Madhusmita Dishri

Bio: Madhusmita Dishri is an academic researcher from VIT University. The author has contributed to research in topics: Yield (engineering). The author has an hindex of 1, co-authored 2 publications receiving 3 citations.

Inheritance of fruit attributes in chilli pepper

Abstract: Capsicum annuum has been known for the amount of variability present in the genus for fruit traits and also for other morphological traits. The present study used F1 and F2 generations developed from diverse parental stocks to report the inheritance pattern for different fruits traits. Our results demonstrate that pepper fruit bearing habit, its colour at unripe stage and fruit apex are simply inherited traits with or without epistatic interactions while fruit length is a quantitative character. Fruit orientation(drooping or erect) and fruit habit (solitary or cluster)showed segregation ratio of 3: 1 indicating monogenic inheritance of the trait where drooping character was dominant in nature over erect type and solitary fruit type was dominant over cluster type, fruit bearing habit (single pendant, single erect, cluster pendant and cluster erect) exhibited typical dihybrid ratio of 9: 3: 3: 1, fruit colour at unripe stage (green, purple and mixture of green & purple) segregated in the ratio of 9: 3: 4 exhibiting recessive gene epistasis and fruit apex (acute or blunt) showed a ratio of 15: 1 indicating duplicate dominant gene epistasis. Fruit length exhibited quantitative inheritance with plants showing fruit length greater than the positive parent (parent showing higher fruit length among the two parents) and lesser than the negative parent (parent showing lesser fruit length among the two parents) from different crosses. These results provide new data to clarify and further add on to the information available on the inheritance of chilli pepper fruit attributes.

Crack Identification on the Fresh Chilli (Capsicum) Fruit Destemmed System

Abstract: Destemming fresh chilli fruit (Capsicum) in large productivity is necessary, especially in the Mekong Delta region. Several studies have been done to solve this problem with high applicability, but a certain percentage of the output consisted of cracked fruits, thus reducing the quality of the system. The manual sorting results in high costs and low quality, so it is necessary that automatic grading is performed after destemming. This research focused on developing a method to identify and classify cracked chilli fruits caused by the destemming process. The convolution neural network (CNN) model was built and trained to identify cracks; then, appropriate control signals were sent to the actuator for classification. Image processing operations are supported by the OpenCV library, while the TensorFlow data structure is used as a database and the Keras application programming interface supports the construction and training of neural network models. Experiments were carried out in both the static and working conditions, which, respectively, achieved an accurate identification rate of 97 and 95.3%. In addition, a success rate of 93% was found even when the chilli body is wrinkled due to drying after storage time at 120 hours. Practical results demonstrate that the reliability of the model was useful and acceptable.

Studies on combining ability for yield and yield attributes in tomato (Solanum lycopersicum L.)

Abstract: Six diverse lines of tomato were crossed in full diallel mating fashion (Including reciprocal) to study combining ability effects for yield and yield contributing traits. Nature and magnitude of general combining ability effects provide guideline in identifying the better parents and their utilization. Based on gca effects, parent P6 and P5 were found to be the best general combiner as they showed significant gca effects in desirable direction. The specific combining ability effects represents dominance and epistatic gene effects which can be used as an index to determine the usefulness of a particular cross combination for exploitation through heterosis breeding and hybridization programme. The Cross P5 × P6 was found to be superior sca effect on the basis of yield and its attributing traits.

Design of Chili Fruit Flipping Mechanism for Identification of the Damages Caused by Diseases

Abstract: An identification model for detecting damages on fresh destemmed chili (capsicum) was developed, but the limitation is that the cameras can only capture from one side. Therefore, this study focused on developing the flipping mechanism, which rotates and flips chili fruits and helps the camcorder to observe and recognize errors on the entire body. The model was designed, fabricated and tested. Experiments were performed on 2400 fruits with 12000 flipping times, at 12 different velocities. The effective flipping rate was up to 96.3%. The fruits destroying percentage was also found to be remarkably low. These results were acceptable. The mechanism would be used to implement and test the identification algorithms in future chili grading systems.