Purpose: To emphasize the critical role of color in pet food, where appearance influences both consumer perception of quality and their willingness to purchase. While pets rely more on taste and smell, human buyers equate color uniformity with freshness, nutrition, and safety. The paper highlights the challenges of color control across diverse formats such as kibbles, treats, and wet foods, where ingredients, processing methods, and coatings can create variability. It explains why visual inspection is unreliable and how spectrophotometers provide objective, repeatable data to maintain consistent quality. HunterLab solutions are positioned as best-in-class instruments that help manufacturers reduce waste, improve efficiency, and ensure consistent appearance across product lines.

Introduction

The global pet food industry is experiencing rapid expansion, driven by rising pet ownership and the humanization of pets (treating pets like family). Pet owners are increasingly seeking premium, high-quality foods for their animals, and manufacturers face pressure to ensure products are not only nutritious but also visually appealing and consistent in appearance. Color has become a critical quality attribute in pet food: while the pets themselves may not judge their food by color, the pet owners (as buyers) certainly do. An off-color kibble or odd-looking pet treat can raise concerns about product freshness, safety, or ingredients, potentially damaging brand reputation.In this context, spectrophotometric color measurement offers a scientific way to monitor and control the color of pet foods throughout production. By objectively quantifying color, manufacturers can maintain tight quality control, ensure batch-to-batch consistency, and meet consumer expectations for appearance.

This white paper provides a technical overview of how integrating spectrophotometric color measurement enhances pet food manufacturing. We will cover the global pet food market landscape, explain why color matters at all production stages, discuss what color reveals about product quality, explore practical applications and challenges of color control (visual vs. instrumental methods), and review global measurement standards. We then recommend specific HunterLab solutions (notably the ColorFlex L2 and Aeros spectrophotometers) and compare the competitive landscape – illustrating why HunterLab is best-in-class.

Hypothetical case studies for dry kibble, wet food, and pet treats will demonstrate these concepts in action. Finally, a summary table of HunterLab product features and their Features, Advantages, and Benefits (FABs) is included for reference. The goal is a scientifically grounded understanding of pet food color measurement that manufacturing and quality professionals can apply to improve product quality and consistency.

Overview of the Global Pet Food Market and Key Application Areas

The pet food market is a large and growing sector worldwide. In 2021, the global pet food market was valued around USD $120 billion, and it is projected to exceed $170 billion by 2027, with a CAGR of ~5–7%. Growth is driven by trends like premiumization (demand for natural, organic, and health-focused recipes) and increased spending on pets’ well-being. North America holds the largest market share and is the biggest consumer of pet food globally, followed by Europe and the fast-rising Asia-Pacific region. Pet humanization trends in these regions have pet owners willing to pay more for high-quality, visually appealing pet foods that mirror human food standards.

Key product categories in pet food include dry foods, wet (canned/pouch) foods, and treats/snacks. Dry pet food (kibble) dominates the market by volume, thanks to its convenience and shelf stability. Wet foods and pet treats are growing segments, especially for owners of older pets or pets with special diets. Within these categories, there are specialized application areas such as functional and therapeutic diets (for weight management, digestive support, etc.), which are also expanding rapidly. Each of these product types presents unique challenges and requirements for quality control, including color consistency:

• Dry Kibble: Typically brown/tan pieces, often coated with palatants (flavor‐enhancing ingredients) or nutrients. Customers expect a uniform color per flavor or formulation.
• Wet Food: Stews or pâtés containing meat chunks, gravies, and vegetables. Color should signal appetizing freshness (e.g. rich meaty browns, natural ingredient colors) without unappetizing variation.
• Treats and Snacks: Biscuits, chews, or jerky treats come in various colors (often natural hues like golden baked colors or reddish meat tones). Consistent color is important for brand identity and consumer appeal.

Across all these segments, color measurement is emerging as a key quality indicator. Manufacturers globally are recognizing that controlling color consistently can differentiate premium products and reinforce consumer trust. The next sections will delve into why monitoring color at every stage of production is so important, and how it can be achieved.

Importance of Color Measurement at All Stages of Production

Color is not merely an aesthetic attribute in pet foods – it is intimately linked to quality, consistency, and even safety. Measuring color at each stage of production (from raw ingredients to finished product and even during shelf-life testing) provides several critical insights:

• Consistency & Quality Control: Uniform color across all kibbles or cans of food indicates proper mixing and processing. If color varies widely within a batch or between batches, it can signal formulation errors, uneven cooking, or other process issues. Pet owners also expect the product to look the same every time they purchase it; any noticeable color variation could make them suspect a bad batch or stale product. By checking color of intermediate and finished products, QA teams ensure each batch meets the established appearance standard before it ships.
• Indicator of Ingredient Quality: Many raw ingredients (meats, grains, vegetables, minerals) have natural color variations. However, certain color deviations can indicate subpar or wrong ingredients. For example, fresher animal proteins might impart a different hue than oxidized or lower-quality ones. Measuring the color of incoming raw materials and pre-mix blends helps verify they meet specifications before production continues. This way, if a meat meal or vitamin premix is darker or lighter than normal (potentially due to supplier variation or spoilage), it can be flagged and checked. Consistent ingredient color contributes to consistent final product color.
• Process Monitoring (Cooking & Drying): Critical processing steps like extrusion cooking, baking, or drying directly affect pet food color. For instance, kibble extruders and ovens induce Maillard browning reactions that give kibble its roasted color – too light might mean undercooked, while too dark could mean overcooked or burnt. Regularly measuring color during production (e.g. sampling kibbles off the line) ensures the product is being cooked at the correct temperature and time. If color starts drifting outside the target range, operators can adjust process settings in real time. In essence, color becomes a quick proxy for whether the process is in control (similar to an in-line quality parameter).
• Product Freshness and Shelf Life: Over time, pet foods can undergo color changes due to oxidation or spoilage, especially those high in fats and natural ingredients. For example, a dry kibble might gradually dull or develop a darker cast if fats oxidize, and a canned food might show surface discoloration if deteriorating. By monitoring color of retained samples over shelf life, manufacturers can detect early signs of degradation. A significant color shift during shelf-life testing could indicate the need for improved antioxidants or packaging to maintain quality. Thus, color measurement helps ensure the product will still look appetizing and “within spec” when the customer opens it, whether that’s days or months after production.
• Consumer Appeal & Brand Identity: Even though dogs and cats have limited color vision, pet owners are heavily influenced by the look of the food. A bright, rich, and natural-looking color tends to be associated with quality ingredients and better taste (in the owner’s mind). Manufacturers often design specific color appearances to differentiate flavors or formulations (for example, a certain shade for “beef” vs a different shade for “chicken” recipes). Maintaining those signature colors is crucial for brand consistency. Regular color checks ensure that each flavor of kibble or treat stays within its defined color range, supporting marketing claims and consumer expectations. In short, color consistency is part of the product’s identity, and measuring it helps protect that identity batch after batch.

By quantifying color at all stages – from incoming ingredients, in-process samples, finished goods, to shelf-life trials – manufacturers gain a comprehensive control over product appearance. This reduces the risk of substandard batches reaching the market and helps deliver a uniformly high-quality product that satisfies both pet and owner. In the next section, we will explore in more detail what specific information the color of pet food can reveal about its quality and condition.

What Color Reveals About Pet Food Quality

Color is often called a “mirror” of pet food quality because changes in color usually correlate with underlying changes in the product. Careful analysis of a pet food’s color can reveal a wealth of information about its formulation and processing. Some key quality insights that color provides include:

• Proper Cooking vs. Overcooking: The extent of browning in a kibble or treat is a direct result of cooking reactions (like the Maillard reaction). If kibble comes out much darker brown than usual, it likely was overcooked or subjected to higher temperatures than intended. This could mean a process deviation that might also affect nutrient levels (overcooking can destroy vitamins) or palatability. Conversely, a kibble that is paler than the standard could be undercooked or not dried properly, risking microbial growth due to higher moisture. Thus, measuring color helps confirm that each batch received the correct thermal processing. Manufacturers often establish a “golden brown” target range that optimizes both appearance and cooking sufficiency.
• Moisture and Dryness: Color and moisture content can be interrelated. For example, in semi-moist pet foods or soft treats, a slight color darkening might occur as the product dries out (water loss can concentrate colors). Uneven color could indicate uneven drying – e.g., darker edges of a treat might mean that part was over-dried. If a normally moist, juicy pet food (like a chunk in gravy) appears unusually dark or desiccated on the surface, it might suggest moisture loss or improper storage. Monitoring color alongside moisture tests helps ensure the product retains the intended texture and juiciness.
• Ingredient or Formula Changes: Pet food formulas are carefully controlled, but if an incorrect ingredient is added or a raw material lot deviates, color is often the first telltale sign. For instance, a batch made with a slightly different meat ratio or a different breed of grain might exhibit a color shift. Unexpected hues or speckles can signal contamination or mixing errors. In fact, regulators note that off-color is a strong indicator of potential hazards – the FDA considers abnormal color one of the primary cues in pet food complaint investigations. For example, a bluish or greenish tint in a meat product could indicate microbial spoilage or chemical contamination. By routinely measuring color, such issues can be caught immediately and investigated before products leave the plant.
• Oxidation and Rancidity: Oxidative spoilage of fats and oils in pet food not only produces off-odors but also often causes color darkening or yellowing. Fats that oxidize can take on a brownish cast and may also create dark spots on kibble. A slight red/brown shift in a poultry-based kibble over time, for instance, might suggest the fats are oxidizing (despite preservatives). Spectrophotometric color measurements can quantify these subtle shifts that human eyes might miss. A rising trend in a “browning index” or a drop in lightness (L*) over the product’s shelf life signals that improvements in antioxidant systems or packaging (e.g., nitrogen flushing) might be needed to preserve quality. In short, color stability is an indicator of shelf-life stability.
• Nutrient and Additive Effects: Some nutrients and additives affect color (intentionally or unintentionally). For example, high levels of certain vitamins or minerals might impart a faint color to kibbles; natural ingredients like beet pulp can lend a reddish hue. If a manufacturer reduces or increases such components, the color will reflect it. By measuring color, R&D teams can gauge the impact of formulation tweaks. Moreover, if artificial colors are not used (common in premium natural pet foods), controlling natural ingredient color becomes even more important to ensure each batch looks the same. Any deviation could reveal a quality control issue in mixing or dosing of an ingredient.

In summary, color acts as an early-warning system for pet food quality. It can expose processing deviations, formulation errors, or degradation that other tests might catch only later or in more costly ways. By interpreting the color data (e.g. a drop in L* value or shift in a*/b* coordinates), quality specialists can often pinpoint if a batch might have an issue with cooking, composition, or freshness. This allows for timely corrective actions – such as rejecting a batch before packaging, adjusting a process parameter, or checking ingredient quality – to maintain the highest quality standards.

Applications of Pet Food Color Measurement

Given the valuable information that color provides, pet food manufacturers apply color measurements in various ways across their operations. Some of the key applications of spectrophotometric color measurement in the pet food industry include:

• Quality Assurance (QA) in R&D and Product Development: When formulating a new pet food, developers will define a target color that is most appealing and characteristic (for example, a golden-brown kibble for a chicken flavor, or a reddish-meaty loaf for a beef wet food). Using a spectrophotometer during the R&D phase helps establish a “color standard” – a set of CIELAB values (or other color scale values) that the new product should hit. This target color becomes part of the product’s specification. Developers might iterate the cooking process or ingredient mix until measurements confirm the color is stable and reproducible. Once defined, these color standards are stored and used for routine QC comparisons during production. Spectrophotometric analysis in development ensures that the product’s appearance is optimized and will remain consistent when scaled to full production.
• Incoming Ingredient Inspection: Some pet food makers use color measurement on certain raw materials or premixes upon arrival. For instance, the color of fish meal or bone meal might correlate with its processing history or purity. A quick scan with a spectrophotometer can flag if an ingredient lot is outside the normal color range, prompting further inspection or lab tests. While not all ingredients have a defined color spec, for those that do (e.g., a dried kelp powder should be greenish-brown within a range), an objective check adds an extra layer of quality control.
• In-Process Monitoring and Adjustments: Modern pet food facilities may employ at-line or even in-line color measurements to keep production in control. For example, kibble exiting the dryer can be periodically sampled and measured. If the color is drifting lighter than the standard, operators might slow down the line or increase extrusion temperature to achieve a bit more browning. In wet food canneries, color of the gravy or mixture can be measured in a lab kitchen before filling to ensure it matches the established standard. This real-time or near-real-time monitoring allows proactive adjustments before a large volume goes out of spec. Some advanced systems even have in-line spectrophotometers that continuously scan product color on the conveyor and alert operators or adjust burners automatically. Whether manually or automatically, using color data for process feedback helps minimize waste and rework.
• Final Batch Release and QC Grading: Perhaps the most common application is at the end of production – batch approval based on color. Quality control labs measure samples from each production lot (kibble, cans, treats) to verify they fall within the acceptable color range (usually defined as a ΔE tolerance around the standard). If the batch’s color readings are within tolerance, it passes this aspect of QA. If not, the batch can be held back. In some cases, off-color batches might be reworked or mixed with others to correct the appearance, but often an out-of-spec color leads to rejection or downgrade (e.g., sold as a different tier product). Having quantifiable color metrics makes these decisions objective – there is a clear pass/fail criterion rather than a subjective visual call. This protects the brand from inconsistent-looking products reaching consumers.
• Regulatory and Food Safety Checks: While color itself is not a direct regulatory parameter (nutrient content and contaminants are the main ones), color measurement can support food safety programs. For example, if a HACCP (Hazard Analysis and Critical Control Points) plan identifies that overheating (which can be seen by color) could produce undesirable compounds, then color can be monitored as a critical quality attribute. Also, in the event of a recall investigation, documented color measurements might help indicate which batches were normal vs. which were problematic (since serious contamination or formulation mistakes often show color anomalies). Thus, systematic color data collection is a part of comprehensive quality records and traceability.
• Shelf-Life and Stability Studies: In R&D and quality assurance, companies conduct shelf-life studies where they store pet food samples under various conditions and periodically measure changes – including color changes. Spectrophotometers are used to track how the product’s color shifts over time (accelerated aging, real-time aging, etc.). If a product holds its color well for the intended shelf life, that’s a good sign of stability. If significant color degradation is measured (even if subtle), it could correlate with nutrient degradation or other quality losses. This application guides improvements in formulation or packaging (for instance, adding an oxygen absorber if color is not stable). It ultimately ensures that the product will look wholesome and appealing throughout its marketed shelf life.

In all these applications, spectrophotometric data provide a numeric, objective basis for decisions, rather than relying on subjective visual comparisons. By eliminating human guesswork, manufacturers can implement exacting color control protocols to enhance product appeal and consistency. The use of portable, benchtop, or in-line spectrophotometers has thus become integral to pet food QA programs, similar to how moisture or protein analyzers are used. In the following section, we discuss the challenges encountered in color control and how instrumental measurements compare to visual assessment in addressing those challenges.

Challenges in Color Control (Visual vs. Instrumental)

Ensuring consistent color in pet food is challenging due to both human and product factors. On the human side, visual color control is notoriously unreliable – different people may perceive color slightly differently, and ambient lighting can dramatically alter how a product’s color is seen. On the product side, pet foods are often non-uniform (irregular shapes, mixed ingredients, surface gloss etc.), which can confound simple color assessments. Here we examine these challenges and how instrumental color measurement helps overcome them:

• Limitations of Visual Inspection: Relying on the naked eye to judge pet food color has several drawbacks. Human color perception is subjective and can be influenced by fatigue, color blindness, or expectations. Under factory floor lighting (which might be fluorescent or uneven), a QA technician might think a batch “looks okay” even if it has drifted from the standard – or conversely might over-reject acceptable product due to a misleading light environment. Visual comparisons against a printed color chart or reference sample are only semi-quantitative at best. Moreover, small gradual changes in color often go unnoticed until they become large. An instrumental approach eliminates these uncertainties: modern spectrophotometers can detect even slight color variations consistently and express them in numeric terms. This provides an objective pass/fail criterion. By translating color into CIELAB values and ΔE differences, it removes guesswork and disagreement – if ΔE is above a set threshold, the batch is out of spec, period. Instruments also standardize the “lighting” (using defined illumination like D65) and viewing angle, so the measurement conditions are always the same, unlike visual checks.
• Inherent Product Variability: Pet foods pose a special challenge because they are often visually heterogeneous – think of a scoop of kibble containing pieces of slightly different shade, or a canned stew with chunks and gravy. A single kibble may not represent the batch’s overall color. If an inspector looks at a handful of kibble, their eyes might be drawn to the darkest or lightest pieces, leading to bias. Even using an instrument, one must ensure the measurement captures a representative average. Textured, irregular surfaces can also cause measurement variation – for example, light hitting a rough kibble surface may scatter unpredictably, and any gloss or oil coating can create shiny highlights that throw off the reading. The challenge is obtaining a consistent measurement that truly represents the perceived color of the product mass.
• Instrumental Solutions to Variability: To address this, instrumentation and methods have been developed. Spectrophotometers can be configured with integrating spheres or large sample ports to collect reflected light from multiple angles, helping to average out surface effects. Additionally, as recommended by HunterLab, samples can be measured in large dishes or cups and rotated between readings to average out differences between individual pieces. For example, a set of kibble might be poured into a sample cup; the instrument measures it, then the cup is rotated 90°, measured again, etc., and the results averaged. This rotation and averaging technique significantly improves the repeatability and representativeness of the color measurement for heterogeneous products. It’s essentially simulating what a consumer would see as the overall color impression of a bowl of kibble, rather than one piece.
• Geometry Considerations (45/0-degree geometry vs. Sphere): Another aspect is the instrument geometry. 45°/0° (or 0°/45°) geometry devices illuminate the sample at a fixed angle and observe at 0° (perpendicular) – this setup is very sensitive to surface appearance (gloss, texture) and is said to mimic human visual perception of color and gloss differences. In contrast, d/8° sphere geometry diffuses the light and collects from all angles, including gloss, which can better average the color of rough surfaces but might not correlate exactly to how the human eye perceives color differences due to gloss. Each approach has benefits. In pet food, 45/0-degree geometry instruments are often favored because they measure color as it appears to the eye (excluding glare from shiny coatings, for example). HunterLab’s popular ColorFlex series uses 45/0-degree geometry directional geometry precisely to capture the appearance of highly textured samples in a way that aligns with visual assessment. On the other hand, an instrument like HunterLab’s Aeros uses a directional approach combined with large area measurement and rotation, yielding extremely high accuracy on non-uniform samples by sheer statistical averaging. The point is that using the right instrument with the right geometry and sample presentation method is crucial – if not, instrumental readings could be inconsistent or not meaningful. This is why simply buying a spectrophotometer is not enough; one must also develop a robust measurement method for the given product (sample prep, averaging, calibration standards, etc.).
• Calibrations and Standardization: Maintaining instrument accuracy is another challenge. Spectrophotometers require regular calibration with reference standards (black and white tiles, perhaps green tiles for diagnostic checks). If calibration is skipped or done improperly, the color data can drift. Companies overcome this by instituting standard operating procedures: e.g., calibrate the instrument daily or every shift using certified standards, run diagnostic tiles (some instruments like HunterLab’s have built-in reminders and diagnostics for this). Following these practices ensures that color measurements remain precise and reliable over time, giving confidence that a measured change in color truly reflects a product change and not an instrument error.

In summary, visual color control in pet food is fraught with human bias and inconsistency, while instrumental control requires managing the complexities of the product’s appearance. By employing well-designed spectrophotometric methods – proper instrument geometry, representative sample presentation, averaging multiple readings, and rigorous calibration – manufacturers can surmount these challenges. Instruments do not tire or vary in judgment like humans, and they can quantify subtle changes that a person might overlook. The result is tighter color control, which translates to more consistent product quality. Next, we will discuss the measurement methods and standards used globally for pet food color, which formalize many of these practices.

Global Color Measurement Methods and Standards

Unlike some industries that have published standard methods for color, the pet food industry currently does not have an official, industry-wide color standard or regulatory method specific to pet food. Each company tends to develop its own internal procedures and acceptance criteria for color. However, there are common practices and reference standards that are widely adopted across the industry, which amount to a de facto global approach to pet food color measurement:

• Use of Spectrophotometers: Virtually all major pet food manufacturers and many ingredient suppliers use reflectance spectrophotometers to quantify color. These instruments are typically benchtop units in quality labs, although portable devices and on-line sensors are also used in some cases. The goal is to move away from subjective visual ratings to objective color data for QA/QC. Spectrophotometers measure the reflected light spectrum and convert it into color values under defined conditions, providing repeatable results across facilities and over time.
• CIELAB Color Space: The most common color scale used is the CIELAB system, which is an internationally recognized standard for quantifying color. In CIELAB, L* represents lightness (0 = black, 100 = white), a* represents the red-green axis, and b* represents the yellow-blue axis. Pet food colors (which are usually various browns, tans, reds) can be clearly described in this space. A specific product might have, for example, L* = 50, a* = +10, b* = +20 as its target. Companies often set tolerances in this color space – e.g., ΔE (total color difference) must be less than 2.0 from the standard for a batch to pass. CIELAB is preferred because it’s device-independent and correlates reasonably well with human vision differences. HunterLab instruments, for instance, typically report in CIELAB by default, and it’s noted that pet food producers commonly use CIELAB with D65 illuminant and 10° observer conditions as their standard measurement setup (D65 simulates daylight illumination, 10° observer is a standard human visual field parameter).
• Illuminant and Observer Standardization: As mentioned, D65/10° is a prevalent condition, meaning all color measurements are computed as if viewed under daylight (D65) and using the 10° standard observer model. This ensures that one plant’s data can be compared to another’s, or to a supplier’s data, without confusion. Other illuminants (like Illuminant A for incandescent light, or F2 for office fluorescent) might be used for specific purposes (e.g., checking appearance under store lighting), but D65 is the closest to a “global” default for pet food color measurement. By agreement, companies will specify which illuminant/observer were used whenever exchanging color data.
• Sample Preparation and Presentation: Because there is no uniform standard, techniques vary, but a common approach (recommended by HunterLab and others) is to fill a sample cup or dish completely with the product (to avoid any gaps or see-through) and measure in reflectance. For kibble or treats, that means filling a glass or plastic sample cup with as many pieces as possible, sometimes even mounding it and covering with a quartz glass plate. Some companies grind the kibble to a powder and measure the powder to eliminate variability – this can give a more uniform measurement, though it might not reflect the visual appearance perfectly. Many prefer measuring the intact product to capture appearance. In either case, consistency in sample prep is key: whether to compress the sample or not, how to orient pieces, etc., should be defined in a SOP.
• Multiple Readings and Averaging: As discussed in the previous section’s challenges, taking a single reading is usually insufficient for heterogeneous pet foods. Thus, industry practice is to take several readings on each sample (often rotating or mixing between readings) and average the results. For example, a lab might take 3–5 readings per sample (rotating 90° between each) and use the average CIELAB as the batch color. This helps overcome small inconsistencies and aligns with best practices. Some instruments, like the Aeros, actually automate this by automatically rotating the sample platform and capturing dozens of readings in seconds.
• Internal Color Standards: Companies maintain internal reference standards for color. This could be physical standards (retained product samples or color tiles) or simply stored numeric standards in software. For instance, after a new product is developed, the QC lab will measure the approved production sample and record its CIELAB as the “standard” in the spectro’s memory. HunterLab’s ColorFlex L2 can store thousands of standards with tolerances, which is useful for manufacturers with many product varieties. When measuring new batches, the instrument can automatically calculate a pass/fail comparison to the stored standard. There are no external, universal color reference materials specifically for pet food, so these internal standards are essentially the “calibration” for product color.
• Indices and Custom Scales: In some cases, specific indices might be used. For example, a producer might define a “brownness index” tailored to their products or use a standardized one if available from literature. Another example: measuring the color difference between surface and interior of a kibble (to check coating uniformity) might involve a custom method.

In summary, although no formal global standard exists for pet food color measurement, the industry converges on using modern spectrophotometers and the CIELAB color system under standard conditions, combined with rigorous sample handling procedures, to achieve consistent color control. Every manufacturer documents their method in detail (which instrument geometry, how sample is prepared, how many readings, etc.) to ensure reproducibility. Some may follow general guidance from food industry color standards or adapt ASTM/ISO methods (for example, ASTM has methods for color of granular materials which can be adapted). The trend is toward more harmonization as well – suppliers and co-manufacturers often have to align their color measurement approaches with those of the brand owners to ensure they’re speaking the same language.
With these methods in place, pet food companies can quantitatively manage color. Next, we will highlight specific HunterLab solutions that exemplify these best practices and are recommended for pet food color applications, and discuss why they stand out.

Recommended HunterLab Solutions (ColorFlex L2, Aeros) and Why

HunterLab, as a pioneer in color science instrumentation, offers several spectrophotometer solutions that are well-suited to the pet food industry’s challenges. Two highly recommended instruments for pet food color measurement are the ColorFlex L2 and the Aeros. Each addresses the needs of pet food manufacturers in different ways:

ColorFlex L2 – Compact 45/0-degree geometry Benchtop Spectrophotometer:

The ColorFlex L2 is a bench-top spectrophotometer with 45°/0° annular geometry—illuminating samples at a 45° angle 360-degrees around the sample and measuring at 0°—so it replicates how the human eye perceives color. As a cost-effective specialist for wet-food–only operations (and uniform dry foods or raw ingredients), it delivers accurate, budget-friendly performance using standard sample cups and directional optics. Its compact, intuitive design—with one-touch measurement and a touchscreen interface—streamlines routine QA on the shop floor. Despite its small size, the ColorFlex L2 handles a wide range of samples—including wet pet foods (gravies, pâtés), opaque solids, and powders—so a single instrument covers raw ingredients, in-process mixes, and finished products.

Under the hood, the ColorFlex L2 provides precise and rapid measurements. It uses a xenon flash lamp and diode array optics for fast spectral acquisition. It delivers direct pass/fail readouts against stored standards, which is perfect for QC – the instrument immediately tells if a sample is within tolerance. The L2 can store thousands of product standards and tolerances in its memory, enabling users to track many recipes and lots internally. It also supports data connectivity (USB, Ethernet) to output results to a PC or LIMS and even can print labels or reports directly. In essence, ColorFlex L2 offers scientific accuracy with practicality: it is small, robust, and economical, making it the go-to choice for many pet food companies’ routine color checks. Indeed, the industry has widely adopted the ColorFlex line (formerly ColorFlex EZ, now L2) because it’s cost-effective and convenient – it fits on any lab bench or could even be brought near the production line, and it uses a simple sample cup that accommodates most pet food samples.

The 45/0-degree geometry design ensures results that correlate with visual appearance, which gives manufacturers confidence that meeting the instrument’s criteria will also satisfy the customer’s eyes. In addition, its versatility means it can measure not just pet food but also related items like pet treats or even cat litter (which some pet food companies also color-check for consumer appeal) with the same device.

Aeros – Recommended for Mixed Dry & Wet Operations

HunterLab’s Aeros is a cutting-edge instrument ideal when a single instrument must handle all product types—dry, wet, treats—ensuring consistent QC workflows and reduced CAPEX on multiple devices. Aeros is purpose-built for non-uniform and difficult-to-measure products like pet foods. It is the only smart, non-contact spectrophotometer on the market designed for color quality control. Unlike traditional benchtop units that require filling a cup and touching a sample, the Aeros measures color without physical contact, which offers several advantages: you can measure products in their natural state (e.g., a pile of kibble or a scoop of wet food) without needing to grind or press them flat. This not only preserves sample integrity but also speeds up the process – no sample prep means quicker results and no cleaning between samples (important for wet or oily pet foods).

The Aeros features an industry-leading large measurement area. It can capture color over an area of 27.5 square inches in one rapid measurement (about 5 seconds). In practice, the Aeros performs 35 simultaneous readings across that area in 5 seconds using a dual rotating platform. This huge sample view and multiple reading average virtually eliminate the problem of sample non-uniformity. The instrument essentially creates a true statistical average of a large number of kibbles or chunks at once, yielding extremely representative color values. This is especially powerful for pet food, where small color differences piece-to-piece can otherwise require many manual measurements. Aeros’s ability to measure such a large sample in one go with automatic rotational averaging gives the highest accuracy and repeatability for heterogeneous products.

Another standout feature is the Aeros’s auto height-sensing and positioning system. The instrument has a sensor that detects the height of the sample and automatically adjusts the measurement distance/focus for optimal results. This means whether you have a thin layer of small kibbles or a heaped pile of larger treats, Aeros will accommodate it without manual intervention, ensuring consistency and preventing measurement errors due to distance. The non-contact design plus auto-height also reduce any risk of contaminating the instrument’s optics with sample debris – a big plus when measuring oily or powdery pet foods.

The Aeros is also a fully self-contained “all-in-one” spectrophotometer. It includes an integrated touchscreen computer and HunterLab’s modern Essentials software embedded, so no external PC is required to operate it. Users can run measurements, set up tolerances, and get results on the unit itself, and even directly print or export data via the built-in connectivity. It supports Ethernet/USB for data transfer and can email or network-share results, making it easy to integrate into quality systems. The user interface is designed to be intuitive and operator-friendly (with features like guided job setup and result visualization), minimizing training needed.

In summary, the Aeros is recommended for pet food applications where non-uniformity and sample handling are the biggest challenges. HunterLab specifically recommends Aeros as the ideal solution for pet foods because it handles the wide variety of product forms and textures with minimal effort. Whether measuring small kibbles, large kibbles, wet chunks, or even powders, Aeros provides accurate results without the need for different accessories or tedious prep. Its speed and large-area averaging improve efficiency and confidence in the measurements. Many pet food companies that demand the highest color consistency (for example, premium brands that emphasize natural appearance) find Aeros invaluable for its precision and time savings. By using Aeros, they can practically eliminate human variability and greatly reduce the chance of an off-color batch slipping through, since the instrument will catch even subtle shifts across a large sample.
In conclusion, HunterLab’s ColorFlex L2 and Aeros complement each other in pet food manufacturing environments:

• The ColorFlex L2 is an excellent all-around workhorse for routine QC on individual samples with a standard, contact measurement (often used with a sample cup). It’s cost-effective, easy to use, and correlates well with visual appearance, making it suitable for most daily checks and for companies with tighter budgets or space.
• The Aeros is a higher-end solution that excels in handling difficult samples and high throughput situations – ideal for companies that require the ultimate in accuracy for color-critical products or who want to measure products in a more production-like state (e.g., measuring random piles of product as seen by consumers).

Both instruments incorporate decades of HunterLab expertise and are backed by software and support tailored to color quality management. In the next section, we will briefly compare the competitive landscape of color measurement solutions and explain why HunterLab’s approach is considered best-in-class for pet food applications.

HunterLab Product Features and F.A.B.s (Features, Advantages, Benefits)

To further clarify the capabilities of HunterLab’s recommended instruments, the table below summarizes the key features of ColorFlex L2 and Aeros and the corresponding advantages and benefits (FABs) they offer for pet food color quality control:

HL Solution		Key Features	Advantages & Benefits
ColorFlex L2 (45°/0° geometry annular reflectance spectrophotometer)		45°/0° annular geometry (directional viewing)	Advantage: Measures color as the human eye perceives it (excluding gloss) on textured surfaces. Benefit: Ensures instrument readings correlate directly with the product’s visual appearance, leading to decisions that align with consumer perception.
		Compact benchtop design with touchscreen interface	Advantage: Small footprint, ergonomic and easy-to-use interface with color touchscreen. Benefit: Convenient fit in lab or production environments; minimal training required for operators, which improves adoption and reduces errors.
		Versatile sample measurement (opaque solids, liquids, powders, pellets)	Advantage: One instrument can handle a wide variety of pet food samples (kibble, wet food, sauces, ingredients) without special attachments. Benefit: Increases efficiency and cost-effectiveness by consolidating color testing to a single device for multiple product forms.
		One-touch measurement & on-board pass/fail analysis	Advantage: Simplified operation – press one button to measure and immediately see if sample is within tolerance. Benefit: Speeds up QC checks and eliminates guesswork; anyone on the QA team can quickly perform color control, ensuring consistent enforcement of standards.
		16G Memory for thousands of sample storage and measurements	Advantage: Stores product color standards and large batches of data internally, with USB/Ethernet connectivity for export. Benefit: Enables easy tracking of color trends over time and across products; facilitates documentation for audits and makes multi-product QC more organized. No PC needed to recall tolerances – reduces setup time for each measurement.
		Economical & robust (sealed spill-resistant case, solid-state optics)	Advantage: Affordable compared to high-end systems, and built to withstand routine use (e.g., accidental spills, dust) in plant labs. Benefit: Lowers the barrier to entry for accurate color control (strong ROI through relatively low capital cost). Durability means less downtime or maintenance costs over the instrument’s life.
Aeros (Non-contact rotating platform spectrophotometer)		Non-contact measurement with auto height positioning	Advantage: Measures samples without touching them, auto-adjusting to sample height. Benefit: No sample prep needed – products can be measured in their natural form (no grinding or compressing). This preserves sample integrity and eliminates cleanup between samples, greatly increasing throughput and hygiene (important for wet pet foods).
		Largest sample area: 27.5 sq. in. measured in ~5 seconds	Advantage: Captures color over an extremely large area via integrated rotating sample stage and multiple readings (up to 35 readings in one go). Benefit: Highly representative results for heterogeneous products – effectively averages out piece-to-piece color variation. Yields superior accuracy and repeatability for kibble, mixed diets, and other non-uniform samples, reducing the risk of batch false rejects or accepts due to sampling error.
		Rapid measurement and averaging (complete reading in 5 seconds)	Advantage: Very fast color assessment even for large samples. Benefit: Allows real-time or high-frequency color monitoring in production. Operators can check many samples per hour or even every batch without causing bottlenecks, enabling tighter process control and quick corrections if color deviates.
		Integrated touchscreen computer with smart software (EasyMatch Essentials)	Advantage: Built-in computing and easy UI – no external PC required to run the instrument; features like automatic data saving, printing, emailing results, etc., are included. Benefit: Simplifies the workflow – the instrument can be placed in a production area or lab as a standalone color station. Results can be shared instantly with QA databases or team members, supporting collaborative and timely decision-making.
		Rotating sample platform with spill tray; industrial-grade design	Advantage: Sample presentation is user-friendly – just pour the sample on the dish. The device’s robust build (touchscreen is industrial-hardened, optics protected from dust) handles the rigors of factory settings. Benefit: Hassle-free operation – minimal risk of operator error in sample handling. The sturdy design and included spill tray mean even messy samples (e.g., gravy-laden foods) can be measured with little risk to the instrument. Longevity and reliability in a production environment contribute to lower total cost of ownership.

Table: Key features of HunterLab’s ColorFlex L2 and Aeros spectrophotometers, with their advantages and benefits for pet food color quality control. These features enable accurate, efficient, and consistent color measurements, thereby improving quality assurance outcomes (fewer off-color batches, better process control, and enhanced consumer satisfaction)

Hypothetical Case Studies by Product Type

To illustrate how spectrophotometric color measurement can be applied in practice, let’s consider a few hypothetical (but realistic) case studies for different pet food product types: dry kibble, wet canned food, and pet treats. In each scenario, we’ll see how using HunterLab instruments and techniques helps ensure quality and consistency.

Case Study 1 – Dry Kibble Production: “Golden Brown Consistency in a Chicken & Rice Kibble”

A pet food company produces a premium chicken & rice dry dog food. The kibble is supposed to have a uniform golden-brown color. In one production run, the QA technician uses a ColorFlex L2 to sample kibble color at the dryer outlet every 30 minutes. The target Lab standard is stored in the instrument from previous successful batches. Mid-shift, the instrument alerts with a fail reading: the kibble L* (lightness) has increased by 2 units and the a* (redness) dropped slightly, resulting in a ΔE of 3.5, above the allowed 2.0. This indicates the kibble is coming out paler than it should. The technician immediately notifies production. Upon checking, they find the dryer temperature had drifted lower. They correct the temperature, and within 15 minutes the kibble color readings are back within spec. By catching this early, they prevent a large volume of under-toasted (light-colored) kibble from being produced. After cooling, QA measures composite samples from the entire batch (combining kibble from different times) and uses the Aeros for a comprehensive check. They pour a bowl of kibble under the Aeros, which in 5 seconds measures the average color of ~50 kibbles at once. The result confirms the overall batch color is within the acceptable range after adjustments. The batch is approved for packaging.

Outcome: The use of spectrophotometers allowed early detection of a process drift and ensured the final bagged product has a consistent appearance. Customers opening the bag will see evenly colored kibble, promoting trust in quality. (Had the color deviation not been caught, the pale kibble could have led to customer complaints or a scrapped batch on final inspection.)

Case Study 2 – Wet Canned Food: “Ensuring Appearances Match the Label Description”

Consider a manufacturer of canned cat food – a “Turkey Dinner” pâté that includes meat chunks in gravy. The product’s visual appeal is important; the gravy should be a rich brown and the meat pieces a hearty reddish-brown, signaling high protein content. The company has had an incident in the past where a formulation error made the gravy overly dark and opaque, which looked unappetizing and prompted customer questions. Now, in the pilot plant, the R&D team uses a ColorFlex L2 with a large reflectance cup to measure the gravy color and the overall blended pâté color for each new batch. In a hypothetical trial, suppose a micronutrient premix was dosed twice by accident – this premix contains iron, which can darken the product. The spectrophotometer reading for the gravy from the sample can shows L* = 20, a* = 8, b* = 6, whereas the standard gravy should be L* ~25. This drop in lightness is a red flag. The team halts production and investigates, discovering the double premix addition. They adjust the batch, and going forward implement a spectro check of gravy from the first filled cans of every batch as a standard QC step. Additionally, they make use of the Aeros for whole-can appearance: after gently mixing a can’s contents, they pour it into a petri dish and measure it non-contact. The Aeros reading covers both chunks and gravy together, simulating what a pet owner would see on a plate. For the “Turkey Dinner,” it consistently reads within the predefined tolerance that correlates with an appetizing color.

Outcome: By instrumenting color checks at multiple points (gravy phase and finished can), the manufacturer can ensure each production batch of wet food looks as intended – for example, a turkey dinner looks lighter brown than a beef dinner, but always uniform and “fresh”. This reduces the risk of mis-formulation going unnoticed. It also provides documentation; if consumers ever question color, the company has objective data showing it was within spec (and thus perhaps variations are due to natural ingredients, which they can explain positively).

Case Study 3 – Pet Treats: “Consistent Color Builds Brand Recognition for Dog Biscuits”

A small company makes artisanal baked dog biscuits in different flavors (pumpkin, salmon, blueberry). Each flavor has a distinct natural color (the salmon treats are pinkish, the pumpkin are orange-brown, etc.). They market them as dye-free; all color comes from real ingredients. Because of natural variability in ingredients, they’ve had issues where one batch of salmon treats came out a dull gray-pink (less salmon meal that time), and pumpkin treats sometimes vary from tan to deep orange based on pumpkin puree batches. To manage this, they invest in a ColorFlex L2. They create internal color standards for each flavor by averaging measurements of an ideal batch. For example, the salmon treats standard is a mild pink hue. On each production day, they measure 5 sample treats from the oven (placing them in the sample cup) and average the reading. If the color deviates beyond tolerance, they know to adjust the recipe. In a hypothetical scenario, suppose a new supplier’s salmon meal is lighter – the first batch with it reads significantly higher L* (lighter) and lower a* (less red) than the standard. QA catches this and works with R&D to add a bit of natural coloring (like beet juice, which is allowed) to bring the color closer to the usual pink. They verify with the spectrophotometer that the adjusted mix now matches the target within ΔE 1.0. For the pumpkin biscuits, they use the Aeros to handle their speckled appearance (oat and pumpkin bits create non-uniform color). The Aeros measures a large sample of mini biscuits at once, giving a robust average color. Over time, the company builds a database of color readings for each flavor and finds that with consistent ingredient sourcing and slight recipe tweaks guided by color data, their product color is much more uniform.

Outcome: The treats on store shelves now have a very consistent appearance, reinforcing brand identity (customers recognize the salmon treats by their signature pink shade). The company also benefits from reduced batch-to-batch variability – fewer off-color batches are rejected or reworked, saving costs. Instrumental color control has effectively become part of their artisan quality promise, ensuring that even without artificial dyes, the treats look appealing and reliable in color.

These case studies demonstrate how spectrophotometric color measurement can be integrated into different pet food production scenarios. In each case, the use of HunterLab instruments provided quantifiable feedback:

• In dry kibble, it prevented a process deviation from affecting final product.
• In wet food, it ensured formula consistency and product appeal.
• In treats, it maintained natural color consistency across batches.

By tailoring the measurement approach (ColorFlex vs. Aeros, at-line vs. lab, single vs. multiple readings) to the product, manufacturers can achieve tight color control without sacrificing efficiency. The hypothetical outcomes – fewer defects, stronger consumer confidence, and data-driven quality management – mirror what real companies attain when they invest in proper color quality programs.

Conclusion

Color measurement has proven to be a critical quality tool in pet food manufacturing, on par with nutritional, textural, and microbiological analysis. As we have explored, the color of pet food carries information about ingredient quality, process control, and even product safety. By implementing spectrophotometric color monitoring at all stages of production, manufacturers can ensure that every bag, can, or pouch of pet food not only meets nutritional specifications but also presents a consistent, appealing appearance to the customer. This consistency builds brand trust – pet owners come to expect that the kibble or treat they buy will look the same each time, signaling the reliable quality their pets enjoy.

Technically, achieving this requires surmounting challenges unique to pet foods (inhomogeneous mixtures, rough surfaces, natural color variation). The advancements in instrumentation – exemplified by HunterLab’s solutions – make it feasible to quantitatively control color in spite of these challenges. Modern spectrophotometers and colorimeters provide fast, objective, and reproducible measurements that far outperform subjective visual checks. With appropriate methods (like averaging and standardizing conditions), manufacturers can maintain tight color tolerances even in complex products. Importantly, because there are no universal industry color standards in pet food, the onus is on each company to establish internal standards and best practices – a task made much easier by the kind of knowledge and technology detailed in this paper.

In a global market where premiumization and consumer scrutiny are growing, color consistency can be a differentiator. Companies that deploy rigorous color quality control are less likely to face complaints like “this batch looks different” or “the food looked bad so I threw it out.” They also can optimize their processes – for instance, reducing overprocessing (and hence nutrient damage) by using color as an indicator to stop cooking at just the right point. All these factors contribute to better efficiency and less waste. Indeed, manufacturers often find that investment in color measurement pays for itself by cutting down the cost of reworks, rejects, and returns. It directly impacts the bottom line by improving yield and ensuring product acceptability.

In conclusion, spectrophotometric color measurement enhances pet food manufacturing by ensuring that every product looks as good as it is formulated to be. It marries the art of pet food making (delivering visually pleasing meals for pets) with the science of colorimetry. The result is a win-win: pets get food that is consistent and appealing (which encourages feeding and satisfaction), pet owners get the confidence of quality and safety through a product’s appearance, and manufacturers reap the benefits of efficiency, consistency, and a strong brand reputation.

By integrating the techniques and solutions discussed in this white paper, pet food producers and quality control teams can achieve new heights of quality control – where color, an attribute once considered subjective, becomes a controlled and optimized parameter in the production of world-class pet nutrition products.

Download the full document below to learn more.

To learn more about Color and Color Science in industrial QC applications, click here: Fundamentals of Color and Appearance

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