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Genetic variability among Indian rainy season sorghum cultivars revealed by morpho-agronomic traits

  • ICAR-Indian Institute of Millets Research (former Directorate of Sorghum Research)

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Sorghum [Sorghum bicolor L. (Moench)] is an important crop for the semi-arid tropics. To protect varieties under Protection of Plant Varieties and Farmers Rights Act (PPV&FRA) 2001 the entries need to be tested for distinctiveness, uniformity and stability during the season of their adaptation itself. Fifteen parental lines and 32 varieties belonging to different categories of sorghum were characterized for DUS traits during the kharif seasons of 2006 and 2007. Among quantitative traits total plant height contributed >70% towards variability of the genotypes. Quantitative traits alone put the 47 genotypes into three clusters, while qualitative traits alone grouped the genotypes into four main clusters. Grouping based on qualitative traits corroborated more towards the total variability as against quantitative traits alone. Generated data clearly could establish distinctiveness among all the genotypes without any ambiguity. Combination of qualitative and quantitative traits in establishing distinctiveness was more effective than any type of trait alone.
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Indian J. Genet., 73(1): 110-115 (2013)
DOI : 10.5958/j.0019-5200.73.1.017
Sorghum [Sorghum bicolor L. (Moench)] is an important
crop for the semi-arid tropics. To protect varieties under
Protection of Plant Varieties and Farmers Rights Act
(PPV&FRA) 2001 the entries need to be tested for
distinctiveness, uniformity and stability during the season
of their adaptation itself. Fifteen parental lines and 32
varieties belonging to different categories of sorghum were
characterized for DUS traits during the kharif seasons of
2006 and 2007. Among quantitative traits total plant height
contributed >70% towards variability of the genotypes.
Quantitative traits alone put the 47 genotypes into three
clusters, while qualitative traits alone grouped the
genotypes into four main clusters. Grouping based on
qualitative traits corroborated more towards the total
variability as against quantitative traits alone. Generated
data clearly could establish distinctiveness among all the
genotypes without any ambiguity. Combination of
qualitative and quantitative traits in establishing
distinctiveness was more effective than any type of trait
Key words: Genetic variability, diversity, dendrogram,
quantitative traits, DUS trait, euclidean
distance, Sorghum bicolor L. (Moench)
Sorghum [Sorghum bicolor (L.) Moench] is the fifth
most important cereal crop to provide food, feed and
fodder across semi-arid tropics including India. In India
since 1969, 23 varieties (CSV 1 to CSV 23) and 25
hybrids (CSH 1 to CSH 25) along with 32 promising
parental lines have been released. Out of these, 19
varieties, 20 hybrids and 26 parental lines are adapted
to kharif season [1]. Characterization of these cultivars
is needed to understand their genetic relationship so
that they may be deployed effectively in breeding
programme. Intra-specific diversity of sorghum has
been studied using agro-morphological traits by various
authors [2-4]. In most of the recent reports
morphological markers have been supplemented with
molecular data [5-7]. Using the accepted DUS testing
guidelines of India for the first time establishment of
distinctiveness among only 11 out of 26 varieties has
been reported [3]. However, this study is restricted to
forage sorghum varieties only. The present work was
carried out (1) to establish the genetic variability among
the extant kharif varieties/parental lines using DUS
traits, and (2) to study the diversity among the kharif
The study was focused on 47 kharif extant
varieties and parental lines (Table 1). The experiments
were conducted during Kharif seasons of 2006 and
2007 as per the DUS test guidelines [8] using
randomized complete block design with four
replications. Genotypes were sown in six rows of 6 m
with 60 × 15 cm spacing. Data were recorded for 12
quantitative traits, namely, days to panicle emergence,
plant height up to base of flag leaf, stigma length,
anther length, total plant height, stem diameter, leaf
blade length, leaf blade width, panicle length without
peduncle, branch length in panicle, neck length of
panicle visible above sheath and 1000 grain weight
(g), and 21 qualitative traits viz., anthocyanin
colouration of coleoptile, leaf sheath anthocyanin
*Corresponding author’s e-mail:
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Short Communication
Genetic variability among Indian rainy season sorghum cultivars
revealed by morpho-agronomic traits
N. Kannababu, S. Rakshit*, S. Audilakshmi, V. A. Tonapi, J. V. Patil, A. Dhandapani, D. C. S. Reddy,
K. Venugopal, M. Swarnalatha, G. Balakrishna, K. Raghunath and V. Subhakar
Directorate of Sorghum Research, Rajendranagar, Hyderabad 500 030
(Received: December 2011; Revised: November 2012; Accepted: December 2012)
February, 2013] Genetic variability in kharif season sorghum 111
Table 1. Sorghum cultivars released for rainy season (kharif) of India subjected to phenotypic analysis determining the genetic diversity
S.No. Cultivar Nature of cultivar Pedigree Year of Central/ Source/centre
name release state
1. 2077B Parental line (B) of CSH 5 IS 2046 × 3677B 1974 Central DSR, Hyderabad, Andhra Pradesh
2. 2219B Parental line (B) of CSH 3 and CSH 6 Selection from Kharif Shallu 1970 & Central DSR, Hyderabad, Andhra Pradesh
3. 296B Parental line (B) of CSH 9, CSH 10, IS 3922 x Karad local 1981, Central DSR, Hyderabad, Andhra Pradesh
CSH 11, CSH 12R, CSH 13K & 1984,
CSH13R 1986 &
4. 27B Parental line (B) of CSH 16 83B x 199B 1997 Central DSR, Hyderabad, Andhra Pradesh
5. AKMS 14B Parental line (B) of CSH 14 (MR 760 x BT 632) x AKMS 2B 1992 & Central PDKV, Akola, Maharashtra
and CSH 17 1999
6. 7B Parental line (B) of CSH 23 Selection from AKMS14A 2005 Central DSR, Hyderabad, Andhra Pradesh
7. IMS 9B Parental line (B) of CSH 18 2077A x (MA9B x Vidisha 60-1) 1999 Central RVSKVV, Indore
8. CS 3541 Parental line (R) of CSH 5 & CSH 9 IS 3675 x IS 3541 1974 & Central DSR, Hyderabad, Andhra Pradesh
9. RS 29 Parental line (R) of CSH 13K & SC 108 x SPV 126 1986 & Central DSR, Hyderabad, Andhra Pradesh
CSH 13R 1992
10. C43 Parental line (R) of CSH 16 CS3541 x IS23549 1997 Central DSR, Hyderabad, Andhra Pradesh
11. RS 673 Parental line (R) of CSH 17 SPV 544 x K 24-1 1998 Central DSR, Hyderabad , Andhra Pradesh
12. MR 750 Parental line (R) of CSH 11 Sel. MR 841 (SC 108-3 x CS 1986 Central ICRISAT, Hyderabad, Andhra Pradesh
13. AKR 150 Parental line (R) of CSH 14 CS 3541 x 900 1992 Central PDKV, Akola, Maharashtra
14. Indore 12 Parental line (R) of CSH 18 (SSV 53 x SPV 475-7-1-1-1) 1999 Central RVSKVV, Indore, Madhya Pradesh
15. AKR73 Parental line (R) of AKSH 73 (SPH 388) 1990 State PDKV, Akola, Maharashtra
16. CSV 13 Grain sorghum variety (IS 12622 × 555) x S 3612 x 1988 Central ICRISAT, Hyderabad, Andhra Pradesh
2219B x E 35-1
17. CSV 15 Grain sorghum variety SPV 475 x SPV 462 1996 Central DSR, Hyderabad, Andhra Pradesh
18. CSV 17 Grain sorghum variety SPV 946 x SPV 772 2002 Central MAUA&T, Udaipur, Rajasthan
19. CSV 20 Grain sorghum variety SPV 946 x Kh 89-246 2006 Central DSR, Hyderabad, Andhra Pradesh
20. ICSV 745 Grain sorghum variety (PM 11344 x A6250- 4-1-1-1) 1990 Central ICRISAT, Hyderabad, Andhra Pradesh
Table 1 contd.
112 N. Kannababu et al.[Vol. 73, No. 1
21. APK 1 Grain sorghum variety TNS 30 x Co-26 1996 State TNAU, Arupukottai, Tamil Nadu
22. BSR 1 Grain sorghum variety Multiple cross (CSC 108-3 x 1990 State TNAU, Bhavanisagar, Tamil Nadu
CSV 4) 16-3-1 x (MR 801x R2751)
23. GJ 9 Grain sorghum variety Pure line selection from local 1979 Central GAU, Surat, Gujarat
Brooch Dist.
24. GJ 37 Grain sorghum variety (2077 x M 28) x Cuandri 1986 State GAU, Surat, Gujarat
25. GJ 38 Grain sorghum variety GJ 35 x E 35-1 1994 State GAU, Surat, Gujarat
26. GJ 40 Grain sorghum variety (2077 A x M 25) x Malvan 1995 State GAU, Surat, Gujarat
27. JJ 741 Grain sorghum variety CSV 4 x E 35-1 1991 Central RVSKVV, Indore, Madhya Pradesh
28. JJ 938 Grain sorghum variety SPV 221 x E 602 1995 State RVSKVV, Indore, Madhya Pradesh
29. JJ 1022 Grain sorghum variety (SPV 475 x SPV 462) 21-3-3 2006 State RVSKVV, Indore, Madhya Pradesh
30. JJ 1041 Grain sorghum variety (SPV 475 x SPV 462) 7-1-2 1997 State RVSKVV, Indore, Madhya Pradesh
31. PVK 400 Grain sorghum variety SDS 2650 x CS 3541 1993 State MAU, Parbhani, Maharashtra
32. PVK 801 Grain sorghum variety Sel. From ICRISAT population 1999 State MAU, Parbhani, Maharashtra
GD 34-5-5-3
33. PVK 809 Grain sorghum variety PVK 801 x SOV 881 2004 State MAU, Parbhani, Maharashtra
34. PSV 1 Grain sorghum variety MS-827 x IS-3691 1996 State ANGRAU, Palem, Andhra Pradesh
35. PVR 453 Grain sorghum variety Selection from local, Parbhani Jyoti 2001 State MAU, Parbhani, Maharashtra
36. K 8 Grain sorghum variety IS 12611 C x SC 108 1990 Central TNAU, Kovilpatti, Tamilnadu
37. Co(S) 28 Grain sorghum variety Co 25 x SPV 942 2001 State TNAU, Coimbatore, Tamilnadu
38. CSV 19SS Sweet sorghum variety RSSV 2 x SPV 462 2004 Central MPKV, Rahuri, Maharashtra
39. SSV 84 Sweet sorghum variety Selection from Zera-Zera 1992 Central MPKV, Rahuri, Maharashtra
sorghum IS 23568
40. Pant chari 3 Forage sorghum variety Visarada 61-1 x IS 6953 1990 State GBPUA&T, Pantnagar, Uttarakhand
41. Pant chari 4 Forage sorghum variety IS 4776 x RIO 1995 State GBPUA&T, Pantnagar, Uttarakhand
42. Pant chari 5 Forage sorghum variety CS 3541 x IS 6935 1999 Central GBPUA&T, Pantnagar, Uttarakhand
43. Pant chari 6 Forage sorghum variety SDSL 92140-MCT-36-93, 2006 Central GBPUA&T, Pantnagar, Uttarakhand
Selection from Zimbabwe
germplasm line
44. HC 136 Forage sorghum variety IS 3214 (bicolor) x PC 7R 1982 Central CCSHAU, Hisar, Haryana
45. HC 171 Forage sorghum variety SPV 8 x IS 4776 1987 Central CCSHAU, Hisar, Haryana
46. SSG 59-3 Forage sorghum variety Non-sweet Sudan grass x JS 263 1977 Central CCSHAU, Hisar, Haryana
47. UP chari 2 Forage sorghum variety Vidisha 60-1 x IS 6953 1984 Central GBPUA&T, Pantnagar, Uttarakhand
Source: Tonapi et al. [1].
Table 1 contd.
February, 2013] Genetic variability in kharif season sorghum 113
colouration, leaf mid rib colour (5th fully developed
leaf), yellow colouration of flag leaf midrib, presence
of arista, stigma anthocyanin colouration, stigma
yellow colouration, length of pedicellate spikelet, colour
of dry anthers, glume colour, panicle density, panicle
shape, glume length, threshability score, caryopsis
colour after threshing, grain shape in dorsal view, grain
shape in profile view, size of mark of germ, endosperm
texture, colour of vitreous albumen and grain lustre.
Ten competitive plants were randomly selected from
middle four lines of each replication for recording the
field observations for all the traits except days to
panicle emergence, which was observed on plot basis.
For the quantitative data, variance components were
estimated with restricted likelihood method (REML)
using SAS Mixed Procedure (SAS 9.2). Genotypes
were considered fixed, while other factors as random.
SAS code for the analysis as given by [8] was followed.
The quantitative and qualitative data were transformed
into binary data according to [6]. The binary data were
used to calculate Jaccard’s similarity coefficients and
were used to construct dendrogram employing UPGMA
(Unweighted Paired Group Method using Arithmetic
Average) using NTSYSpc 2.02e [10].
Analysis of variance showed significant
differences among the 47 genotypes, for all the
quantitative traits studied (data not shown). Maximum
variability as represented by panicle neck length
followed by plant height up to base of flag leaf, panicle
branch length and other traits. This observation is in
complete agreement with earlier report [4]. However,
Elangovan et al. [11] reported much higher variation
Table 2. Broad-sense genotypic (above diagonal) and phenotypic (below diagonal) correlations between quantitative
DPE -0.72 0.41 0.29 0.70 0.42 –0.49 0.04 –0.43 –0.23 –0.49 –0.21
PHFL 0.61 -0.64 0.50 0.99 –0.20 –0.58 –0.36 –0.44 –0.19 –0.24 –0.18
SL 0.33 0.60 -0.71 0.65 –0.16 –0.39 –0.30 –0.11 0.18 –0.16 –0.26
AL 0.15 0.42 0.59 -0.51 –0.26 –0.67 –0.43 –0.25 0.07 –0.06 –0.14
TPH 0.60 0.97 0.62 0.43 -–0.25 –0.52 –0.40 –0.34 –0.09 –0.15 –0.20
SD 0.26 –0.12 –0.13 –0.18 –0.16 -–0.38 0.62 –0.28 –0.49 –0.44 0.19
LL –0.40 –0.37 –0.23 –0.29 –0.35 –0.04 -0.23 0.75 0.46 0.42 0.04
LW –0.05 –0.28 –0.20 –0.29 –0.32 0.46 0.33 -–0.16 –0.52 –0.32 0.44
PL –0.35 –0.41 –0.10 –0.19 –0.32 –0.20 0.47 –0.13 -0.86 0.63 –0.24
PBL –0.19 –0.17 0.17 0.08 –0.09 –0.30 0.31 –0.38 0.78 -0.53 –0.42
PNL –0.34 –0.21 –0.12 –0.04 –0.11 –0.26 0.20 –0.27 0.50 0.43 -–0.08
GW –0.15 –0.16 –0.24 –0.10 –0.18 0.10 –0.03 0.33 –0.20 –0.37 –0.07 -
$ DPE: days to panicle emergence; PHFL: plant height up to base of flag leaf, (cm); SL: stigma length (mm); AL: anther length (mm) ; TPH:
total plant height (cm); SD: stem diameter (at lower one third height of plant) (cm); LL: leaf blade length (the third leaf from top including
flag leaf) (cm); LW: leaf width (the third leaf from top including flag leaf) (cm); PL: panicle length without peduncle (cm) ; PBL: panicle
branch length (middle third of panicle) (cm); PNL: panicle neck length above sheath (cm) ; GW: 1000 grain weight (g)
for all the traits than what we and Reddy et al. [10]
have observed. This may be due to the fact that the
earlier studies included landraces, while the present
investigation study is restricted to released cultivars.
Significant genotype x year interactions were recorded
for all the traits except plant height up to base of flag
leaf, while year effect was insignificant for plant height
up to base of flag leaf, stigma length, leaf length and
panicle length (data not shown). This supported earlier
report by Reddy et al. [4]. High broad sense heritability
(>90%) was recorded for majority of traits except leaf
blade length (66%), stem diameter (72%), leaf blade
width (80%) and anther length (86%). This is partially
in agreement with earlier results [4], which reported
low heritability for days to panicle emergence (55%)
and grain weight (72%).
High positive genetic correlations ( >0.70) were
recorded between plant height up to base of flag leaf
and total plant height (0.99), followed by panicle length-
panicle branch length (0.86), leaf length-panicle length
(0.75), days to panicle emergence-plant height up to
base of flag leaf (0.72), and others (Table 2). Moderate
negative correlations were recorded between leaf
length-anther length (–0.67), plant height up to base
of flag leaf/total plant height-leaf length among others.
This is not in agreement with earlier findings, who
reported predominance of positive correlation among
quantitative traits in sorghum [2, 11]. The high genetic
as well as phenotypic correlation between total plant
height and plant height up to base of flag leaf
suggested that these are highly correlated traits and
one may be dropped as DUS trait. Like Ayana and
114 N. Kannababu et al.[Vol. 73, No. 1
Bekele [2] we also recorded very high correlation
between panicle length and panicle branch length,
which they explained by ‘multiplication and
condensation’ hypothesis.
Cluster analysis was carried out separately using
quantitative and qualitative data separately, which put
the genotypes into three and four clusters, respectively
(data not shown). Jacard’s similarity coefficient based
on combined data (12 qualitative and 21 quantitative
traits) as suggested by Geleta et al. [6] ranged from
0.08-0.93 with an average of 0.44. Clustering pattern
put the genotypes under study into four main clusters
(Fig. 1). Cluster I, was represented by three B lines
(2077B, 27B and 296B). Cluster II was the biggest
with four sub-clusters, represented by 33 genotypes.
Sub-cluster IIa contained two R lines (RS29 and
RS673), three B lines (2219B, AKMS14B and 7B) and
remaining grain sorghum varieties. Sub-clusters IIb
and IId were smallest with two varieties each. Sub-
cluster IIc represented majority of R lines (5 out of 8).
Majority of forage varieties (7 out of 8) were represented
in two clusters, III and IV. Cluster III contained eight
genotypes, of which four were forage sorghum varieties
(HC 136, Pant Chari 3, HC 171, UP Chari 2), two grain
sorghum varieties (GJ 9, PVR 453), and two sweet
sorghum varieties (CSV 19SS and SSV 84). Cluster
V was represented by only forage sorghum varieties
(Pant Chari 4, Pant Chari 6, SSG 59-3). The PCA fully
did not support the clustering pattern, as obtained by
UPGMA. However, most of the forage sorghum
varieties and sweet sorghum variety, CSV 19SS
remained distinctly different from rest of the genotypes
based on qualitative traits. The clustering pattern
remained much similar to that obtained using qualitative
traits alone with some differences in term of similarity
values (Fig. 1). The product moment correlation
coefficients through Mentel’s test between the
clustering patterns using qualitative data and
quantitative data alone to that of combined data set
were 0.93 and 0.83, respectively. This suggests that
there was very good fit to the trees obtained by
qualitative data and the combined data set, while good
correlation could be obtained between quantitative data
and combined data set.
Existence of wide variability among extant
varieties and parental lines was observed in the present
investigation. Reddy et al. [4] first reported the
variability among the released sorghum cultivars in
India. The findings of present study are in broad
agreement with their results. Relatively less variability
among the male sterile (MS) lines was observed.
Unlike the previous report, we found that IMS 9B was
quite divergent from the remaining MS lines. The R
lines were also relatively similar majority being grouped
in sub-cluster IIc. More divergent R lines, like RS 29
or RS 673 may be hybridized with other R lines to
derive new R lines. Genotypes in cluster I or II and III
or IV were quite divergent. However, these may not
Fig. 1. Dendrogram based on Jaccard’s coefficient using combined data (R = 0.88)
February, 2013] Genetic variability in kharif season sorghum 115
readily be used in crossing programme as they are
predominantly quite different (grain types and forage
types). Some of the grain type genotypes which are
present in cluster III may be used in crossing
programme with genotypes in cluster I or II to bring in
wider variability among the progenies. Similarly, much
diverse forage genotype, Pant Chari 5 (IId) may be
crossed with other forage varieties in Cluster IIIb or IV
to create more genetic variability for various
morphological traits. In addition towards parental line
development of grain sorghum genotypes belonging
to Cluster I may be hybridized with genotypes
belonging to Cluster IIb or IIc to derive new parental
lines. Reddy et al. [4] also suggested crossing between
genotypes from diverse clusters for improvement of
female parents for DUS traits.
In the present study a considerable variability
among genotypes was observed. However, few
genotype combinations like AKMS14B-7B or JJ938-
JJ1041 are much similar (Fig. 1). Pedigree information
suggests that 7B is a selection from AKMS14B (Table
1). Thus, their morphological closeness is expected,
which is certainly due to their similar genetic
architecture. Similar was the case with JJ1022 and
JJ1041. Some combinations were quite similar in
terms of qualitative traits, as was the case with RS673
and GJ38. However, they were diverse in terms of
quantitative traits. On the other hand several
combinations, like CSV 15-CSV 20 or JJ 1041-PKV
809 came very close for quantitative values, but were
diverse enough qualitatively (data not shown). So
rightly these both are part of the DUS testing guidelines
across crop species. It may be noted that in spite of
existence of much variability for morphological traits
some genotypes came much closer to each other
(Fig. 1). Thus, it is imperative that efforts are needed
continuously to search for new morphological traits to
supplement existing traits as available in DUS testing
guidelines in sorghum. Efforts are also needed to
explore the application of DNA markers in such testing.
This work was carried out with the financial support
from the Authority for Protection of Plant Varieties
and Farmers’ Rights, India (PPV&FRA) under central
sector scheme on “preparation for plant variety
protection and DUS testing through ICAR-SAU
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... Characterization of varieties is thus of significance for the purpose of establishment and verification of identity and assessment of varietal purity for seed production and certification (Singh et al., 2016). Previously study on diversity of inter specific sorghum has been reported using agro-morphological traits by various researchers (Ayana and Bekele, 2000;Joshi et al. 2009;Reddy et al., 2009;Kannababu et al., 2013;Raghuvanshi et al., 2014). It is therefore, important to identify key diagnostic traits of different genotypes. ...
Full-text available
The present investigation was conducted to characterize 20 genotypes of sorghum {Sorghum bicolor (L.) moench} on the basis of 33 morphological characters provided by Protection of Plant Variety & Farmer's Right Act (PPV&FRA) for Distinctiveness Uniformity and Stability (DUS) testing in sorghum. Experimental results revealed that maximum variation was found on the basis of glume colour among the genotypes i.e. G 46, HC 308, HJ 513 had green white, IS 3237, SSG 9, HC 171 had yellow white, SSG 59-3, COFS 29 had grayed purple, S 437-1, SGL-87, S 540-S, SSG (PSSG) had grayed yellow and remaining seven genotypes had grayed orange glume colour. The studied traits showed five genotypes had distinct state of expression. Genotype S-540 showed very high plant height upto the base of flag leaf, HC 136 had compact panicle density at maturity, COFS 29 had very long glume length, SSG 59-3 had distinct expression for days to panicle emergence (50 % of the plants with 50 % of anthesis) and COFS 29 and IS 18551 had short and very long leaf width of blade, respectively. The Principal Component Analysis (PCA) revealed principal Factor (PFI) and Principal Factor (PFII) with maximum variability (64.99 %). Classification of genotypes on the basis of DUS traits provided identification of key characteristics of various genotypes.
... In addition, 15 parental and 32 Indian sorghum varieties were also grouped into four clusters based on qualitative and quantitative traits. This established distinctiveness among all the genotypes more precisely than any trait alone [18]. ...
Post-rainy season-cultivated sorghum lines are local landraces, known for their grain quality and used exclusively for human consumption. Because of their importance, the present study was undertaken to estimate genetic diversity for morphological and yield-contributing traits at two locations. The ANOVA for days to flower, stem diameter, panicle width, yield per plant and 100 seed weight showed significant differences among 85 sorghum landraces and 15 popular varieties. Mean squares for all the traits were significantly affected by genotypes (G), environments (E) and G × E interaction. Relatively high broad-sense heritability was observed for grain yield at BARC, Mumbai (E1), and panicle length at ARS, Gulbarga (E2) locations, respectively. Significant positive correlations between panicle width and grain yield (0.23**) and between seed weight and grain yield (0.22**) were observed. Cluster analysis based on Euclidean distance grouped all the genotypes into five clusters with PC-6 emerging as a distinct variety. Promising landraces identified in this study would serve as genetic resources for recombination breeding.
... The positive correlation among these yield contributing traits suggested that these characters are important and are also good indicator for direct selection of high yielding genotypes. Similar results were reported by Elangovan et al. [ AT21 AT16 AT27 AT48 AT101 AT53 AT93 AT105 AT41 AT40 AT15 AT07 AT130 AL59 AT02 AT37 AT43 AT23 AT44 AT17 AT25 AT26 AT06 AT33 AT31 AT49 AT32 AT09 AT55 AT125 AT36 AT137 AT30 AT124 AT01 AT138 AT20 AT102 AL67 AT116 BO82 BO78 AT99 AT129 BO81 AT19 AT117 AT110 AT100 AT120 AT139 AT126 AT86 AT39 AT88 AT89 AT132 AT106 AL61 AL60 AT05 AT123 AL71 AT94 AT22 AT111 AT35 AT119 AT52 AT122 AT114 AT136 AT118 AT11 AT104 AL64 AT92 AT103 AL70 AT115 AT140 AT85 AT134 AT13 AL63 AT87 AT113 AT98 AT128 AT109 AT95 AT12 BO75 BO74 AT121 AT97 AT28 AT50 AT03 AT45 AT18 AT96 AT108 AT127 BO84 BO80 BO79 BO73 AT135 BO76 AT112 AT90 AT04 AT91 AT54 AL56 AT46 AT14 AT10 AT42 AT133 AT24 AL72 AT38 AT51 BO83 AT131 AL66 AL57 AL58 AT141 AL65 BO77 AL69 AT142 AL62 AL68 AT34 AT47 AT107 AT08 Bubuche [16]; and Kannababu et al. [27]. The width of third leaf from top and length of third leaf from top were highly associated as reported by Khaliq et al. [28]. ...
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Sorghum [Sorghum bicolor (L.) Moench] is an important staple food crop in northern Benin. In order to assess its diversity in Benin, 142 accessions of landraces collected from Northern Benin were grown in Central Benin and characterised using 10 qualitative and 14 quantitative agromorphological traits. High variability among both qualitative and quantitative traits was observed. Grain yield (0.72–10.57 tons/ha), panicle weight (15–215.95 g), days to 50% flowering (57–200 days), and plant height (153.27–636.5 cm) were among traits that exhibited broader variability. Correlations between quantitative traits were determined. Grain yield for instance exhibited highly positive association with panicle weight (í µí±Ÿ = 0.901, í µí±ƒ = 0.000) and 100 seed weight (í µí±Ÿ = 0.247, í µí±ƒ = 0.000). UPGMA cluster analysis classified the 142 accessions into 89 morphotypes. Based on multivariate analysis, twenty promising sorghum genotypes were selected. Among them, AT41, AT14, and AT29 showed early maturity (57 to 66 days to 50% flowering), high grain yields (4.85 to 7.85 tons/ha), and shorter plant height (153.27 to 180.37 cm). The results obtained will help enhancing sorghum production and diversity and developing new varieties that will be better adapted to the current soil and climate conditions in Benin.
Technical Report
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The activities of NAIP Component-1 were oriented towards capacity building in NARS for adapting or response to the fast changing requirements of research, technology development and dissemination in the scenario of globalized agriculture. The aim of the Component was mainly to create a conducive environment that could ensure better flow of knowledge, collaborations, experimentations and implementation of innovations in terms of (a) information, communication and dissemination systems, (b) competitive business planning and technology commercialization models, (c) advance learning and state-of-the-art capacity building initiatives, (d) value added market intelligence services, (e) sound monitoring and evaluation (M&E), and strengthened impact evaluation systems, and (f) project friendly financial management and procurement systems. With the aim to create an enabling environment for the management of change; to increase efficiency, effectiveness and productivity of Indian NARS, the objectives of Component-1 were addressed through 55 sub-projects distributed over five sub-components namely; Information, Communication and Dissemination System (22); Business Planning and Development (23); Learning and Capacity Building (2); Policy, Gender Analysis and Visioning (7), and Remodelling Financial and Procurement Systems (1). The Project Implementation Unit (PIU) of NAIP was also a part of this component.
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Maldandi is a popular sorghum variety for post-rainy or rabi cultivation in southern and central states of India, which is predominantly used for food purpose. Over time many landraces have been collected from these states which have vernacular connection with Maldandi. Genetic diversity among 82 Maldandi landraces, collected from such geographical regions was evaluated using both morphological (quantitative and qualitative) and SSR markers. In general, both morphological and SSR diversity revealed wide variability among the accessions studied. Euclidean distances based on 17 quantitative traits classified the accessions into two major clusters with two out groups, while the 19 qualitative traits clustered the accessions in one major cluster with six out groups. Sixteen out of 20 (80%) SSR markers detected polymorphism among the accessions with average PIC value of 0.36. Un-weighted neighbor joining clustering grouped the accessions into three clusters with 46, 16 and 17 accessions, respectively throwing three outliers. Average similarity coefficients of 0.62 and 0.34 based on morphological (qualitative) and SSR data indicated presence of wide variability among the Maldandi landraces. The standard check, M 35–1 (a selection from the original Maldandi) could not be differentiated from EP 98, LG 2, LG 10, IS 4509 and IS 40791 based on qualitative data alone, while EP 54 and IS 33839 were indistinguishable from M 35–1 solely using SSR markers. Either of the dendrogram threw unique grouping patterns with some identity. Thirteen promising Maldandi accessions selected based on field performance as well as morphological and molecular diversity could be used in the rabi improvement programme. SSR markers combined with morphological traits may effectively be used for designing breeding strategy and management of biodiversity and conservation of Maldandi genetic resources.
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A total of 415 sorghum (Sorghum bicolor (L.) Moench) accessions representing different regions of Ethiopia, Eritrea and a group of introduced lines were evaluated for 15 quantitative characters to determine the extent and geographical pattern of morphological variation. The extent of variation was highly pronounced for agronomically important characters for sorghum. These characters included plant height, days for 50% flowering, peduncle exsertion, panicle length and width, number and length of primary branches per panicle and thousand seed weight. Significant regional variation was also observed for most of the characters. The results implied that environmental factors such as altitude, rainfall, temperature and growing period are important in regional variation. Mean for plant height and for days for 50% flowering showed clinal variation along the gradients of rainfall pattern and growing period in Ethiopia. Moreover, there were significant positive correlation coefficients between most of the characters. This included the correlation between agronomic characters of primary interest in sorghum breeding such as plant height and days for 50% flowering and also between various characters and the altitude of the collection sites. The implications of the results in plant breeding, germplasm collection and conservation as well as the probable sources of the wide range of variation are discussed.
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Plant breeders traditionally have estimated genotypic and phenotypic correlations between traits using the method of moments on the basis of a multivariate analysis of variance (MANOVA). Drawbacks of using the method of moments to estimate variance and covariance components include the possibility of obtaining estimates outside of parameter bounds, reduced estimation efficiency, and ignorance of the estimators' distributional properties when data are missing. An alternative approach that does not suffer these problems, but depends on the assumption of normally distributed random effects and large sample sizes, is restricted maximum likelihood (REML). This paper illustrates the use of Proc MIXED of the SAS system to implement REML estimation of genotypic and phenotypic correlations. Additionally, a method to obtain approximate parametric estimates of the sampling variances of the correlation estimates is presented. MANOVA and REML methods were compared with a real data set and with simulated data. The simulation study examined the effects of different correlation parameter values, genotypic and environmental sample sizes, and proportion of missing data on Type I and Type II error rates and on accuracy of confidence intervals. The two methods provided similar results when data were balanced or only 5% of data were missing. However, when 15 or 25% data were missing, the REML method generally performed better, resulting in higher power of detection of correlations and more accurate 95% confidence intervals. Samples of at least 75 genotypes and two environments are recommended to obtain accurate confidence intervals using the proposed method.
Twenty six varieties of forage sorghum [Sorghum bicolor (L.) Moench] which included 20 released and notified and 6 indigenous local varieties were characterized using 40 morphological descriptors adopted from the DUS guidelines of PPV & FR Authority and ICAR and subsequently examined for their Distinctiveness, Uniformity and Stability. Among the 26 visually assessed characters 2 characters were monomorphic, 10 characters were dimorphic and 14 characters were polymorphic indicating their potential for varietal characterization and distinctiveness. No intra-varietal variation was observed for any of the visual characteristics and expression of characters in different varieties remained same for the two consecutive years confirming the uniformity and stability of the varieties. Combined Over Years Distinctiveness (COY-D) analysis was made on 14 measurable DUS descriptors which revealed distinctiveness for all the 26 varieties. COY-D analysis supported with MJRA analysis revealed that the slope of the MJRA curve and regression probability were too negligible which indicated that all the considered characteristics were independent and their interactions with environment as well as with themselves were negligible in both the years. This indicates the distinctiveness of all the candidate varieties. Combined Over Years Uniformity (COY-U) analysis revealed that all the released and notified varieties were more or less uniform for the 14 measurable characters. However, three local varieties viz., Rampur local, Gwalior local and Rajasthan local were not uniform for 7, 6 and 4 measurable characters respectively emphasizing the need for their further purification to attain a considerable level of homogeneity in their heterogeneous blend. The present experimental material possessed relatively low magnitude of differences between PCV and GCV, high heritability coupled with high to moderate genetic advance for most of the measurable descriptors, thus emphasizing their consistency and stability over the years and their utility in varietal characterization. On the basis of grouping characteristics unique morphological profiles could be established for 9 varieties. When all the 33 morphological descriptors of PPV & FR Authority and 7 morphological descriptors of ICAR were studied distinctiveness could be obtained for two more varieties viz., UPFS 38 and SSG 59-3. Thus out of a total of twenty six varieties unique morphological profiles could be obtained for 11 varieties. However, the rest of 15 varieties remained in groups of two or three varieties. Thus the morphological DUS descriptors could establish distinctiveness of some varieties but varieties showing overlapping of the expression for these characters could not be discriminated hence some other markers/ descriptors could be thought for complementing the morphological DUS descriptors.
A study was conducted during rainy (kharif) seasons of 2003-04 to evaluate 29 sorghum (Sorghum bicolor L. Moench) cultivars for 39 agro-morphological traits used in DUS testing (UPOV guidelines). Analysis of variance showed significant differences among cultivars for 35 traits. Large variation among cultivars was found for the traits, time of panicle emergence (65-87 days), plant total height (120-272 cm), leaf length (57-87 cm), panicle length (22- 35 cm), 1 000-grain weight (23-46 g). Selections can be practised for traits, such as discolouration of midrib of flag leaf, yellow colouration of midrib of flag leaf, lemma arista formation and yellow colouration of stigma as they are governed by additive gene action. The 12 traits are governed by the non-additive gene effects and can be made use in developing distinct hybrid. Four out of 6 of the male sterile lines were grouped in same cluster revealing low divergence among them, emphasizing the need to diversify the female lines for DUS testing traits.
A comparison of the different methods of the estimation of genetic diversity is important to evaluate their utility as a tool in germplasm conservation and plant breeding. Amplified fragment length polymorphism (AFLP), microsatellites or SSR and morphological traits markers were used to evaluate 45 sorghum germplasm for genetic diversity assessment and discrimination power. The mean polymorphism information content (PIC) values were 0.65 (AFLPs) and 0.46 (SSRs). The average pairwise genetic distance estimates were 0.57 (morphological traits), 0.62 (AFLPs) and 0.60 (SSRs) markers data sets. The Shannon diversity index was higher for morphological traits (0.678) than AFLP (0.487) and SSR (0.539). The correlation coefficients obtained by the Mantel matrix correspondence test, which was used to compare the cophenetic matrices for the different markers, showed that estimated values of genetic relationship given for AFLP and SSR markers, as well as for morphological and SSR markers were significantly related (p<0.001). However, morphological and AFLP data showed non-significant correlation (p>0.05). Both data sets from AFLP and SSR allowed all accessions to be uniquely identified; two accessions could not be distinguished by the morphological data. In summary, AFLP and SSR markers proved to be efficient tools in assessing the genetic variability among sorghum genotypes. The patterns of variation appeared to be consistent for the three marker systems, and they can be used for designing breeding programmes, conservation of germplasm and management of sorghum genetic resources.