Faculty of Agricultural Sciences and Technology, Sivas University of Science and Technology, Sivas, Turkey.
Department of Agricultural Biotechnology, Faculty of Agriculture, Erciyes University, Kayseri, Turkey.
Plant Mol Biol. 2024 Mar 25;114(2):33. doi: 10.1007/s11103-024-01427-y.
Industrial hemp (Cannabis sativa L.) is a highly recalcitrant plant under in vitro conditions that can be overcome by employing external stimuli. Hemp seeds were primed with 2.0-3.0% hydrogen peroxide (HO) followed by culture under different Light Emitting Diodes (LEDs) sources. Priming seeds with 2.0% yielded relatively high germination rate, growth, and other biochemical and enzymatic activities. The LED lights exerted a variable impact on Cannabis germination and enzymatic activities. Similarly, variable responses were observed for HO × Blue-LEDs combination. The results were also analyzed by multiple regression analysis, followed by an investigation of the impact of both factors by Pareto chart and normal plots. The results were optimized by contour and surface plots for all parameters. Response surface optimizer optimized 2.0% HO × 918 LUX LEDs for maximum scores of all output parameters. The results were predicted by employing Multilayer Perceptron (MLP), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost) algorithms. Moreover, the validity of these models was assessed by using six different performance metrics. MLP performed better than RF and XGBoost models, considering all six-performance metrics. Despite the differences in scores, the performance indicators for all examined models were quite close to each other. It can easily be concluded that all three models are capable of predicting and validating data for cannabis seeds primed with HO and grown under different LED lights.
工业大麻（Cannabis sativa L.）在体外条件下是一种高度抗逆性植物，可以通过外部刺激来克服。将大麻种子用 2.0-3.0%的过氧化氢（HO）引发，然后在不同的发光二极管（LED）光源下培养。用 2.0%的 HO 引发种子可以获得相对较高的发芽率、生长率和其他生化和酶活性。LED 灯对大麻的发芽和酶活性有不同的影响。同样，HO 和蓝 LED 组合也观察到了不同的反应。结果还通过多元回归分析进行了分析，然后通过 Pareto 图和正态图分析了两个因素的影响。用等高线和曲面图对所有参数进行了优化。响应面优化器优化了 2.0%HO×918 LUX LED，以获得所有输出参数的最高分数。通过使用多层感知器（MLP）、随机森林（RF）和极端梯度提升（XGBoost）算法对结果进行了预测。此外，还使用了六种不同的性能指标来评估这些模型的有效性。考虑到所有六种性能指标，MLP 模型的性能均优于 RF 和 XGBoost 模型。尽管得分存在差异，但所有检查模型的性能指标彼此非常接近。可以很容易地得出结论，所有这三种模型都能够预测和验证经过 HO 引发并在不同 LED 光下生长的大麻种子的数据。
