Abstract
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 (R2) 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.
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Abbreviations
- ANN:
-
Artificial neural network
- BBBM:
-
Biotechnology-based breeding method
- CIP:
-
Callus induction percentage
- DH:
-
Doubled haploid
- GA:
-
Gum arabic
- IP:
-
Image processing
- Kin:
-
Kinetin
- MAE:
-
Mean absolute error
- MLP:
-
Multi-layer perceptron
- MLR:
-
Multiple linear regression
- NRC:
-
Number of regenerated calli
- PGRs:
-
Plant growth regulators
- TCB:
-
Tissue culture based
- QTL:
-
Quantitative trait loci
- RMSE:
-
Root mean square error
- R 2 :
-
Coefficient of determination
- 2,4-D:
-
2,4-Dichlorophenoxyacetic acid
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M.N. conceived the idea, performed the anther culture and laboratory works along with ANN and IP analyses, and wrote the manuscript; M.E.S contributed in the idea and corrected the manuscript; M.A. contributed in ANN, IP, and other statistical analyses; and M.O. conducted the DAPI experiments.
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Niazian, M., Shariatpanahi, M.E., Abdipour, M. et al. Modeling callus induction and regeneration in an anther culture of tomato (Lycopersicon esculentum L.) using image processing and artificial neural network method. Protoplasma 256, 1317–1332 (2019). https://doi.org/10.1007/s00709-019-01379-x
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DOI: https://doi.org/10.1007/s00709-019-01379-x