Non-destructive Mathematical Modeling Techniques for Fruit Volume Estimation: A Systematic Review and Meta-analysis Article Swipe
Neetu Rani
,
Kiran Bamel
,
S. K. Garg
,
R. Nath
,
Ishita Mishra
,
Vaibhav Bhatt
,
Sneha Gupta
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.18805/ijare.a-6311
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.18805/ijare.a-6311
In the recent past, the global fruit industry has experienced incredible growth, fueled by growing per capita earnings and greater health consciousness for fresh produce. Fruit volume plays a key role in precise yield estimation, improving productivity, sorting and packaging. This systematic review accompanied by meta-analysis sheds light on the non-destructive techniques and algorithms used in the estimation of fruit volume through mathematical modeling. A total of 50 studies published between 2008 and 2023 were reviewed in this work in 2023 at Shivaji College (University of Delhi), Delhi. Reviewing the studies analytically, the modeling techniques adopted by researchers usually belonged to categories of either statistical modeling or geometric modeling. An I-square statistic of 88.48% was obtained in the heterogeneity analysis demonstrating the extreme diversity between the above categories. Egger’s and Begg’s tests were also performed for examining the presence of publication bias, however they did not turn up any compelling evidence of its occurrence. The comparison between different categories with their coefficient of determination (R2) between estimated and actual volume was also established using effect measures like odds ratios, risk ratiosand weighted odds ratios while sensitivity analysis was performed to assess the changes in result. This study also elucidates the strengths and shortcomings of different non-destructive techniques while using statistical methods to identify the performance of individual studies and to find the most suitable approach for estimating fruit volume. The meta-analysis concluded that the studies following statistical approach offered better R2 values as compared to other methodologies.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.18805/ijare.a-6311
- https://arccarticles.s3.amazonaws.com/OnlinePublish/Final-article-attachemnt-with-doi-A-6311-6089603e9087340b9bdcbbb1.pdf
- OA Status
- diamond
- References
- 48
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4405769612
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4405769612Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.18805/ijare.a-6311Digital Object Identifier
- Title
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Non-destructive Mathematical Modeling Techniques for Fruit Volume Estimation: A Systematic Review and Meta-analysisWork title
- Type
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reviewOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-12-25Full publication date if available
- Authors
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Neetu Rani, Kiran Bamel, S. K. Garg, R. Nath, Ishita Mishra, Vaibhav Bhatt, Sneha GuptaList of authors in order
- Landing page
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https://doi.org/10.18805/ijare.a-6311Publisher landing page
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https://arccarticles.s3.amazonaws.com/OnlinePublish/Final-article-attachemnt-with-doi-A-6311-6089603e9087340b9bdcbbb1.pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://arccarticles.s3.amazonaws.com/OnlinePublish/Final-article-attachemnt-with-doi-A-6311-6089603e9087340b9bdcbbb1.pdfDirect OA link when available
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Meta-analysis, Estimation, Volume (thermodynamics), Mathematics, Applied mathematics, Veterinary medicine, Statistics, Computer science, Econometrics, Medicine, Pathology, Engineering, Physics, Thermodynamics, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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48Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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