Plasma chemical method of extending the apples shelf life
Bibliographic record
Abstract
Article Details: Received: 2020-12-21 | Accepted: 2021-02-10 | Available online: 2021-09-30 https://doi.org/10.15414/afz.2021.24.03.202-205 The efficiency of using ozone and plasma chemical technology to reduce the concentration of ethylene impurities to extend the shelf life of apples has been studied. The ozone concentration was measured by sensors located in the experimental box. The ethylene concentration was measured with an ICA56 meter (in the experimental box) and monitored by sampling from the circulation lines of both boxes. The ICA56 meter use electrochemical sensor with ethylene resolution 0.2 ppm. This sensor have cross sensitivities for CO (40%), ethanol (72%), CO2 (0%), H2 S (220%) and its reason use control method of measuring ethylene. Control samples were analyzed with a Thermo Scientific Trace 1310 gas chromatograph with a flame ionization detector. The chromatograph was pre-calibrated with calibration gas mixtures with ethylene content of 10 and 100 ppm. It has been shown that Gala, McIntosh and Jonathan apples are stored several times better when the air in which apples are stored is treated with a plasma-chemical system. After 40 days of storage in the control box, the weight of apples acceptable for consumption (absence of rot and mold) was for varieties Gala – 3.3 kg (31%), Jonathan – 2.1 kg (15.6%), McIntosh – 2 kg (20%). In the experimental boxing varieties Gala – 12.1 kg (66.4%), Jonathan – 10.2 kg (59.3%), McIntosh – 9.3 kg (52.5%). Thus, the combined plasma-ozone method of air treatment of stored apples has shown high efficiency and has prospects for use. Keywords: plasma treatment, barrierless plasma chemical reactor, ethylene References Bagher, H. et al. (2020). Effect of Cold Plasma on Quality Retention of Fresh-Cut Produce. Journal of Food Quality, 8. https://doi.org/10.1155/2020/8866369 Crocker, W. et al. (1935). Similarities in the effects of ethylene and the plant auxins. Contrib. Boyce Thompson inst., 7, 231–248. Concello, A. et al. (2005). Effect of chilling on ethylene production in eggplant fruit. Food Chemistry, 92, 63–69. https://doi.org/10.1016/j.foodchem.2004.04.048 Dong, L. et al. (2002). Effect of 1-methylcyclopropene on ripening of ‘Canino’ apricots and ‘Royal Zee’ plums. Postharvest Biology and Technology, 24, 135–145. https://doi.org/10.1016/S0925-5214(01)00130-2 Golden, K. (2014). Ethylene in Postharvest Technology: A Review. Asian Journal of Biological Sciences, 7(4), 135–143. https://doi.org/10.3923/ajbs.2014.135.143 Golota, V. et al. (2003). Patent US #6,544,486 B2 Date 04/18/2003. Golota, V. et al. (2018), Decomposition of ethylene in low temperature plasma of barrierless discharge. Problems of Atomic Sci. and Technol. Ser. Plasma Electronics and New Methods of Acceleration, №4 (116), 160–163. http://dspace.nbuv.gov.ua/handle/123456789/147342 Golota, V. et al. (2018). The use of ozone technologies in grain storage. Problems of Atomic Science and Technology, 116(4), 185–188. http://dspace.nbuv.gov.ua/handle/123456789/149325 Ma, L. et al. (2017). Recent developments in novel shelf life extension technologies of fresh-cut fruits and vegetables. Trends in Food Science & Technology, 64, 23–38. https://doi.org/10.1016/j.tifs.2017.03.005 Miller, F. A. et al. (2013). Review on Ozone-Based Treatments for Fruit and Vegetables Preservation. Food Eng Rev, (5), 77–106. https://doi.org/10.1007/s12393-013-9064-5 Nakatsuka, A. et al. (1998). Differential Expression and Internal Feedback Regulation of 1-Aminocyclopropane-1- Carboxylate Synthase, 1-Aminocyclopropane-1-Carboxylate Oxidase, and Ethylene Receptor Genes in Tomato Fruit during Development and Ripening. Plant Physiol, 118, 1295–1305. https://doi.org/10.1104/pp.118.4.1295 Skog, L. J. et al. (2001). Effect of ozone on qualities of fruits and vegetables in cold storage. Canadian Journal of Plant Science, 81(4), 773–778. https://doi.org/10.4141/P00-110 Taran, G.V. et al. (2019). Plasma-chemical methods for control of biotic contaminants. Problems of Atomic Sci. and Technol. Ser. Plasma Electronics and New Methods of Acceleration, 2019, №4 (122), 198–202. https://vant.kipt.kharkov.ua/ARTICLE/ VANT_2019_4/article_2019_4_198.pdf
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".