CMB_2026v16n2

Computational Molecular Biology 2026, Vol.16, No.2, 129-145 http://bioscipublisher.com/index.php/cmb 143 Gong L., Yu M., and Kollias S., 2023, Optimizing crop yield and reducing energy consumption in greenhouse control using PSO-MPC algorithm, Algorithms, 16(5): 243. https://doi.org/10.3390/a16050243 Gong L., Yu M., Jiang S., Cutsuridis V., and Pearson S., 2021, Deep learning based prediction on greenhouse crop yield combined TCN and RNN, Sensors, 21(13): 4537. https://doi.org/10.3390/s21134537 Harel D., Fadida H., Slepoy A., Gantz S., and Shilo K., 2014, The effect of mean daily temperature and relative humidity on pollen, fruit set and yield of tomato grown in commercial protected cultivation, Agronomy, 4(1): 167-177. https://doi.org/10.3390/agronomy4010167 Hemming S., Zwart F., Elings A., Petropoulou A., and Righini I., 2020, Cherry tomato production in intelligent greenhouses-Sensors and AI for control of climate, irrigation, crop yield, and quality, Sensors, 20(22): 6430. https://doi.org/10.3390/s20226430 Higashide T., 2022, Review of dry matter production and growth modelling to improve the yield of greenhouse tomatoes, The Horticulture Journal, 91(2): 143-157. https://doi.org/10.2503/hortj.UTD-R019 Kasimatis C., Psomakelis E., Katsenios N., Papatheodorou M., Apostolou D., and Efthimiadou A., 2025, Industrial tomato yield prediction using machine learning models, Smart Agricultural Technology, 11: 100920. https://doi.org/10.1016/j.atech.2025.100920 Kim S., Jeong J., and Kim S., 2025, Morphological analysis-based yield modeling in greenhouse grown cherry tomato (Solanum lycopersicum) under prolonged heat stress, Frontiers in Plant Science, 16: 1730694. https://doi.org/10.3389/fpls.2025.1730694 Kolapkar M.S., and Sayyad S.R., 2021, Greenhouse microclimate study for humidity, temperature and soil moisture using agricultural wireless sensor network system, Advances in Communication and Computational Technology, 668: 278-289. https://doi.org/10.1007/978-981-16-0493-5_25 Kürklü A., Pearson S., and Felek T., 2025, Climate change impacts on tomato production in high-tech soilless greenhouses in Türkiye, BMC Plant Biology, 25(1): 307. https://doi.org/10.1186/s12870-025-06307-1 Lee K., Rajametov S., Jeong H., Cho M., Lee O., Kim S., Yang E., and Chae W., 2022, Comprehensive understanding of selecting traits for heat tolerance during vegetative and reproductive growth stages in tomato, Agronomy, 12(4): 834. https://doi.org/10.3390/agronomy12040834 Li Y., Henke M., Zhang D., Wang C., and Wei M., 2024, Optimized tomato production in Chinese solar greenhouses: The impact of an east-west orientation and wide row spacing, Agronomy, 14(2): 314. https://doi.org/10.3390/agronomy14020314 Li Y., Jian Y., Wang S., Liu X., Li W., Arıcı M., Zhang L., Li W., and Cao Y., 2024, Spatial temperature distribution and ground thermal storage in the plastic greenhouse: An experimental and modeling study, Journal of Energy Storage, 75: 109938. https://doi.org/10.1016/j.est.2023.109938 Lin D., Wei R., and Xu L., 2019, An integrated yield prediction model for greenhouse tomato, Agronomy, 9(12): 873. https://doi.org/10.3390/agronomy9120873 Lin Y., Fang S., Kang L., Chen C., Yao M., and Kuo B., 2024, Combining recurrent neural network and sigmoid growth models for short-term temperature forecasting and tomato growth prediction in a plastic greenhouse, Horticulturae, 10(3): 230. https://doi.org/10.3390/horticulturae10030230 Liu H., Shao M., and Yang L., 2023, Photosynthesis characteristics of tomato plants and its’ responses to microclimate in new solar greenhouse in North China, Horticulturae, 9(2): 197. https://doi.org/10.3390/horticulturae9020197 Liu H., Zhao H., Liu S., Tian Y., Li W., Wang B., Hu X., Sun D., Wang T., Wu S., Wang F., Zhu N., Tao Y., and Lei X., 2025, When tomatoes hit the winter: A counterattack to overwinter production in soft-shell solar greenhouses in North China, Horticulturae, 11(4): 436. https://doi.org/10.3390/horticulturae11040436 Locatelli S., Barrera W., Verdi L., Nicoletto C., Marta D., and Maucieri C., 2024, Modelling the response of tomato on deficit irrigation under greenhouse conditions, Scientia Horticulturae, 324: 112770. https://doi.org/10.1016/j.scienta.2023.112770 Miller G., Beery A., Singh P., Wang F., Zelingher R., Motenko E., and Lieberman-Lazarovich M., 2021, Contrasting processing tomato cultivars unlink yield and pollen viability under heat stress, AoB Plants, 13(4): plab046. https://doi.org/10.1093/aobpla/plab046 Nassar J.M., Khan S.M., Villalva D.R., Nour M.M., Almuslem A.S., and Hussain M.M., 2018, Compliant plant wearables for localized microclimate and plant growth monitoring, npj Flexible Electronics, 2(1): 24. https://doi.org/10.1038/s41528-018-0039-8 Lin D., Wei R., and Xu L., 2019, An integrated yield prediction model for greenhouse tomato, Agronomy, 9(12): 873. https://doi.org/10.3390/agronomy9120873

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