CMB_2026v16n2

Computational Molecular Biology 2026, Vol.16, No.2, 129-145 http://bioscipublisher.com/index.php/cmb 145 Sun W., Coules A., Zhao C., and Lu C., 2025, A lettuce growth model responding to a broad range of greenhouse climates, Biosystems Engineering, 251: 1-16. https://doi.org/10.1016/j.biosystemseng.2025.01.008 Talukder M., All N., Bappy H., Haque M., Abul M., Molla H., Alam M., Mosharaf M., Limon S., and Quzzaman S., 2025, Fluctuation of ambient day-night temperature influences morphological traits, floral characters, fruit yield and quality of summer tomato genotypes grown in hydroponics, New Zealand Journal of Crop and Horticultural Science, 53(4): 2731-2754. https://doi.org/10.1080/01140671.2025.2504209 Tatsumi K., Igarashi N., and Xiao M., 2021, Prediction of plant-level tomato biomass and yield using machine learning with unmanned aerial vehicle imagery, Plant Methods, 17(1): 27. https://doi.org/10.1186/s13007-021-00761-2 Tong Z., Zhang S., Yu J., Zhang X., Wang B., and Zheng W., 2023, A hybrid prediction model for CatBoost tomato transpiration rate based on feature extraction, Agronomy, 13(9): 2371. https://doi.org/10.3390/agronomy13092371 Ugbe L., Ushie P., Morebise A., and Akomaye F., 2025, Assessing the impact of climate change on the growth and yield of tomato (Lycopersicon esculentum) cultivars in Obudu, northern Cross River State, Nigeria, World Journal of Advanced Research and Reviews, 28(1): 3508. https://doi.org/10.30574/wjarr.2025.28.1.3508 Xu D., Xu L., Wang S., Wang M., Jin J., and Shi C., 2024, Rule-based year-round model predictive control of greenhouse tomato cultivation: A simulation study, Information Processing in Agriculture, 12(2): 356-370. https://doi.org/10.1016/j.inpa.2024.11.001 Xu K., Guo X., He J., Yu B., Tan J., and Guo Y., 2022, A study on temperature spatial distribution of a greenhouse under solar load with considering crop transpiration and optical effects, Energy Conversion and Management, 266: 115277. https://doi.org/10.1016/j.enconman.2022.115277 Yadav D., Meena Y., Bairwa L., Singh U., Bairwa S., Choudhary M., and Singh A., 2021, Morphological, physiological and biochemical response to low temperature stress in tomato (Solanum lycopersicumL.): A review, International Journal of Bio-resource and Stress Management, 12(5): 462-471. https://doi.org/10.23910/1.2021.2480 Yadav R., Kumar R., Kalia P., Jain V., and Varshney R., 2014, Effect of high day and night temperature regimes on tomato (Solanum lycopersicum) genotypes, Indian Journal of Agricultural Sciences, 84(2): 228-233. https://doi.org/10.56093/ijas.v84i2.38052 Zepeda A., Vorage S., Van Mourik S., Heuvelink E., and Marcelis L., 2026, Too cold or too warm? Modelling seed set and fruit mass based on the effect of temperature on pollen quality, AoB Plants, 18(1): plag004. https://doi.org/10.1093/aobpla/plag004 Zhang H., Sun X., and Song W., 2023, Physiological and growth characteristics of tomato seedlings in response to low root-zone temperature, HortScience, 58(5): 596-603. https://doi.org/10.21273/hortsci16924-22 Zhang Q., Zhang X., Yang Z., Huang Q., and Qiu R., 2022, Characteristics of plastic greenhouse high-temperature and high-humidity events and their impacts on facility tomatoes growth, Frontiers in Earth Science, 10: 848924. https://doi.org/10.3389/feart.2022.848924 Zhou B., Lastiri D., Wang N., Yang Q., and Van Henten E., 2025, An opensource indoor climate and yield prediction model for Chinese solar greenhouses, Biosystems Engineering, 250: 244-262. https://doi.org/10.1016/j.biosystemseng.2024.12.007

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