ENGINEERING PROPERTIES AND SHELF LIFE OF FRESHLY HARVESTEDINDIAN KIWI CULTIVARS FOR FACILITATING PRIMARY PROCESSING
Bibliographic record
Abstract
The present study deals with the engineering properties of three Indian kiwi cultivars.These engineering properties will facilitate the farmers, and industry personals involve in handling, packaging and transportation of fresh harvested fruit.The complete information on physical, mechanical, thermal and biochemical properties of three Indian kiwi cultivars were presented in this paper.This knowledge may be utilized to design and develop modern machineries for primary processing, and packaging of fresh kiwifruit.The shelf life study data also provided in this paper which will help the growers and processors for safe handling, packaging and transportation of the fruit.The physical dimensions viz.length, width and thickness, mean diameters, surface area, volume, sphercity, static coefficient of friction on different materials were measured for all the three Indian cultivars.Significant (p<0.05)difference for aspect ratio with Hayward and Monty was observed.Bruno was bigger and heavier than others cultivars.Mean diameters (GMD, AMD and EMD) were varying less than 10%.The mechanical properties viz.firmness, hardness, adhesiveness, adhesive force and total positive area for peeled and unpeeled Hayward, Bruno and Monty.Thermal properties i.e. thermal conductivity, specific heat capacity, thermal diffusivity and latent heat of fusion and biochemical properties i.e. moisture, pH, titrable acidity and total soluble solids were also measured in this study.Significant (p<0.05) for total positive area was observed for Bruno with Hayward and Monty was observed.No significant (p>0.05)difference for moisture and sphericity was observed between Hayward and Monty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".