Stability for Grain Yield in Little Millet

Department of Genetics and Plant Breeding
ACHARYA N.G RANGAAGRICULTURAL UNIVERSITY,
AGRICULTURAL COLLEGE,BAPATLA.
MASTER'S SEMINAR
TOPIC : Stability for Grain Yield in Little Millet
(Panicum sumatrense)
Course No : GP-591
Department : Genetics and Plant Breeding
Agricultural College, Bapatla

Submitted by,
M. Muni Khyathi,
BAM-20-20,
Department of
Genetics and Plant
Breeding
Stability for Grain Yield in
Little Millet (Panicum
sumatrense)
Submitted to,
Dr. T. Srinivas,
Professor and Head,
Department of
Genetics and Plant
Breeding

Contents:
 Introduction
 Nutritional status
 Importance
 Crop improvement
 Variability
 Heritability
 Genetic advance
 Stability
 Case studies

Taxonomic position
 Kingdom: Plantae
 Sub-kingdom: Tracheobionta
 Super-division: Spermatophyta
 Division: Angiospermae/ Magnoliophyta
 Class: Monocotyledonae
 Sub-class: Commelinidae
 Order: Poales
 Family: Poaceae
 Sub-family: Panicoideae
 Genus: Panicum
 Species: sumatrense
(Source: www.wikipedia.org)

Introduction:
 Little millet (Panicum sumatrense), locally known as
‘Samalu’ is a traditional crop among cereal crops
commonly cultivated in the subtropical and tropical areas
of the country.
 It has diploid chromosome number 2n = 36,
 In India, it is grown in Karnataka, Tamil Nadu, Orissa,
Madhya Pradesh and Andhra Pradesh.
 13 varieties are released during 1986 to 2009 in Little
millet.
 Little millet in India is cultivated in an area of 0.26 m ha
with 0.12 m t of production. (Vetriventhan et al., 2020)

(Source: All India Coordinated Small
Millets Improvement Project)

Proximate profile of dehulled little millet
samples
Fat (g%) Starch
(g%)
Protein
(g%)
Total Phenol
Concentration
(TPC) (mg %)
Ascorbic Acid
Equivalent
(AAEQ)
Sama 2.59±0.00
4
65.87±0.01
5
12.65±0.1
98
34.453±3.09 211.23±8.4
LAVT-
1
2.2±0.001 62.32±0.01
0
12.77±0.0
06
21.464±1.74 198.59±0.3
(Source: AICRP- Small millets: Annual report
2019-2020)
•Little millet contains fiber and minerals such as zinc,
iron and calcium and others like potassium,
magnesium and vitamin B3.
•It shows higher concentration of magnesium than
other small millets.
Nutritional status:

Importance:
 Small millets are rich in micronutrients and account for
about 10% of global millet production.
 They are extremely resilient in the face of drought and
other abiotic stresses, making them valuable food
security crops for millions living in marginal
environments.
(Source: www.wikipedia.org)

Health benefits:
 Little millet, bestowed with fibre and minerals such
as potassium, zinc, iron and calcium and vitamin B3
supports fat metabolism, tissue repair, reduces
cholesterol and energy production.
 It is beneficial for health due to the presence of
bioactive neutaceuticals such as phenolic compunds,
gamma amino butyric acid (GABA), carotenoids and
tocoferols.
 Little millet is non-glutinous (non-sticky) and are not
acid-forming foods, thus making them very easy to
digest.

Crop improvement
 IC0483220, IC0483429, GPMR1153-2 were early
maturing.
 Two millets exploration programme were undertaken in the
states of Maharashtra, Karnataka and Tamil Nadu.
 Of the 125 millets accessions collected, 8 are of little millet
(Source: AICRP- Small millets: Annual report 2019-2020)

Little millet elite germplasm
 Twenty elite germplasm from NBPGR and 12 IIMR promising
selections were evaluated during kharif, 2019 at three locations viz.,
Hyderabad, Akola and Hagari.
 Based on the performance for grain yield at Hyderabad, 6 lines were
promising over the better check DHLM36-3 viz., IC-0483220, IC-
0483142, IC-0298429, IIMR-7, GPMR-223, GPMR-960.
 At Hagari, the lines, GPMR 1153-2, GPMR-6, IC-0483220, IC-
0483359, IC-0483429 were superior over the better check DHLM 36-
3.
 Based on the mean of two locations, five lines were promising for
grain yield and related traits.
 Among five lines, three lines IC-0483220, IC-0483429, GPMR1153-2
were early maturing.
(Source: AICRP- Small millets: Annual report 2019-2020)

Promising germplasm lines for grain
yield
Germplasm
Plant
height
(cm)
Tillers
(no.)
Panicle
length (cm)
Days to
Maturity
(d)
Grain yield
(g/plot)
% increase
over
DHLM36-3
(check)
IC0483220 96.4 3.1 18.2 96 345 16.81
IC0483359 105.4 3.4 21 110 325 11.69
IC0483429 105 2.1 19.6 86 320 10.31
IIMR-7 124.7 2.3 21.7 112 305 5.90
GPMR1153-2 100.3 3.2 20.8 96 347.5 17.41
DHLM36-3
(check)
116 3.2 25.7 96 287.5
(Source: AICRP- Small millets: Annual report 2019-
2020)

Variability:
 Definition:
The amount of variation present among the members of
a population or species; may have reference to one or
more characters, and at genotypic or phenotypic levels.
 Genetic variability:
The amount of genetic variation present among the
members of a species.
(Source: Singh, B.D, 2016)

Types:
 Free variability: Genetic variability available for selection to
act on.
 Potential variability: Genetic variability not available for
selection to act on.
 Homozygotic Potential variability: Variability stored in
homozygotes having intermediate phenotypes.
 Heterozygotic Potential variability: Variability stored in
heterozygotes.
 Mather (1973) hypothesised that all 3 states of variability
remain in a dynamic equilibrium through constant crossing,
segregation and recombination.

Flow of variability from one state to another in random mating
population
(Source: Chahal, G.S and Gosal, S.S,
2015)

Heritability:
 In crop improvement, only the genetic component of variation
is important since only this component is transmitted to the
next generation.
 The ratio of genetic variance to the total variance i.e.
phenotypic variance is known as heritability.
H = Vg / Vp
Vp = Vg+Ve
 Where, Vp = Phenotypic variance
Vg = Genotypic variance
Ve = Error variance of environmental variance
(Source: Phundan Singh, 2019)

 Two specific types of heritability can be estimated.
 The broad-sense heritability is the ratio of total
genetic variance to total phenotypic variance.
 H(bs) = Vg/Vp x 100
 The narrow-sense heritability is the ratio of additive
genetic variance to the total phenotypic variance.
 H(ns)=1/2 D/Vp
 Where, D = Additive genetic variance.
Vp= Phenotypic variance
(Source: Phundan Singh, 2019)

Genetic Advance :
 Improvement in the mean genotypic value of the selected
families over that of the base population is known as
Genetic Advance
 It can be predicted by the following formula.
Gs = K X σp X H
Where,
K = Selection intensity 2.06 when 5% of the population is
selected
σp = Phenotypic standard deviation of the character in the
population

Stability:
 Stability: Ability of a genotype to produce a narrow range of
phenotypes that perform well over a range of environments.
 Stability analysis: An analysis to estimate the adaptability of
a genotype.
 Homeostatic stability: Stability resulting from homeostasis.
 Agronomic stability: ability of a genotype to perform well
relative to the productive potential of the concerned
environment, desirable in improved varieties.
 It is important to identify genotypes with stable performance
over environments. Such identification of stable genotypes can
be done by carrying out stability analysis of multi location
trails.
 Stability analysis helps in accurate estimation of yield.

Case
Studies

Case Study-1
Genetic variability, heritability and
correlation of
quantitative traits in little millet genotypes
N Anuradha, TSSK Patro, M Divya, Y Sandhya Rani and U Triveni
Journal of Pharmacognosy and Phytochemistry
NAAS rating: **

 30 little millet genotypes including three national and one
local check varieties, viz., OLM 203, JK 8, BL 6 and Pedda
Sama were evaluated at Agricultural Research Station,
Vizianagaram, Andhra Pradesh during kharif, 2016.
 Genotypes were sown in a randomized complete block
design (RCBD) in three replications with a spacing of 22.5 ×
7.5 cm per each entry.
 Each genotype was grown in 10 lines of 3 m length.
 Observations were recorded on plant height (cm), panicle
length (cm), productive tillers per plant, days to 50%
flowering, maturity, fodder yield (t/ha) and grain yield
(q/ha). (Source: Anuradha et al.,
2017)

Results and discussion:
 Early flowering was noticed in LM 74 (36.7 days) and WV 126
(96.4) was late in flowering.
 Highest grain yield was recorded in LM 148 (21.26q/ha) with
an average yield of 12.70 q/ha.
 The coefficient of variation was maximum (14.30 %) for fodder
yield followed by grain yield (12.45%).
 Grain yield ranged from 7.69 to 21.26 q/ha with a mean of
12.70 q/ha.
 Overall, the difference in duration was from 67 to 127 days
with a mean of 88.58 days.
 PCV of all the traits was higher than GCV
(Source: Anuradha et al., 2017)

•Table 1 revealed existence of enormous variability in 30 little
millet genotypes under study for all the characters considered.

(Source: Anuradha et al.,
2017)

•PCV of all the traits was higher than GCV.
•Highest GCV and PCV were observed for fodder yield, days to 50%
flowering and grain yield indicating presence of more amount of
variability of these two traits among little millet genotypes.
•GCV and PCV are low for plant height indicating lesser variability of
this trait in the population.

• Association of different characters gives an insight about
simultaneous selection of characters.
• Both phenotypic and genotypic correlations were
significantly high and were in positive direction for grain
yield with panicle length, number of productive tillers per
plant and fodder yield.
• Days to 50% flowering was highly and positively
associated with days to maturity and negatively associated
with plant height, number of productive tillers per plant and
fodder yield.
• But, there is no association of days to 50% flowering with
grain yield in the present study.
• Hence, in this population of 30 genotypes, selection for
panicle length and number of productive tillers per plant
will lead to higher grain yield.

Conclusion:
 Higher variability is exhibited by fodder yield, days to
50% flowering and grain yield where GCV and PCV
are high.
 Number of productive tillers per plant, panicle length
and fodder yield are having significant positive
association with grain yield per plant, predominantly
controlled by additive gene action.
 Hence, selection of grain yield via these traits is
effective.

Case Study-2
Studies on genetic parameters, character association
and path analysis of yield and its components in little
millet (Panicum sumatrense)
Jyothsna S., Patro T.S.S.K., Sandhya Rani Y., Neeraja B., Ashok S. and Triveni U.
International Journal of Agriculture Sciences
NAAS rating: 4.73

 The field experiment was conducted at Agricultural
Research Station, Vizianagaram during Kharif 2014. The
design adopted was Randomised Block Design with three
replications.
 The fertilizer dose of 60:40:30 kg NPK/ha (50% N in +
Full P & K at the time of sowing) was applied and seeds
were sown by hand dibbling. The remaining 50% N was
applied after three weeks of sowing.
 Observations were recorded on five plants for five
quantitative characters viz., plant height, number of
productive tillers per plant, days to 50% flowering,
days to maturity and grain yield per plot.
(Source: Jyothsna et al., 2016)

Analysis of variance (mean sum of squares) for yield and yield component characters in
little millet
Estimates of variability, heritability and genetic advance as per cent of mean for grain yield
and yield components in little millet

 The phenotypic coefficient of variance (PCV) was slightly higher
in magnitude than genotypic coefficient of variance (GCV) for all
the characters studied indicating the interaction of genotypes
with environment
 High PCV and GCV were recorded for number of productive
tillers per plant and grain yield per plot, indicating sufficient
variation among the genotypes studied
 Heritability estimates were high for days to 50% flowering
(99.00%), days to maturity (98.30%), plant height (82.90%) and
grain yield per plot (71.60%).
 High heritability coupled with high genetic advance was
observed for days to 50% flowering and grain yield per plot
indicating the importance of additive gene action in governing
the inheritance of these traits.

Phenotypic and genotypic correlation coefficient in 18 genotypes of little
millet

Path coefficients of yield and yield components of little millet

•Path analysis studies revealed that days to 50% flowering showed true relationship
by establishing significant positive association and direct effect on grain yield per
plot both at genotypic and phenotypic levels and plant height at genotypic level and
number of productive tillers at phenotypic level
(Source: Jyothsna et al, 2016)

Case Study-3
Variability, character association and path
analysis
studies in little millet (Panicum sumatrense)
L. Madhavilatha, M. Subba Rao, M. Shanthi Priya and M. Hemanth Kumar
Andhra Pradesh Journal of Agricultural Sciences
NAAS rating: 2.94

 An experiment was conducted with fifty little millet elite
germpalsm accessions at Agricultural Research Station,
Perumallapalle during kharif, 2014.
 The design adopted was RCBD with two replications.
 Observations were recorded on five randomly selected plants
for nine quantitative traits viz. days to 50% flowering, plant
height (cm),number of effective tillers per plant, flag leaf
length (cm), flag leaf width (cm), length of peduncle (cm),
length of inflorescence (cm), length of lower raceme (cm)
and grainyield per plant (gm).
 Heritability in broad sense was estimated.
 Genetic advance was estimated and was expressed as per cent
of mean.

Estimates of variability, heritability, and genetic advance as per cent mean for
quantitative traits in little millet
(Source: Madhavilatha et al., 2020)

Phenotypic (above diagonal) and genotypic (below diagonal) correlations
coefficients for quantitative traits in little millet

Phenotypic and Genotypic path coefficients of quantitative traits in little millet

Conclusion:
 Heritability estimates were high for grain yield, plant
height and number of effective tillers per plant which
indicated that these characters were less influenced by
environmental conditions and phenotypic selection would
be effective.
 Path analysis of grain yield revealed that plant height,
number of effective tillers per plant, length of
inflorescence, days to 50% flowering and flag leaf length
contributed maximum to the grain yield by having
significant positive association and direct effect on grain
yield per plant both at genotypic and phenotypic levels

Case Study-4
Genetic variability study in little millet (Panicum
miliare L.) genotypes in relation to yield and quality
traits
Savankumar N. Patel, Harshal E. Patil, Harshalkumar M. Modi and Th. Joydeep
Singh
International Journal of Current Microbiology and Applied Sciences
NAAS rating: **

 The experiment was conducted at Hill Millet Research Station,
Navsari Agricultural University, Waghai (The Dangs) using 32
genotypes of little millets in randomized block design with 3
replications.
 Data were recorded on total 16 morphological and biochemical
traits viz., days to 50 % flowering, days to maturity, zinc
content (mg), plant height at maturity (cm), 1000 seed
weight (g), fiber content (%), number of productive tillers
per plant, Protein content (%), number of branches per
panicle, ash content (%), Panicle length (cm), fat content
(%), grain yield per plant(g), calcium content (mg), straw
yield per plant (g), iron content (mg).
 Heritability in broad sense was estimated.
 Genetic advance was estimated and was expressed as per
cent of mean.

Different genotypes of little millet showing difference in
panicle shape and size
VR-37
WV-28
VR-49
VR-56
(Source: Savankumar et al.,
2018)

KOPLM-36
KOPLM-37
KOPLM-41
KOPLM-48
2018)

WV-32
WV-37
VR-52
VR-45
2018)

WV-125
KOPLM-18
KOPLM-
30
GPUL-27
2018)

Analysis of variance (Mean Sum of Square) for sixteen different characters of
little millet
•The genotypic
mean square
values were highly
significant for all
quantitative traits,
implying that the
genotypes tested
were highly
variable
2018)

Range, mean, component of variance for sixteen characters of little millet
(Source: Savankumar et al., 2018)

GCV%, PCV%, heritability, genetic advance and genetic advance as present of
mean of sixteen characters in thirty two genotype of little millet

Heritability (broad sense %) and genetic advance (% of mean) of various
quantitative characters of little millet

Conclusion:
 The high heritability coupled with high genetic advance
was observed for number of productive tillers per
plant, grain yield per plant, straw yield per plant, 1000
seed weight, protein content, ash content, fat content,
calcium content, iron content and fiber content.
 These characters are governed by additive gene
action.

References:
 www.wikipedia.org
 AICRP- Small millets: Annual report 2019-2020)
 Singh, B.D. 2016. Plant Breeding Principles and Methods. Kalyani
Publishers, New Delhi.
 Chahal, G.S and Gosal S.S. 2015. Principles and Procedures of Plant
Breeding- Biotechnological and conventional Approaches. Narosa
Publishing House, New Delhi.
 Phundan Singh. 2019. Essentials of Plant Breeding. Kalyani
Publishers, New Delhi.
 Vetriventhan, M., Azevedo, V.C., Upadhyaya, H.D., Nirmalakumari, A.,
Kane-Potaka, J., Anitha, S., Ceasar, S.A., Muthamilarasan, M.,
Bhat, B.V., Hariprasanna, K., Bellundagi, A., Cheruku, D.,
Backiyalakshmi, C., Santra, D., Vanniarajan, C and Tonapi, V. A. 2020.
Genetic and genomic resources, and breeding for accelerating
improvement of small millets: current status and future

References:
 Anuradha, N., Patro, T.S.S.K., Divya, M., Rani, Y.S and Triveni, U.
2017. Genetic variability, heritability and correlation of quantitative
traits in little millet genotypes. Journal of Pharmacognosy
and Phytochemistry. 6 (6): 489-492.
 Jyothsna, S., Patro, T.S.S.K., Rani, Y.S., Neeraja, B., Ashok, S and
Triveni, U. 2016. Studies on genetic parameters, character
association and path analysis of yield and its components in little
millet (Panicum sumatrense). International Journal of Agriculture
Sciences. 8 (5): 1018-1020
 Madhavilatha, L., Rao, M.S., Priya, M.S and Kumar, M.H. 2020.
Variability, character association and path analysis studies in little
millet (Panicum sumatrense). Andhra Pradesh Journal of Agrcultural
Sciences. 6 (1): 49-54.
 Savankumar N. Patel, Harshal E. Patil, Harshalkumar M. Modi1 and
Th. Joydeep Singh. 2018. Genetic variability study in little millet

Stability for Grain Yield in Little Millet

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