ArticleJournal of food science and technology2022
Determination of pizzas quality and acceptability by physic-mechanical tests.
Article in Journal of food science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Image-Based Machine Learning for Predicting Acceptability Limits in Frozen Pizza Shelf Life.Foods (Basel, Switzerland) · 2026Article
- Analysis of the Physical and Structure Characteristics of Reformulated Pizza Bread.Foods (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The growing need for developing more efficient and sustainable technologies for the processing of bakery products leads to the need for replacing the current subjective methodology by an instrumental method to evaluate the quality of these products. In this work, relevant physic characteristics that define the quality and acceptability of pizzas were identified, and instrumental methods were established to evaluate them. Cooking quality of the pizza base was established through rapid visco analysis and scanning electron microscopy. The physic attributes considered of the pizza base with and without toppings were final cooking temperature, specific volume, water content, color, and texture. Aiming to validate the applicability of the instrumental methods, we prepared well-accepted pizzas, using three different oven technologies, and carried out a sensory test with 60 non-trained panelists. We observed that the proposed method is sensitive enough to identify differences in the quality of pizzas produced by the oven technologies. However, those variations were not enough to be recognized by participants of the sensory panel. The values of pizza attributes obtained in this work could be used as a baseline of comparison for pizzas produced by new and more efficient cooking technologies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1007/s13197-021-05148-8).
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.