Data · dataset · 2025
Preliminary Qualitative Analysis of Plant-based Industrial Food Processing Waste in Anand City, Gujarat, India
Listed in Teesside University Research Data Repository
This dataset forms the bedrock for a preliminary qualitative analysis centered on industrial food processing waste, specifically focusing on sweet corn and tomato by-products.
Description
These waste materials were meticulously collected directly from hot processing lines within various food industries situated in and around Anand City, Gujarat, India. This collection method ensures that the samples represent the waste generated under actual industrial operational conditions, providing a realistic perspective on their composition immediately post-processing.
Upon collection, the raw waste samples underwent a crucial pre-treatment step: they were thoroughly dried to remove excess moisture and then carefully stored. This preparation was essential to prevent degradation and maintain sample integrity, ensuring their suitability for subsequent comprehensive analyses. A key aspect of this dataset involves the qualitative phytochemical screening of these dried waste materials, a methodology adapted from Shaikh et al. (2020).
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The study specifically looked for the qualitative detection of alkaloids, carbohydrates, phenolic compounds, sugars, and proteins. Beyond the organic components, the dataset also encompasses a detailed screening of essential elemental nutrients. This includes carbon (C), hydrogen (H), nitrogen (N), phosphorus (P), and potassium (K), collectively referred to as NPK, which are vital for agricultural applications and biochemical conversions.
The elemental analysis for carbon, hydrogen, and nitrogen was meticulously performed using a high-precision Element Analyzer Instrument (Model: Elemetar Analysensysteme GmbH, Germany, Make: Unicube), a technique consistent with the methods described by Firdaus et al. (2018). For phosphorus and potassium, the analysis was conducted using Wavelength Dispersive X-Ray Fluorescence (WD-XRF) (Model: AxiosMAX, Make: PANalytical, Netherland).
These advanced analytical instruments, housed at the Sophisticated Instrumentation Centre for Applied Research and Testing (SICART) in Vallabh Vidyanagar, ensured accurate and reliable elemental quantification, building upon established protocols like those referenced by Horf et al. (2021). The fundamental information derived from this study, encompassing both phytochemical and elemental composition, offers crucial insights into the chemical profile of industrial food processing wastes in the Anand region.
This comprehensive understanding is vital for moving beyond simple waste disposal towards innovative waste utilization strategies. Ultimately, the outcomes of this preliminary qualitative analysis provide a foundational dataset that can significantly aid in estimating and enhancing the overall quality and utility of plant-based industrial food processing waste, not just at a regional level within Gujarat but also on a broader national and global scale, fostering a more sustainable and circular economy within the food industry.
Links
Where it is published
- DOI doi.org/10.17632/3z7c48bdjd.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Economics & Finance · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Industrial biotechnology 75%
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/3z7c48bdjd.1 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:3106 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (75%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |