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Identification and characterisation of nutmeg (Myristica fragrans Houtt.) genotypes of southern Kerala

By: Nainu Joseph.
Contributor(s): Sreekala, G S (Guide).
Material type: materialTypeLabelBookPublisher: Vellayani Department of Plantation Crops and Spices, College of Agriculture 2021Description: 149p.Subject(s): Plantation Crops and Spices | Nutmeg | Myristica fragrans HouttDDC classification: 633.8 Dissertation note: M Sc Summary: The research work on “Identification and characterisation of nutmeg (Myristica fragrans Houtt.) genotypes of Southern Kerala” was undertaken during 2020-21 at the Department of Plantation Crops and Spices, College of Agriculture, Vellayani. A survey was conducted in the nutmeg growing belts of Agro-Ecological Unit (AEU) 4 of Kottayam and Pathanamthitta districts, AEU 8 of Thiruvanathapuram district, AEU 9 of Kottayam, Pathanamthitta and Thiruvanathapuram districts, AEU 12 of Kottayam and Kollam districts and AEU 14 of Pathanamthitta district for identification of nutmeg genotypes with superior yield and variability. Among the fifty nutmeg genotypes surveyed twenty one genotypes were selected for characterization and in situ evaluation. The twenty one selected nutmeg genotypes from homesteads and estates were denoted as KDR 1, MNA 2, MNA 3, MNA 4, MPY 5, MPY 6, MPY 7, MPY 8, NLD 9, NLD 10, PND 11, PND 12, PKM 13, PLA 14, PLA 15, PLA 16, PLA 17, PRA 18, VNI 19, VNI 20 and VNI 21 based on the location of study. Qualitative and quantitative characterization of twenty one genotypes was undertaken for tree, leaf, flower, fruit and seed characters. Based on the DUS guidelines provided by PPV & FRA (2015) and minimal descriptor developed (Vikram, 2016) on nutmeg, thirty six qualitative characters were observed in the study in which height of tree, sex form, presence of caruncle and fruit length were non variable characters. The thirty two variable qualitative characters were subjected to hierarchical cluster analysis. UPGMA (Unweighted Pair Group Method with Arithmetical Averages) dendrogram was generated from the qualitative characters and fourteen clusters were formed at 65 percent similarity. Based on the clusters formed in the dendrogram, genotypes namely, MNA 3, NLD 9, NLD 10, PRA 18 and PLA 16 were closely related (cluster II), MPY 5 and PKM 13 (cluster III), PKD 11 and PLA 15 (cluster IV) and PLA 17 and VNI 20 (cluster VI). KDR 1 with yellow mace formed a separate cluster (Cluster I). The monoecious genotype VNI 21 was distinctly different from other clusters. Thirty two quantitative characters including biochemical characters were observed in the selected genotypes. Under the multivariate analysis for quantitative characters, principal component analysis was used as a statistical tool to interpret the parameters. The thirty two quantitative characters were reduced to eight principal component groups contributing a total variance of 84.518%. Based on the loadings in principal components 1 and 2, score plot and biplot was generated. The score plot grouped genotypes into 15 clusters in which genotypes with superior yield namely, PKD 11, PLA 14, NLD 9, PKM 13 and PRA 18 formed unique clusters. The pooled mean of yield characters revealed that five genotypes namely PKD 11, PLA 14, NLD 9, PKM 13 and PRA 18 were superior in yield. Significantly superior number of fruits per tree, fresh and dry mace yield and fresh nut yield per tree was observed in PKD 11 which was followed by PLA 14 with high yield in terms of number of fruits per tree, mace, nut and kernel yield. Significantly superior dry nut and kernel yield was obtained in NLD 9. PKM 13 and PRA 18 also recorded significantly high number of fruits per tree, dry mace, dry nut and dry kernel yield as compared to other genotypes. Thirty six qualitative characters were reduced to a minimal descriptor of eight characters namely, crown shape, shape of leaf blade, number of flowers per cluster, nature of fruit bearing, colour of mace (fresh), mace covering pattern, attachment of mace to nut and seed colour. Thirty two quantitative characters was reduced to a minimal data set of five characters such as number of flowers per cluster, height of tree, fruit weight, single kernel weight (dry) and fruit set percentage. Those genotypes with best combinations of these qualitative and quantitative characters can be selected for yield in nutmeg. Thus based on the identification, characterization and in situ evaluation for two years, PKD 11, PLA 14, NLD 9, PKM 13 and PRA 18 with superior yield and yellow maced genotype KDR 1 were selected for future crop improvement studies in nutmeg.
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Theses Theses KAU Central Library, Thrissur
Theses
Reference Book 633.8 NAI/ID PG (Browse shelf) Available 175303

M Sc

The research work on “Identification and characterisation of nutmeg (Myristica
fragrans Houtt.) genotypes of Southern Kerala” was undertaken during 2020-21 at the
Department of Plantation Crops and Spices, College of Agriculture, Vellayani.
A survey was conducted in the nutmeg growing belts of Agro-Ecological Unit
(AEU) 4 of Kottayam and Pathanamthitta districts, AEU 8 of Thiruvanathapuram district,
AEU 9 of Kottayam, Pathanamthitta and Thiruvanathapuram districts, AEU 12 of
Kottayam and Kollam districts and AEU 14 of Pathanamthitta district for identification of
nutmeg genotypes with superior yield and variability. Among the fifty nutmeg genotypes
surveyed twenty one genotypes were selected for characterization and in situ evaluation.
The twenty one selected nutmeg genotypes from homesteads and estates were denoted as
KDR 1, MNA 2, MNA 3, MNA 4, MPY 5, MPY 6, MPY 7, MPY 8, NLD 9, NLD 10,
PND 11, PND 12, PKM 13, PLA 14, PLA 15, PLA 16, PLA 17, PRA 18, VNI 19, VNI
20 and VNI 21 based on the location of study. Qualitative and quantitative
characterization of twenty one genotypes was undertaken for tree, leaf, flower, fruit and
seed characters. Based on the DUS guidelines provided by PPV & FRA (2015) and
minimal descriptor developed (Vikram, 2016) on nutmeg, thirty six qualitative characters
were observed in the study in which height of tree, sex form, presence of caruncle and
fruit length were non variable characters.
The thirty two variable qualitative characters were subjected to hierarchical cluster
analysis. UPGMA (Unweighted Pair Group Method with Arithmetical Averages)
dendrogram was generated from the qualitative characters and fourteen clusters were
formed at 65 percent similarity. Based on the clusters formed in the dendrogram,
genotypes namely, MNA 3, NLD 9, NLD 10, PRA 18 and PLA 16 were closely related
(cluster II), MPY 5 and PKM 13 (cluster III), PKD 11 and PLA 15 (cluster IV) and PLA
17 and VNI 20 (cluster VI). KDR 1 with yellow mace formed a separate cluster (Cluster
I). The monoecious genotype VNI 21 was distinctly different from other clusters.
Thirty two quantitative characters including biochemical characters were observed
in the selected genotypes. Under the multivariate analysis for quantitative characters,
principal component analysis was used as a statistical tool to interpret the parameters.
The thirty two quantitative characters were reduced to eight principal component
groups contributing a total variance of 84.518%. Based on the loadings in principal
components 1 and 2, score plot and biplot was generated. The score plot grouped
genotypes into 15 clusters in which genotypes with superior yield namely, PKD 11, PLA
14, NLD 9, PKM 13 and PRA 18 formed unique clusters.
The pooled mean of yield characters revealed that five genotypes namely PKD 11,
PLA 14, NLD 9, PKM 13 and PRA 18 were superior in yield. Significantly superior
number of fruits per tree, fresh and dry mace yield and fresh nut yield per tree was
observed in PKD 11 which was followed by PLA 14 with high yield in terms of number
of fruits per tree, mace, nut and kernel yield. Significantly superior dry nut and kernel
yield was obtained in NLD 9. PKM 13 and PRA 18 also recorded significantly high
number of fruits per tree, dry mace, dry nut and dry kernel yield as compared to other
genotypes.
Thirty six qualitative characters were reduced to a minimal descriptor of eight
characters namely, crown shape, shape of leaf blade, number of flowers per cluster,
nature of fruit bearing, colour of mace (fresh), mace covering pattern, attachment of mace
to nut and seed colour. Thirty two quantitative characters was reduced to a minimal data
set of five characters such as number of flowers per cluster, height of tree, fruit weight,
single kernel weight (dry) and fruit set percentage. Those genotypes with best
combinations of these qualitative and quantitative characters can be selected for yield in
nutmeg.
Thus based on the identification, characterization and in situ evaluation for two
years, PKD 11, PLA 14, NLD 9, PKM 13 and PRA 18 with superior yield and yellow
maced genotype KDR 1 were selected for future crop improvement studies in nutmeg.

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