Department of Tissue and Cell Culture, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Mahdasht Road, P.O. Box 31535-1897, Karaj, Iran.
Kohgiluyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), C.P. 75891-72050. Blvd. Keshavarzi, Yasouj, Iran.
Protoplasma. 2019 Sep;256(5):1317-1332. doi: 10.1007/s00709-019-01379-x. Epub 2019 May 4.
Doubled haploids, subsequent to haploid induction, have wide range of applications in basic and applied plant studies. Various parameters can affect the efficiency of haploid induction through an anther culture of tomato. The hybrid system of image processing-artificial neural network (ANN) was used to better understand callus induction and regeneration in an anther culture of tomato. The effect of parameters such as plant genotype, the concentrations of 2,4-dichlorophenoxyacetic acid (2,4-D) and kinetin (Kin) plant growth regulators, the concentration of gum arabic (GA) additive, the cold pretreatment duration, and flower length on callus induction percentage and number of regenerated calli in an anther culture of tomato were studied using multiple linear regression (MLR) and ANN models. The precise flower bud length was measured using an image processing technique. The 4',6-diamidino-2-phenylindole (DAPI) analysis showed that the flowers with 5-6.9 mm length had the highest percentage of the mid- to late-uninucleate microspore stage. The best ANN model for both callus induction percentage and number of regenerated calli was a model with one hidden layer, 12-15 neurons in the first hidden layer, Levenberg-Marquardt learning algorithm, and Tan-Sigmoid transfer function in hidden layer, based on the root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R) statistics. The scatter plot of measured values versus the predicted values showed the superiority of the ANN to MLR model to predict the callus induction percentage in an anther culture of tomato. The sensitivity analysis of MLR and ANN models revealed the plant genotype and 2,4-D concentration as the most important factors affecting both callus induction percentage and number of regenerated calli. Since tomato is a recalcitrant plant to androgenesis-based pathway of haploid induction, therefore the results of the present study can be helpful to develop an efficient haploid induction protocol in tomato through an anther culture pathway.
加倍单倍体,继单倍体诱导之后,在基础和应用植物研究中有广泛的应用。各种参数可以通过番茄花药培养来影响单倍体诱导的效率。图像处理-人工神经网络 (ANN) 的杂交系统用于更好地理解番茄花药培养中的愈伤组织诱导和再生。使用多元线性回归 (MLR) 和 ANN 模型研究了植物基因型、2,4-二氯苯氧乙酸 (2,4-D) 和激动素 (Kin) 植物生长调节剂浓度、阿拉伯树胶 (GA) 添加剂浓度、冷预处理时间和花长等参数对番茄花药培养中愈伤组织诱导率和再生愈伤组织数量的影响。使用图像处理技术精确测量花蕾长度。4',6-二脒基-2-苯基吲哚 (DAPI) 分析表明,长度为 5-6.9mm 的花朵具有最高比例的中期至晚期单核小孢子阶段。对于愈伤组织诱导率和再生愈伤组织数量,最佳的 ANN 模型是具有一个隐藏层、第一个隐藏层中的 12-15 个神经元、Levenberg-Marquardt 学习算法和 Tan-Sigmoid 传递函数的模型,基于均方根误差 (RMSE)、平均绝对误差 (MAE) 和决定系数 (R) 统计数据。测量值与预测值的散点图显示,ANN 优于 MLR 模型,可预测番茄花药培养中的愈伤组织诱导率。MLR 和 ANN 模型的敏感性分析表明,植物基因型和 2,4-D 浓度是影响愈伤组织诱导率和再生愈伤组织数量的最重要因素。由于番茄是对基于雄核发育途径的单倍体诱导具有抗性的植物,因此本研究的结果有助于通过花药培养途径开发番茄高效的单倍体诱导方案。