What the Data Hides: Spotting Errors and Recalls in a Sea of Dog Food Numbers
From flawed carbohydrate figures to a recalled chicken recipe, a deep dive into 128,736 hand-entered cells reveals how to compare cost, filter for allergies, and see past label claims to make smarter choices.
2,384 recipes, 128,736 cells — and every single one entered by hand
The table encompasses 2,384 recipes from 57 brands, organized across 54 columns with 128,736 cells, all manually entered. Formulas embedded in the spreadsheet compute dry-matter nutritional values and cost-per-calorie when manufacturers omit them, ensuring apples-to-apples comparisons across food types like dry kibble, wet cans, and fresh meals. For carbohydrate content, values are calculated by summing protein, fat, fiber, moisture, and ash—using estimated averages of 8% ash for dry foods and 2% for others when unspecified—and subtracting from 100%, though 39 recipes showed anomalous results like negative carbs. Readers can leverage built-in filter views to sort foods by metrics such as calories per cup or ounce, protein percentage, fat levels, or sodium content, with charts showcasing rankings like the most affordable at $0.0002 per calorie and the costliest at $0.30 per calorie. This allows owners to identify high-calorie options for active dogs, low-sodium choices for kidney concerns, or novel protein recipes for allergies, while navigating pricing through cost-per-calorie filters to fit budgets.
Cost per calorie — the only fair way to compare a can to a bag
A 12-ounce can of wet food and a 25-pound bag of kibble have almost nothing in common on price tags. Dollar amounts per ounce or per pound ignore the caloric differences between wet and dry foods. The comparison table calculates cost-per-calorie for every recipe by dividing the retail price by total calories in the package, offering a fair comparison metric. The most affordable food in the dataset costs roughly $0.0002 per calorie — a fraction of a cent — while the most expensive costs $0.30 per calorie. These values are often rounded to the fourth decimal place in the table for clarity. Owners can sort the spreadsheet by this column to view foods ranked from least to most expensive per calorie, aiding budget decisions across different food types. Since retailer prices vary, considering the general position in the spreadsheet rather than exact rankings is practical. Fresh meal-plan services, which bundle subscriptions around weekly deliveries, often obscure these figures behind monthly charges, making the standardized calculation especially useful for owners comparing options.
Thirty-nine recipes returned impossible carbohydrate numbers — a red flag for data accuracy
Most manufacturers list protein, fat, fiber, and moisture but omit carbohydrates, so the table calculates net carbs by subtracting those components plus ash from 100%. For 39 of the 2,385 recipes — 1.64% — the math produced negative or zero carbohydrate values, which is physically impossible. The likely culprit is incorrect data supplied by the manufacturer: protein and fat are reported as minimums, moisture and fiber as maximums, so a food could contain more protein or less moisture than listed, throwing the calculation off. The team flagged these anomalies rather than correcting them silently. They also used an average ash content of 8% for kibble and 2% for wet, raw, and fresh foods when the actual figure was unavailable, introducing a small margin of error for every recipe lacking that specification.
A freeze-dried chicken recipe was recalled for dangerously low thiamine
Nutritional deficiencies like low thiamine in dog food are not directly addressed in comprehensive comparison tables. The dog food comparison table includes 2384 recipes from 57 brands, with data on protein, fat, fiber, ash, sodium, and cost-per-calorie across 54 columns. It was created manually by listing major brands, collecting data, and implementing formulas for dry-matter calculations and cost-per-calorie. Sodium content was missing for about 55% of recipes, despite efforts to reach out to manufacturers. The table provides filter views for sorting foods by nutritional aspects such as protein, fat, carbs, and sodium, but it does not cover vitamin content like thiamine. Additionally, it includes hidden columns and charts for ranking foods by calories, protein, fat, carbs, and sodium, aiding in comparative analysis. Thus, identifying recalls relies on external sources, as consumer-accessible data may be incomplete.
Novel-protein and legume-free filters exist for dogs with allergies or sensitivities
The comparison table flags every recipe as containing conventional proteins (chicken, beef, pork, turkey, eggs) or novel proteins only (alligator, kangaroo, venison, rabbit, and similar alternatives). Owners managing food allergies — a common cause of itchy skin and chronic ear infections in dogs — can filter for novel-only recipes to build a shortlist of elimination-diet candidates. A separate column marks whether each recipe contains legumes, defined broadly enough to include ingredients like guar gum. Some owners avoid legumes because of ongoing questions about their role in diet-associated dilated cardiomyopathy investigations. Both filters let owners cross-reference against the nutritional data, so a dog that needs a novel protein, legume-free, moderate-fat recipe can be matched in seconds rather than hours of label reading.
Fat content ranges widely — and matters more than most owners realize
AAFCO requires a minimum of 5.5% dry-matter fat for adult maintenance and 8.5% for puppies, but the comparison table shows recipes that fall well below and climb well above those thresholds. High-fat formulas suit working dogs, those exposed to very cold temperatures, or underweight dogs in need of packing on weight. Low-fat options serve dogs with pancreatitis or those that are overweight. Most owners of healthy dogs simply need a food that meets the AAFCO minimum and keeps their dog at a healthy body weight — fat content can otherwise fall toward the bottom of their priority list. The table reports both as-fed and dry-matter fat values because direct comparison across food types requires removing moisture from the equation. A canned food and a kibble with identical as-fed fat percentages can differ dramatically once water is factored out. The ten highest-fat and ten lowest-fat recipes are ranked in separate charts, giving owners a quick reference without requiring them to calculate dry-matter numbers from the guaranteed analysis printed on every package.
Five types of food, one set of numbers — why dry-matter values change everything
Different dog food formats—dry kibble, canned wet food, freeze-dried, frozen raw, and fresh refrigerated meals—vary widely in moisture content, making direct nutritional comparisons tricky. The comparison table addresses this by providing both as-fed values (the food as it comes) and dry-matter values (nutrients with water removed). For instance, a wet food might show lower protein as-fed but higher dry-matter protein once moisture is accounted for. Built-in formulas automatically calculate dry-matter values from as-fed data, and vice versa, covering protein, fat, fiber, carbohydrates, and sodium across 2,384 recipes from 57 brands. Owners can sort the table by dry-matter protein to identify truly high-protein foods, or by dry-matter sodium to find low-sodium options for dogs with kidney concerns. This mechanism lets users compare a 12-ounce can of wet food against a 25-pound bag of kibble on equal footing, focusing on nutrient density that informs practical feeding decisions.
The spreadsheet is a starting point — the shortlist is where real decisions happen
Owners interact with the 128,736-cell spreadsheet, which spans 54 columns and 2,384 recipes, by applying filters for protein, fat, sodium, and cost-per-calorie to shrink options to a shortlist. Nutritional data appears in as-fed and dry-matter formats, with dry-matter values calculated to enable direct comparison between wet and dry foods. The table flags AAFCO life stages and marks incomplete rows, indicating where values are estimates versus manufacturer-confirmed. Filter views rank recipes by characteristics like calories per ounce or carbohydrate content, revealing extremes such as the top 10 lowest-calorie wet foods or highest-protein dry foods. Built-in formulas compute overall cost-per-calorie and dry-matter percentages, accounting for factors like ash content estimates. After filtering, owners narrow choices further by considering ingredient lists, brand trust, or taste preferences, using these metrics to assess value across all food types.
Compiled from published reference material: www.k9ofmine.com
