Evidence map›Paper›PMID 38843189›Full record

ArticlePloS one2024

Non-destructive identification of varieties of Hawaii-grown avocados using near-infrared spectroscopy: Feasibility studies using bench-top and handheld spectrometers.

Jemma M Godbout, Nicolas C Ladizinsky, Serenity Harris, Melissa L Postler, Xiuxiu Sun, Tracie Matsumoto, Peishih Liang

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Jemma M GodboutUniversity of Hawaii at Hilo, Pacific Internship Program for Exploring Science, Hilo, Hawaii, United States of America.
Nicolas C LadizinskyUSDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.
Serenity HarrisUniversity of Hawaii at Hilo, Department of Physics and Astronomy, Hilo, Hawaii, United States of America.
Melissa L PostlerUSDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.
Xiuxiu SunUSDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.
Tracie MatsumotoUSDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.
Peishih LiangUSDA, Agricultural Research Service, U.S. Pacific Basin Agricultural Research Center, Hilo, Hawaii, United States of America.ORCID 0000-0003-2690-5249

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Avocados are an important economic crop of Hawaii, contributing to approximately 3% of all avocados grown in the United States. To export Hawaii-grown avocados, growers must follow strict United States Department of Agriculture Animal and Plant Health Inspection Service (USDA-APHIS) regulations. Currently, only the Sharwil variety can be exported relying on a systems approach, which allows fruit to be exported without quarantine treatment; treatments that can negatively impact the quality of avocados. However, for the systems approach to be applied, Hawaii avocado growers must positively identify the avocados variety as Sharwil with APHIS prior to export. Currently, variety identification relies on physical characteristics, which can be erroneous and subjective, and has been disputed by growers. Once the fruit is harvested, variety identification is difficult. While molecular markers can be used through DNA extraction from the skin, the process leaves the fruit unmarketable. This study evaluated the feasibility of using near-infrared spectroscopy to non-destructively discriminate between different Hawaii-grown avocado varieties, such as Sharwil, Beshore, and Yamagata, Nishikawa, and Greengold, and to positively identify Sharwil from the other varieties mentioned above. The classifiers built using a bench-top system achieved 95% total classification rates for both discriminating the varieties from one another and positively identifying Sharwil while the classifier built using a handheld spectrometer achieved 96% and 96.7% total classification rates for discriminating the varieties from one another and positively identifying Sharwil, respectively. Results from chemometric methods and chemical analysis suggested that water and lipid were key contributors to the performance of classifiers. The positive results demonstrate the feasibility of NIR spectroscopy for discriminating different avocado varieties as well as authenticating Sharwil. To develop robust and stable models for the growers, distributors, and regulators in Hawaii, more varieties and additional seasons should continue to be added.

Indexed as

PerseaSpectroscopy, Near-InfraredFeasibility StudiesFruitHawaii

Identifiers

PMID38843189
PMCPMC11156329

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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.