RESULTS: This study was done to assess the hereditary assorted variety of selected genotypes of Capsicum annuum based on their morphophysiological and yield traits in two planting seasons. The biochemical properties, capsaicinoid content (capsaicin and dihydrocapsaicin), total phenolics content and antioxidant action determination of unripe and ripe chili pepper fruits were carried out in dry fruits. AVPP9813 and Kulai 907 were observed to have high fruit yields, with 541.39 and 502.64 g per plant, respectively. The most increased genotypic coefficient of variation (GCV) and phenotypic coefficient of variation (PCV) were shown by the fruit number per plant (49.71% and 66.04%, respectively). High heritability was observed in yield characters viz-à-viz fruit weight, length and girth and indicated high genetic advance. Eight groups were obtained from the cluster analysis. For the biochemical analysis, the capsaicinoid content and total phenolic content were high in Chili Bangi 3 at unripe and ripe fruit stages, while for antioxidant activity SDP203 was the highest in ripe dry fruit.
CONCLUSION: Higher GCV and PCV, combined with moderate to high heritability and high hereditary progress, were seen in number of fruit per plant, fruit yield per plant and fruit weight per fruit. These findings are beneficial for chili pepper breeders to select desirable quantitative characters in C. annuum in their breeding program. © 2018 Society of Chemical Industry.
RESULTS: In this research, chili pest and disease features extracted using the traditional approach were compared with features extracted using a deep-learning-based approach. A total of 974 chili leaf images were collected, which consisted of five types of diseases, two types of pest infestations, and a healthy type. Six traditional feature-based approaches and six deep-learning feature-based approaches were used to extract significant pests and disease features from the chili leaf images. The extracted features were fed into three machine learning classifiers, namely a support vector machine (SVM), a random forest (RF), and an artificial neural network (ANN) for the identification task. The results showed that deep learning feature-based approaches performed better than the traditional feature-based approaches. The best accuracy of 92.10% was obtained with the SVM classifier.
CONCLUSION: A deep-learning feature-based approach could capture the details and characteristics between different types of chili pests and diseases even though they possessed similar visual patterns and symptoms. © 2020 Society of Chemical Industry.
RESULTS: Yield per plant showed positive and highly significant (P ≤ 0.01) correlations with most of the characters studied at both the phenotypic and genotypic levels. By contrast, disease incidence and days to flowering showed a significant negative association with yield. Fruit weight and number of fruits exerted positive direct effect on yield and also had a positive and significant (P ≤ 0.01) correlation with yield per plant. However, fruit length showed a low negative direct effect with a strong and positive indirect effect through fruit weight on yield and had a positive and significant association with yield.
CONCLUSION: Longer fruits, heavy fruits and a high number of fruits are variables that are related to higher yields of chili pepper under tropical conditions and hence could be used as a reliable indicator in indirect selection for yield. © 2016 Society of Chemical Industry.
RESULTS: In this experiment, thick and short hairy roots were induced at all induction sites of C. annuum while thin, elongated hairy roots appeared mostly at wound sites of C. frutescens. Overall, the hairy root induction percentages of C. frutescens were higher compared with C. annuum. Hairy root initiation was observed earliest using radicles (1st week), followed by cotyledons (2nd week), and hypocotyls (3rd week). Cotyledon explants of both species had the highest induction frequency with all strains compared with the other explants types. Strains ATCC 13333 and ATCC 15834 were the most favourable for C. frutescens while ATCC 43056 and ATCC 43057 were the most favourable for C. annuum. The interactions between the different explants and strains showed significant differences with p-values < 0.0001 in both Capsicum species.
CONCLUSIONS: Both Capsicum species were amenable to A. rhizogenes infection and hairy root induction is recommended for use as an alternative explants in future plant-based studies.