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Genetic stock development for phytophthora pod rot disease resistance in cocoa (Theobroma cacao L.)

By: Veeresh S Akki.
Contributor(s): Minimol, J S (Guide).
Material type: materialTypeLabelBookPublisher: Vellanikkara Department of Plant Breeding and Genetics, College of Horticulture 2017Description: 96p.Subject(s): Agriculture | Plant Breeding and GeneticsDDC classification: 630.28 Online resources: Click here to access online Dissertation note: MSc. Abstract: Cocoa production is ruthlessly affected by pod rot disease caused by many Phytophthora species. Among these, the pod rot caused by Phytophthora palmivora is of prime importance. Since, the disease infection period is rainy season, the application of fungicides has not evidenced as a successful control measure. Hence, the effective and eco-friendly way to tackle this disease is by developing resistant varieties. The success of any breeding programme depends upon the availability of well characterised genetic resources. In this context, the current study was formulated for characterisation of exotic germplasm and identifying genetic stock of cocoa for Phytophthora pod rot resistance. Morphological characterization of 30 genotypes were carried out by recording ten qualitative and 23 quantitative characters governing leaf, flower, pod and bean. High variability was observed for most of the characters except petal colour and number of ridges and furrows. The germplasm when characterized based on biochemical parameters such as fat, polyphenols and mineral content (Na, K and Ca) also expressed wide variability. It is essential to quantify the diversity available among genotypes in order to design an effective breeding programme. Hence, cluster analysis was carried out by D2 statistics and principal component analysis. Among all the qualitative clusters, cluster III was the biggest with eight members. Cluster analysis of quantitative characters showed that most of the genotypes were placed separately in distinct cluster due to wide variability available in the germplasm. Cluster analysis of biochemical characters also exhibited wide variability which is evident from the fact that it formed 15 clusters even at 25 per cent similarity. Correlation studies and path analysis were employed to know the nature and relationships among the yield attributing characters. Here, it was found that wet bean weight (g) showed positive correlation with pod weight (g), furrow thickness (cm), pod length (cm), pod breadth (cm), weight of the bean (g) and number of beans per pod. Results of path analysis revealed that total wet bean weight (g) was directly influenced by pod thickness (cm), number of beans per pod, single dry bean weight (g) and wet bean weight (g). Since, quantitative and qualitative descriptors serve as an effective tool to discriminate among the genotypes, a evaluation data was constructed for all the genotypes considering distinct characters governing them. The non-pricking and pricking methods of pod inoculation with pure culture of pathogen were employed to know the disease resistance reaction exhibited by different genotypes. In the non-pricking method, five genotypes (ICS 41, SIAL 339, PNG 250, PNG 336 and IMC 20) with zero per cent infection and 14 genotypes (CRU 12, MO 109, GDL 7, GU 261/P, NA 149, PA 156, LX 43, POUND 4/B, JA 10/12, DOM 14, ICS 75, DOM 25, POUND 18 and POUND 16/A) with infection less than 15 per cent were grouped under highly resistant category. However, these genotypes did not show same disease resistance reaction in pricking method which indicated that the resistance was influenced by certain morphological characters apart from the internal resistance and the significance of those morphological characters were lost when pods were pricked. Binomial logistic regression revealed that different phenes like ridge thickness, polyphenol content and calcium content were positively contributing to disease resistance. Whereas, phenes like pod rugosity, pod basal constriction and pod length were negatively correlated with disease resistance. If these phenes are considered for selection, ample increase in the level of resistance will be noticed in the resultant population. Genetic stock was developed considering disease resistance and yield. As opined by many scientists “Disease resistance is a double-edged sword”. The phytotoxin developed in plants against pathogen is not only toxic to the pathogen but also to the plants resulting in yield reduction. Here also same trend was noticed and majority of the genotypes which expressed high resistance were low yielders. The accessions manifested high resistance can be used for further breeding programme.
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MSc.

Cocoa production is ruthlessly affected by pod rot disease caused by many
Phytophthora species. Among these, the pod rot caused by Phytophthora palmivora is
of prime importance. Since, the disease infection period is rainy season, the application
of fungicides has not evidenced as a successful control measure. Hence, the effective
and eco-friendly way to tackle this disease is by developing resistant varieties. The
success of any breeding programme depends upon the availability of well characterised
genetic resources. In this context, the current study was formulated for characterisation
of exotic germplasm and identifying genetic stock of cocoa for Phytophthora pod rot
resistance.
Morphological characterization of 30 genotypes were carried out by recording
ten qualitative and 23 quantitative characters governing leaf, flower, pod and bean. High
variability was observed for most of the characters except petal colour and number of
ridges and furrows. The germplasm when characterized based on biochemical
parameters such as fat, polyphenols and mineral content (Na, K and Ca) also expressed
wide variability.
It is essential to quantify the diversity available among genotypes in order to
design an effective breeding programme. Hence, cluster analysis was carried out by D2
statistics and principal component analysis. Among all the qualitative clusters, cluster
III was the biggest with eight members. Cluster analysis of quantitative characters
showed that most of the genotypes were placed separately in distinct cluster due to wide
variability available in the germplasm. Cluster analysis of biochemical characters also
exhibited wide variability which is evident from the fact that it formed 15 clusters even
at 25 per cent similarity.
Correlation studies and path analysis were employed to know the nature and
relationships among the yield attributing characters. Here, it was found that wet bean
weight (g) showed positive correlation with pod weight (g), furrow thickness (cm), pod
length (cm), pod breadth (cm), weight of the bean (g) and number of beans per pod.
Results of path analysis revealed that total wet bean weight (g) was directly influenced
by pod thickness (cm), number of beans per pod, single dry bean weight (g) and wet
bean weight (g).
Since, quantitative and qualitative descriptors serve as an effective tool
to discriminate among the genotypes, a evaluation data was constructed for all the
genotypes considering distinct characters governing them.
The non-pricking and pricking methods of pod inoculation with pure culture
of pathogen were employed to know the disease resistance reaction exhibited by
different genotypes. In the non-pricking method, five genotypes (ICS 41, SIAL 339,
PNG 250, PNG 336 and IMC 20) with zero per cent infection and 14 genotypes (CRU
12, MO 109, GDL 7, GU 261/P, NA 149, PA 156, LX 43, POUND 4/B, JA 10/12, DOM
14, ICS 75, DOM 25, POUND 18 and POUND 16/A) with infection less than 15 per
cent were grouped under highly resistant category. However, these genotypes did not
show same disease resistance reaction in pricking method which indicated that the
resistance was influenced by certain morphological characters apart from the internal
resistance and the significance of those morphological characters were lost when pods
were pricked.
Binomial logistic regression revealed that different phenes like ridge thickness,
polyphenol content and calcium content were positively contributing to disease
resistance. Whereas, phenes like pod rugosity, pod basal constriction and pod length
were negatively correlated with disease resistance. If these phenes are considered for
selection, ample increase in the level of resistance will be noticed in the resultant
population.
Genetic stock was developed considering disease resistance and yield. As
opined by many scientists “Disease resistance is a double-edged sword”. The
phytotoxin developed in plants against pathogen is not only toxic to the pathogen but
also to the plants resulting in yield reduction. Here also same trend was noticed and
majority of the genotypes which expressed high resistance were low yielders. The
accessions manifested high resistance can be used for further breeding programme.

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