References
- Aliasgarian, S., Ghassemzadeh, H.R., Moghaddam, M., & Ghaffari, H. (2015). Mechanical damage of strawberry during harvest and postharvest operations. Acta Technologica Agriculturae, 18, 1-5. https://doi.org/10.1515/ata-2015-0001
- Auzanneau, N., Weber, P., Kosińska-Cagnazzo, A., & Andlauer, W. (2018). Bioactive compounds and antioxidant capacity of Lonicera caerulea berries: Comparison of seven cultivars over three harvesting years. Journal of Food Composition and Analysis, 66, 81-89. https://doi.org/10.1016/j.jfca.2017.12.006
- Basara, O., & Gorzelany, J. (2024). Assessment of Selected Chemical and Morphological Properties of Lonicera var. kamtschatica and Lonicera var. emphyllocalyx Treated with Gaseous Ozone. Molecules, 29, 3616. https://doi.org/10.3390/molecules29153616
- Becker, R., & Szakiel, A. (2019). Phytochemical characteristics and potential therapeutic properties of blue honeysuckle Lonicera caerulea L.(Caprifoliaceae). Journal of Herbal Medicine, 16, 100237.
- Bolandnazar, E., Rohani, A., & Taki, M. (2019). Energy consumption forecasting in agriculture by artificial intelligence and mathematical models. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 42(13), 1618–1632. https://doi.org/10.1080/15567036.2019.1604872
- Bożek, M. (2012). The Effect of Pollinating Insects on Fruiting of Two Cultivars of Lonicera caerulea L. Journal of Apicultural Science, 56(2), 5-11. https://doi.org/10.2478/v10289-012-0018-6
- Česonienė, L., Labokas, J., Jasutienė, I., Šarkinas, A., Kaškonienė, V., Kaškonas, P., Kazernavičiūtė, R., Pažereckaitė, A., & Daubaras, R. (2021). Bioactive Compounds, Antioxidant, and Antibacterial Properties of Lonicera caerulea Berries: Evaluation of 11 Cultivars. Plants, 10, 624. https://doi.org/10.3390/plants10040624
- Cevher, E.Y., & Yildirim, D. (2022). Using Artificial Neural Network Application in Modeling the Mechanical Properties of Loading Position and Storage Duration of Pear Fruit. Processes, 10, 2245.
- Clay, D. E., Brugler, S., & Joshi, B. (2024). Will artificial intelligence and machine learning change agriculture: A special issue. Agronomy Journal, 116, 791–794. https://doi.org/10.1002/agj2.21555
- Contigiani, E. V., Jaramillo-Sánchez, G., Castro, M. A., Gomez, P. L., & Alzamora, S. M. (2018). Postharvest quality of strawberry fruit (Fragaria x Ananassa Duch cv. Albion) as affected by ozone washing: Fungal spoilage, mechanical properties, and structure. Food and Bioprocess Technology, 11, 1639-1650.
- Duarte-Molina, F., Gómez, P.L., Castro, M.A., & Alzamora, S.M. (2016). Storage quality of strawberry fruit treated by pulsed light: Fungal decay, water loss and mechanical properties. Innovative Food Science & Emerging Technologies, 34, 267-274. https://doi.org/10.1016/j.ifset.2016.01.019.
- Dziedzic, E., Błaszczyk, J., Bieniasz, M., Dziadek, K., & Kopeć, A. (2020). Effect of modified (MAP) and controlled atmosphere (CA) storage on the quality and bioactive compounds of blue honeysuckle fruits (Lonicera caerulea L.). Scientia Horticulturae, 265, p.109226. https://doi.org/10.1016/j.scienta.2020.109226.
- El Bilali, A., Moukhliss, M., Taleb, A., Nafii, A., Alabjah, B., Brouziyne, Y., Mazigh, N., Teznine, K., & Mhamed, M. (2022). Predicting daily pore water pressure in embankment dam: Empowering Machine Learning-based modeling. Environmental Science and Pollution Research, 29, 47382–47398. https://doi.org/10.1007/s11356-022-18559-7.
- Elibox, W., Meynard, C., & Umaharan, P. (2017). Fruit volume and width at harvest can be used to predict shelf life in pepper (Capsicum chinense Jacq.). Tropical Agriculture, 94(2), 122-131. https://doi.org/0041-3216/2017/020122-10.
- Gawroński, J., Hortynski, J., Kaczmarska, E., Dyduch-Sieminska, M., Marecki, W., & Witorozec, A. (2014). Evaluation of phenotypic and genotypic diversity of some Polish and Russian blue honeysuckle (Lonicera caerulea L.) cultivars and clones. Acta Scientiarum Polonorum Hortorum Cultus, 13, 157-169.
- Geasa, M. M. M. (2022). Effect of mechanical damage on tomato fruits under storage conditions. Journal of Soil Sciences and Agricultural Engineering, 13(3), 93-98. https://doi.org/10.21608/jssae.2022.124035.1053.
- Gorzelany, J., Belcar, J., Kuźniar, P., Niedbała G., & Pentoś K. (2022). Modelling of Mechanical Properties of Fresh and Stored Fruit of Large Cranberry Using Multiple Linear Regression and Machine Learning. Agriculture, 12, 200. https://doi.org/10.3390/agriculture12020200.
- Hosseini Monjezi, P., Taki, M., Abdanan Mehdizadeh, S., Rohani, A., & Ahamed, M.S. (2023). Prediction of Greenhouse Indoor Air Temperature Using Artificial Intelligence (AI) Combined with Sensitivity Analysis. Horticulturae, 9, 853. https://doi.org/10.3390/horticulturae9080853.
- Hu, M., Dong, Q., Liu, B., & Opara, U.L. (2016). Prediction of mechanical properties of blueberry using hyperspectral interactance imaging. Postharvest Biology and Technology, 115, 122-131, https://doi.org/10.1016/j.postharvbio.2015.11.021.
- Huang, W., Wang, X., Zhang, J., Xia, J., & Zhang, X. (2023). Improvement of blueberry freshness prediction based on machine learning and multi-source sensing in the cold chain logistics. Food Control, 145, 109496. https://doi.org/10.1016/j.foodcont.2022.109496.
- Kula, M., & Krauze-Baranowska, M. (2016). Blue Honeysuckle (Lonicera caerulea L.)-The current state of phytochemical research and biological activity. Post Fitoter, 17, 111-118.
- Kuźniar, P., Belcar, J., Zardzewiały, M., Basara, O., & Gorzelany, J. (2022). Effect of Ozonation on the Mechanical, Chemical, and Microbiological Properties of Organically Grown Red Currant (Ribes rubrum L.) Fruit. Molecules, 27, 8231. https://doi.org/10.3390/molecules27238231.
- Leisso, R., Jarrett, B, & Miller, Z. (2021b). Haskap Preharvest Fruit Drop and Stop-drop Treatment Testing. HortTechnology, 31(6), 820-827. https://doi.org/10.1139/cjps-2021-0138.
- Leisso, R., Jarrett, B., Richter, R., & Miller, Z. (2021a). Fresh haskap berry postharvest quality characteristics and storage life. Canadian Journal of Plant Science, 101(6), 1051-63.
- Lufu, R., Ambaw, A., & Opara, U. L. (2020). Water loss of fresh fruit: Influencing pre-harvest, harvest and postharvest factors. Scientia Horticulturae, 272, 109519. https://doi.org/10.1016/j.scienta.2020.109519.
- Lv, Y., Tahir, I.I., & Olsson, M.E. (2019). Effect of ozone application on bioactive compounds of apple fruit during short-term cold storage. Scientia Horticulturae, 253, 49–60. https://doi.org/10.1016/j.scienta.2019.04.021.
- Martinez Romero, D., Bailén, G., Serrano, M., Guillen, F., Valverde, J.M., Zapata, P., Castillo, S., & Valero, D. (2007). Tool to maintain postharvest fruit and vegetable quality through the inhibition of ethylene action: a review. Critical reviews in food science and nutrition, 47 (6), 543-560. https://doi.org/10.1080/10408390600846390.
- Miller, F.A., Silva, C.L., & Brandao, T.R. (2013). A review on ozone-based treatments for fruit and vegetables preservation. Food Engineering Reviews, 5(2), 77-106.
- Moggia, C., Beaudry, R.M., Retamales, J.B., & Lobos, G.A. (2017). Variation in the impact of stem scar and cuticle on water loss in highbush blueberry fruit argue for the use of water permeance as a selection criterion in breeding. Postharvest Biology and Technology, 132, 88-96. https://doi.org/10.1016/j.postharvbio.2017.05.019.
- Mohsen, A., Shabankareh, S.H., Kiapey, A., Rezaeiasl, A., Mahmoodi, M.J., & Torshizi, M.V. (2024). Assessing kiwifruit quality in storage through machine learning. Journal of Food Process Engineering, 47. https://doi.org/10.1111/jfpe.14681.
- Nawaz, M., & Babar, M.I.K. (2024). IoT and AI: a panacea for climate change-resilient smart agriculture. Discover Applied Sciences, 6, 517. https://doi.org/10.1007/s42452-024-06228-y.
- Ngcobo, M.E., Delele, M.A., Opara, U.L., Zietsman, C.J., & Meyer C.J. (2012). Resistance to airflow and cooling patterns through multi-scale packaging of table grapes. International Journal of Refrigeration, 35(2), 445-452. https://doi.org/10.1016/j.ijrefrig.2011.11.008.
- Niedbała, G., Kurek, J., Świderski, B., Wojciechowski, T., Antoniuk, I., & Bobran K. (2022). Prediction of Blueberry (Vaccinium corymbosum L.) Yield Based on Artificial Intelligence Methods. Agriculture, 12, 2089. https://doi.org/10.3390/agriculture12122089.
- Ochmian, I., Skupien, K. Grajkowski, J., Smolik, M., & Ostrowska, K. (2012). Chemical composition and physical characteristics of fruits of two cultivars of blue honeysuckle (Lonicera caerulea L.) in relation to their degree of maturity and harvest date. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 40, 155-162. https://doi.org/10.15835/nbha4017314.
- Pan, H., Yang, J., Shi, Y., & Li, T. (2015). BP neural network application model of predicting the apple hardness. Journal of Computational and Theoretical Nanoscience, 12(9), 2802–2807. https://doi.org/10.1166/jctn.2015.4180.
- Peipei, Z., Bingbing, S., Hongwei, Ji., Wang, H., Yuexuan, L., Zhang, X., & Chunhua, R. (2022). Nondestructive Prediction of Mechanical Parameters to Apple Using Hyperspectral Imaging by Support Vector Machine. Food Analytical Methods, 1, 1397-1406.
- PN-90/A-75101-03:1990. Fruit and vegetable preserves. Preparation of samples for physicochemical tests. Determination of dry matter content by the gravimetric method. Polski Komitet Normalizacyjny.
- Ranieri, A., Petacco, F., Castagna, A., & Soldatini, G.F. (2000). Redox state and peroxidase system in sunflower plants exposed to ozone. Plant Science, 159(1), 159-167.
- Ren, B., Zhang, L., Chen, J., Wang, H., Bian, C., Shi, Y., Qin, D., Huo, J., & Gang, H. (2023). Response of Abscission Zone of Blue Honeysuckle (Lonicera caerulea L.) Fruit to GA3 and 2,4-D Spray Application. Agronomy, 13, 2937. https://doi.org/10.3390/agronomy13122937.
- Ropelewska, E. (2022). Assessment of the Influence of Storage Conditions and Time on Red Currants (Ribes rubrum L.) Using Image Processing and Traditional Machine Learning. Agriculture, 12, 1730. https://doi.org/10.3390/agriculture12101730.
- Saeidirad, M. H., Rohani, A., & Zarifneshat, S. (2013). Predictions of viscoelastic behavior of pomegranate using artificial neural network and Maxwell model. Computers and Electronics in Agriculture, 98, 1-7. https://doi.org/10.1016/j.compag.2013.07.009
- Satitmunnaithum, J., Kitazawa, H., Arofatullah, N.A., Widiastuti, A.,.Kharisma, A.D., Yamane, K., Tanabata, S., & Sato, T. (2022). Microbial population size and strawberry fruit firmness after drop shock-induced mechanical damage. Postharvest Biology and Technology, 192, p.112008. https://doi.org/10.1016/j.postharvbio.2022.112008
- Senica, M., Stampar, F., & Mikulic-Petkovsek, M. (2018). Blue honeysuckle (Lonicera cearulea L. subs. edulis) berry; a rich source of some nutrients and their differences among four different cultivars. Scientia Horticulturae, 238, 215–221. https://doi.org/10.1016/j.scienta.2018.04.056
- Son, N., Chen, C., Cheng, Y., Toscano, P., Chen, C., Chen, S., Tseng, K., Syu, C., Guo, H., & Zhang, Y. (2022). Field-scale rice yield prediction from Sentinel-2 monthly image composites using machine learning algorithms. Ecological Informatics, 69, 101618. .https://doi.org/10.1016/j.ecoinf.2022.101618.
- Tappi, S., Ragni, L., Tylewicz, U., Romani, S. Ramazzina, I., & Rocculi, P. (2017). Browning response of fresh-cut apples of different cultivars to cold gas plasma treatment. Innovative Food Science & Emerging Technologies, 53, 56-62. https://doi.org/10.1016/j.ifset.2017.08.005.
- Yu M., Li S., Zhan Y., Huang Z., Lv J., Liu Y., Quan X., Xiong J., Qin D., & Huo J. (2023). Evaluation of the Harvest Dates for Three Major Cultivars of Blue Honeysuckle (Lonicera caerulea L.) in China. Plants, 12, 3758. https://doi.org/10.3390/plants12213758.
- Zapałowska, A., Matłok, N., Zardzewiały, M. Piechowiak, T., & Balawejder, M. (2021). Effect of Ozone Treatment on the Quality of Sea Buckthorn (Hippophae rhamnoides L.). Plants, 10, 847. https://doi.org/10.3390/plants10050847.
- Zhu, C., Zhang, L., Gao, Y., Qin, D., & Huo, J. (2022). Two novel blue honeysuckle (Lonicera caerulea L.) cultivars: Lanjingling and Wulan. HortScience, 57(9), 1145-1147. https://doi.org/10.21273/HORTSCI16674-22.
- Zhu, S., Liu, J., Yang, Q., Jin, Y., Zhao, S., Tan, Z., ... & Zhang, H. (2023). The impact of mechanical compression on the postharvest quality of ‘Shine Muscat’grapes during short-term storage. Agronomy, 13(11), 2836.
- Ziaratban, A., Azadbakht, M., Ghasemnezhad, A. (2016). Modeling of volume and surface area of apple from their geometric characteristics and artificial neural network. International Journal of Food Properties, 20(4), 762–768. https://doi.org/10.1080/10942912.2016.1180533