scales to train employees on color and shape, but these tools were only as good as the original picture-taker and the printer you had to display the grading. Now, camera technology has gotten so good that a color scale and a given shape template can be programmed to ensure each piece of treat or kibble is within specification. This uniformity will lead to higher yields and fewer packaging issues, as the product itself will be more consistent.   Process Control Monitoring for Food Safety and Processing Parameters
Examples include thermal process schedule reviews, critical control point (CCP) and process control point (PCP) monitoring, and temperature and weight monitoring. One limitation of inspection is that you may only be able to perform it at a limited frequency, say, once per hour.
  Almost anything that can be continuously measured can now be enhanced with AI logic to provide continuous, real-time monitoring of all your critical or process control points. This provides tons of data, and as root causes are identified and logged for a deviation or failure, your AI system will begin to predict useful information, such as, 'Your average temperature deviation is every 41 days and has been assigned to a sensor failure. You should add it to the preventive maintenance list to change or check every 40 days.' Real-time monitoring also increases release time and does not need a formal pre-shipment review.   Unblinking Eyes: The Future of Food Safety
The creativity and uses for AI in food safety and quality systems are only now being realized. The market for equipment and use is only in its infancy. As a food safety and quality professional, I am excited to see how more advanced technology, like these systems that never get fatigued and have 'eyes that never blink,' is implemented.
  If you share my enthusiasm or have a compelling use case from your own operation, please share it in the comments. The future of food safety will be written not just by the technology itself, but by the professionals bold enough to implement it. By August Konie
Source: BSM Partners
  About the Author
August Konie has been a Food Safety, Quality and Regulatory Professional for over 30 years. He was worked in many sectors of the food industry including fisheries, beverages, poultry, pork and pet food, under both FDA and USDA regulatory oversight. As an active committee member in various trade organization for food and pet food organizations, he was successful of implementing new regulatory guidance. He has worked with various teams across Asian, Europe, North and South American on various food safety, quality and import/export concerns. He currently serves as the Principal of BSM Assurance overseeing FSQAR activities at BSM Partners.

07/04/2026

Digital Twins in the Pet Food Industry: From Simulation to Predictive Control

What Digital Twins Are and How They Are Used Today
A digital twin is a dynamic, virtual representation of a physical object, process, or entire an production system. Unlike static simulation, it continuously utilizes real data from sensors and control systems, enabling it to accurately reflect the current state of the process and predict its future behavior.

According to IBM, digital twins are currently used in manufacturing to improve operational efficiency, optimize processes, reduce failures, accelerate product development, and enable predictive maintenance. In industrial environments, their application ranges from individual production lines to entire plants, integrating operating variables, energy consumption, quality, and equipment performance, as well as supporting plant planning, virtual testing of new products, layout optimization, and control of complex processes, among other uses.
From Simulation to Predictive Decision-Making
The advancement of digital twins is closely linked to the convergence of process simulation, industrial sensors, artificial intelligence, and cloud computing. This integration enables manufacturers to move from a reactive model—based on manual sampling and subsequent adjustments—to a predictive and preventive approach.

According to an article by StartUs Insights, the market for digital twins applied to manufacturing could reach USD 714 billion by 2032, driven by the need to optimize complex processes and reduce operational inefficiencies. The same report indicates that more than 81% of global companies are already actively exploring the industrial metaverse, and that 62% increased their investment in these technologies over the past year.

These figures reflect a structural shift: simulation is no longer limited to the design stage but is becoming a central tool for day-to-day plant management.

The study, Digital Twin applications in the food industry: a review, identifies four main approaches to applying digital twins in the food industry, defined by their role within the production system. First, forecasting digital twins are used to anticipate the future behavior of processes or equipment based on the analysis of historical data and current conditions, enabling the prediction of deviations, inefficiencies, or failures before they occur. Second, reactive simulation models allow real-time process monitoring and autonomous responses to deviations, adjusting operating variables and recommending corrective or preventive actions. A third approach is virtual commissioning, which utilizes digital twins to test, validate, and optimize new technologies, equipment, or plant configurations in a virtual environment before physical implementation. Finally, synchronization-based simulation keeps the digital twin aligned in real time, or near real time, with the physical system, creating a highly accurate representation of the process that is especially valuable for scenario analysis, operational optimization, and improved decision-making in complex systems.
How Do Digital Twins Contribute to the Pet Food Industry?
Focusing specifically on the pet food industry, raw material variability is one of the main factors affecting final product quality. Ingredients, such as cereals, protein meals, fats, and animal by-products naturally fluctuate in moisture, protein content, fat levels, and particle size distribution.

According to a technical analysis published by Haskell, these variations directly affect critical operations such as extrusion and drying, influencing attributes such as texture, density, nutritional stability, and product shelf life. Traditional control methods often detect these deviations only after the product has already been produced, leading to reprocessing, waste, and efficiency losses. Digital twins, by contrast, anticipate these effects before they impact the final product.

In pet food production, a digital twin is built from models that represent the thermal, mechanical, and dynamic behavior of each unit operation (mixing, conditioning, extrusion, drying, and cooling). These models are powered in real time with data from sensors installed in the plant, such as ingredient moisture measurements, extruder barrel temperature, screw speed, pressure, airflow, and dryer parameters. This information synchronizes the virtual model with the real process, creating a living representation of the plant in operation.

In closed-loop control systems, besides observing the process, digital twins predict how variations in raw materials will affect the final product and automatically adjust operating parameters to compensate—often even before the ingredient enters the extruder.
Benefits of Implementation
Implementing digital twins delivers tangible benefits at multiple levels. First, it significantly improves product consistency by reducing batch-to-batch variability, a key factor for consumer trust and brand reputation.

By preventing out-of-spec production, raw materials and energy waste are reduced. This approach also optimizes energy consumption and increases throughput without compromising quality, directly impacting operating costs.

Another strategic benefit is to hasten product development. Formulations can be tested virtually, evaluating their performance in the process before conducting physical trials, thereby reducing time, risk, and costs associated with industrial testing.

Added to this is the ability to integrate predictive maintenance, using digital twins to detect deviations in equipment performance and anticipate failures, avoiding unplanned downtime.
Digital Twins: Key Technology for Building Truly Connected Plants
The incorporation of digital twins marks a turning point in how pet food production plants are managed. It is no longer just about automation, but about deeply understanding the process, anticipating deviations, and making decisions based on real, comparable data.

In a context where efficiency, sustainability, and quality are increasingly decisive, digital twins are consolidating their role as a strategic tool for manufacturers seeking to scale, differentiate, and build truly connected and resilient plants. By Candelaria Carbajo – All Pet Food
Source: All Pet Food Magazine
References
Gallagher, Nick (Updated October 17, 2025) What is a Digital Twin? IBM
Prasser, David R. (July 21, 2025). Future of Manufacturing: 13 Trends Driving 2026-2035 Growth. StarUs Insights
Abdurrahman, Emadaldin Elfatih M. & Ferrari, Giovanna. (April 3, 2025). Digital Twin applications in the food industry: a review. Frontiers
Haskell. (December 19, 2025). A Process Engineering Perspective on Digital Twins in Pet Food Manufacturing.

By María Candelaria Carbajo

17/03/2026

Dog and Cat Food Processing: Our Daily Challenge

Pet foods are currently classified into three categories: complete, complementary, and specific, whether dry or wet. Within each category, companies develop sub-segments to meet the needs of different animal profiles, such as senior pets, athletic animals, and obese pets, among others. The search for alternative diets, functional ingredients, and more sustainable solutions has shown steady growth. This movement has driven intensive research to ensure that products deliver not only adequate nutrition but also additional health benefits, improved quality of life, and a reduced environmental footprint.
  To achieve all of this, the industry no longer relies solely on robust equipment or generic formulations for dogs and cats. More than ever, manufacturers must be connected in real time to every stage of the process, with each department involved in the production of pet food. Machines, sensors, software, and people, therefore, need to operate in an integrated manner so that production continuously adapts to the process and improves over time. By combining automation, data, and technical expertise, an automated plant transforms production into a dynamic, intelligent system capable of continuous evolution.
Daily Manufactured Innovation   The achieved precision at each stage of the process—extrusion, drying, and coating— is a practical example of how this approach is carried out. An automated system enables:
  Precise, automated dosing of micro-ingredients, especially in complementary foods that require a high level of accuracy. Automated control and inclusion of fresh meat, meals, and oils. High-tech laboratories that analyze all raw materials upon reception. Aligned NIR systems with just-in-time results, enabling immediate adjustments when required. Minimization of variations that affect digestibility and palatability. Fully digital traceability, from raw material intake to finished product. Automation of Overall Equipment Effectiveness (OEE) helps identify bottlenecks and opportunities for improvement.
  In extrusion, one of the most critical steps in kibble manufacturing, the process is significantly optimized through automation:
  Temperature and pressure control in each extruder zone. Screw speed control. Steam and water addition as required. Greater baking consistency, which improves digestibility, texture, and kibble durability. More homogeneous kibble density and expansion, with improved starch gelatinization and reduced waste. Automatic recording of process parameters, ensuring traceability and batch-to-batch standardization.
  The drying stage is crucial for removing moisture and controlling water activity, both of which directly contribute to microbiological safety. Moisture also affects palatability: dogs tend to prefer slightly higher-moisture foods, while cats generally accept drier products. For this reason, the integration of sensors and intelligent software in dryers is critical to prevent under- or overprocessing and to ensure that each batch reaches the exact target moisture content. This level of precision ensures stability, safety, and palatability aligned with the specific requirements of each species.
  Another key step is coating, a particularly delicate stage in the manufacturing of dry pet food. Today, the market offers more advanced coating systems, such as vacuum batch processing equipment, which allows highly precise ingredient application. This level of control directly impacts palatability, oxidative stability, and final product acceptance, ensuring superior sensory performance and overall food quality.
  Automation enables much more robust and accessible traceability. With integrated systems, each batch can be tracked from raw material to finished product, ensuring:
  Rapid identification of non-conformities. More efficient responses in case of product recalls. Greater transparency for consumers. Complete, auditable history of every stage of the process.
  This traceability is especially critical in the production of complementary and therapeutic foods, where any nutritional deviations may compromise product efficacy. Through digitalized controls, the industry ensures precision, consistency, and total batch safety for pet consumption.   The Importance of Labeling   Labelling is another equally essential step to ensuring that all mandatory information is present and accurate, in compliance with the legislation of each country.
  At this stage, it is crucial to involve representatives from all areas of the production chain—including Regulatory Affairs, Quality Control, Research and Development, Packaging, and Marketing. This integration ensures that labeling and packaging are developed safely and efficiently, without rework, while remaining compatible with filling lines and attractive to the end consumer. Technology also plays an increasingly important role in this process. Many companies now utilize specialized software that automatically checks label descriptions against each version. It compares information, detects inconsistencies, and significantly reduces the risk of human error. With automation, greater document security, faster review processes, and higher reliability in final label approval are obtained.
  Another topic gaining increasing relevance in the pet food industry—and one that directly impacts the entire production chain—is sustainability. Far from being just a trend, sustainability has become a strategic pillar guiding decisions from raw material selection to packaging development and industrial process design. Implementing sustainability in the pet food industry is a complex challenge, as it requires balancing production efficiency, costs, and regulatory requirements while also meeting consumer expectations that are increasingly influenced by environmental awareness. The supply chain is complex: it depends on both animal- and plant-based ingredients, requires large volumes of water and energy, and relies on high-barrier packaging that is often difficult to recycle.
  Nevertheless, the sector has made consistent progress. An increasing number of companies are incorporating innovative raw materials, so-called super proteins, including insect meals, which offer a reduced environmental footprint and excellent nutritional value. At the same time, there is a growing internal movement to reduce water and energy consumption, reuse resources, monitor and mitigate CO₂ emissions, and develop 100% recyclable mono-material packaging, facilitating reintegration into the production cycle and reducing environmental impact.
  An even more strategic step is the adoption of Life Cycle Assessment (LCA), a tool that quantifies the environmental impact of a product from the origin of its ingredients to its destination. Companies that already apply LCA stand out for making data-based decisions, identifying critical points, and directing their efforts more effectively—whether in raw material selection, process efficiency, or packaging sustainability. LCA is considered one of the key trends shaping the future of the industry and a competitive advantage for organizations genuinely committed to reducing environmental impact across all stages of the value chain.
  By combining innovation, responsibility, and a long-term vision, the pet food industry demonstrates that sustainability is not merely rhetoric, but an irreversible path and a tangible opportunity to create better products, more efficient processes, and a more balanced future for the planet and coming generations. This underscores that the challenge of producing pet food goes far beyond formulation or ingredient selection; it involves a complex chain that depends on technology, integration, rigorous control, and continuous innovation.
  By Josiane Volpato and Juliana Soares Brazorotto
Source: All Pet Food Magazine

By Josiane Volpato