Evidence map›Paper›PMID 39468886›Full record

ReviewJournal of food science2024

Measuring palatability of pet food products: Sensory components, evaluations, challenges, and opportunities.

Natalia Calderón, Brittany L White, Han-Seok Seo

Abstract readReview
In one paragraph

Review in Journal of food science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Gaps and Controversies in Feline Food Palatability.Animals : an open access journal from MDPI · 2026
    Review
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Natalia CalderónDepartment of Food Science, University of Arkansas, Fayetteville, Arkansas, USA.
Brittany L WhiteSimmons Pet Food, Siloam Springs, Arkansas, USA.
Han-Seok SeoDepartment of Food Science, University of Arkansas, Fayetteville, Arkansas, USA.ORCID https://orcid.org/0000-0001-9845-8199

Funding

U.S. Department of Agriculture
6 · The paper itself

Abstract

The pet food industry is a growing business launching a variety of new products in the market. The acceptability or preference of pet food samples has traditionally been measured using either one-bowl or two-bowl tests. Academic researchers and professionals in the pet food industry have explored other methods, including the cognitive palatability assessment protocols and the ranking test, to evaluate more than two samples. A variety of approaches and perspectives were also utilized to predict palatability and key sensory attributes of pet foods, including descriptive sensory analysis by human-trained panelists and pet food caregivers' perceptions of pet food. This review article examined a range of testing methods for evaluating the palatability of pet foods, specifically targeting products for dogs and/or cats. It outlined the advantages and disadvantages of each method. Additionally, the review provided in-depth insights into the key sensory attributes of pet foods and the methodologies for assessing palatability. It also explored pets' behavioral responses and facial expressions in relation to different pet foods. Furthermore, this review discussed current challenges and future opportunities in pet food development, including the use of instrumental analyses and artificial intelligence-based approaches.

Indexed as

Animal FeedFood PreferencesPetsTasteAnimalsCatsDogsHumansacceptabilitypalatabilitypet foodpreferencesensory

Identifiers

PMID39468886
PMCPMC11673441

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.