Revolutionary use of Linseed in enhancing Nutritional security

3. FLAX or LINSEED

4. REVOLUTIONARY USE OF
LINSEED
IN ENHANCING
NUTRITIONAL SECURITY
PR E S E N T E D BY
Darshana Patra

5.  It is a popular food among urban
consumers but farmers are
gradually withdrawing from
cultivation of this wonder seed
despite of its growing demand.
 At present, linseed is cultivated in
about 3.42 lakh ha with the
contribution of 1.537 lakh tons to
the annual oilseed production of
our country and the yield being
449 kg/ ha is far below the world
production of 21.23 lakh tons from
21.12 lakh ha with productivity of
1006 kg/ ha (2011).
Linseed or flaxseed is a health and nutritional primer

7.  There is a need to bring a huge revolution for the cultivation of
linseed for its essential oil, seeds and natural fibre (i.e. linen which
is made from the stalk of flax plant).
 Apart from omega-3, linseed is also rich in proteins, magnesium and
vitamins, particularly vitamin B1, which provide multiple health
benefits.
 Fibre of the flax plants is widely used in textile industry and this
way flaxseed can be used as a dual purpose crop.
 There is a need for genetic improvement for its qualitative and yield
attributing characters of linseed.

8. HOW TO START ?
 For this, specific genotypes can be developed for higher oil content
and essential anti-oxidants, metabolites using targeted crop breeding
by scanning desirable genotypes of various linseed cultivars found in
our ecosystem for the yield enhancement.
 It must be simultaneously followed by biochemical assessment of
ALA and UFA for its utility in medicinal and industrial aspect.
 Dietary supplementation of these linseed genotypes in form of whole
seeds , powdered form, oil capsules can help to curb multifarious
urban health disorder , mental issues, post natal problems faced by
millions of people today .

9. MORPHOLOGICAL AND BIOCHEMICAL
CHARACTERIZATION OF LINSEED
Objectives :
 EVALUATION of pre existing linseed genotypes for yield and components
traits and identify promising genotypes based on per se performance.
 EXAMINE the nature of variation & the scope of selection for the elite lines.
 ASSESS the existing genetic diversity and grouping them by multivariate
techniques to understand the magnitude of genetic divergence.
 RECORD morphological and biochemical characters for higher seed and oil
yield estimation.
 ANALYSE the fatty acid compositions of seed oil using gas chromatography
and near infrared spectroscopy.

10. RELEVANCE OF THIS STUDY :
 Non availability of good genotypes for local
conditions
 Farmers preference for other oilseeds instead of
linseed in spite of its higher nutritive values
 Selection of high ALA genotypes for better
market value.
 Selection for short stature genotypes for seed
purposes.

11.  Brief description of experimental site
 Brief description of materials used in the study
 Brief description of experimental details
 Brief description of experimental methods followed

12. GENERAL VIEW OF EXPERIMENTAL PLOT

13.  The present investigation undertaken at EB-II
section of the Department of PBG, CA, during
Rabi, 2016-17
 Geographically the site is located at 200 52` N
latitude, 820 52` E longitude , at an altitude of
25.9 m above MSL
 Humid and sub-tropical climate
 Materials provided by OUAT , Bhubaneswar
 Sowing Date : 6TH December 2016
 Harvesting Date : 11th March 2017

14.  Experimental Design : RBD with two replications
 Plot Size : Each genotype sown
 In four lines of 3 m row length
 30 cm spacing between lines
 10 cm spacing between plants within a line
 52 number of elite Indian linseed genotypes with
checks
 Experimental materials comprising of advanced
breeding lines , progeny of inter varietal crosses,
and commercial varieties
EXPERIMENTAL DETAILS

15. LIST OF CHARACTERS STUDIED
 The phenotypic observations were recorded
on
 Days to 50% Flowering
 Days to maturity
 Plant Height (cm)
 Number of branches per plant
 Number of capsules per plant
 Number of seeds per capsule
 1000-seed weight (g)
 Single plant yield (g)

16. BIOCHEMICAL ANALYSIS :
 The composite processed seed samples were analysed for
estimating different biochemical parameters of fifty two
accessions as follows on percentage basis :
 Fatty Acid Composition
 Moisture Content
 Protein Content
 Oil Content
 Glucosinolate Content
 This study was carried out using Gas Chromatography and
Near Infrared Spectroscopy (NIRS) during my internship
research work at DUSC, New Delhi.

17. DETAILS OF THE PARAMETERS
STUDIED :
1. Estimation of Genetic Variability was done by ANALYSIS
OF VARIANCE and subsequently the parameters of
variability :
 Range
 Grand Mean
 Phenotypic Coefficient of Variance
 Genotypic Coefficient of Variance
 Heritability
 Genetic Advance
 Genetic Advance as % of Mean
 CD at 5% level of significance
 CV

18. MULTIVARIATE ANALYSIS OF GENETIC
DIVERGENCE
Mahalanobis D2 statistics
 Clusters derived using Tocher’s method
 Estimation of Intra and Inter cluster distances
 Tabulation of Cluster means for 8 quantitative
characters
Contribution of different characters to total divergence
over all paired combinations (1485) by
 D2 for individual trait (Singh, 1981)
 Rank total for individual trait (Murthy and Quadri, 1966).

19. 2. Canonical analysis
 Estimation of Z1 and Z2 values as per Anderson
(1958) corresponding to the first two canonical vectors
 Supplement to grouping by Tocher’s method

20. 3. STUDY OF CHARACTER ASSOCIATION
3.1 CORRELATION STUDIES
 Analysis of covariance (ANCOVA)
 Computation of the genotypic, phenotypic and
environmental correlations between character pairs
were according to Robinson et al. (1951), Johnson et
al. (1955) and Al-Jibouri et al. (1958)
3.2 PATH ANALYSIS
 Partitioning of the correlations between a causal factor
and the effect variable into components of direct and
indirect effects
 yield was taken as the “effect” with 7 other characters
related to yield as the causal factors

21.  A brief description of the outcome of different analysis
 These can be utilized to derive a suitable crop
improvement programme and increase efficiency of
selection for different quantitative traits
RESULTS OF THE INVESTIGATION

22. PARAMETERS OF VARIABILITY
 The estimates of error variations ranged from 1.04 (days to
50% f) to 15.02 (capsules per plant), indicating high
precision during analysis.
 The PCV ranged from 2.00 % in days to maturity to 28.30%
for SPY.
 The GCV values were lower than PCV values with a range
of 1.77 % for days to maturity to 26.90 % for SPY.
 Low difference in GCV and PCV for days to 50%
flowering, days to maturity, capsules per plant and 1000-
seed weight – traits governed by genetic factors and
minor effect of environment

23.  Heritability (bs) estimates for 8 characters
 High heritability (> 90 %) : for days to 50% flowering (97.91%) and
SPY (90.38 %.)
 Moderate heritability (70-90 %) : days to maturity (78.28%), plant
height (83.82 %), branches per plant (82.95%), capsules per plant
(73.32%), 1ooo seed weight (85.67%).
 Low heritability < 70 % : for number of seeds per capsule (67.95 %).
 Genetic advance as per cent of mean
 Low(<10%): days to maturity (2.75%,) and days to 50%
flowering (8.79%)
 Moderate (10-20 %) : for 1000-s.w. (16.43 %), plant height
(14.21%), number of seeds per capsule (10.12%)
 High (> 20 %) : for SPY (45.01 %), number of branches per
plant (29.50 %) and capsules per plant (26.53%).

24.  The order of contribution to total divergence By Avg. D2
values from highest to lowest was from days to 50%F
(44.68 %), SPY (20.29 %), 1000 S.W. (12.25 %).
 On the basis of rank total too, the maximum and minimum
contribution was by days to 50%F (6.98 %), SPY (9.30 %),
1000 S.W. (11.15 %).
 The genotypes were grouped on the basis of genetic
closeness or divergence by D2 into 08 clusters. Cluster I
was found largest with 19 genotypes
 The three clusters VI, VII and VIII were comprising of a
single genotype each indicating that these three genotypes,
OL-98-6-2, V1K1-99-40, PADMINI B respectively

25. CHARACTER ASSOCIATION
 The high estimates of correlation both at genotypic and
phenotypic level was between yield and no of productive
branches per plant .
 Days to 50% flowering had positive significant correlation
with days to maturity, seeds per capsule at both phenotypic and
genotypic levels .
 Path analysis revealed that high direct positive effect on yield
was manifested by number of branches per plant (0.340)
followed by 1000-seed weight (0.302), days to maturity
(0.199), no. of seeds per capsule (0.164), no. of capsules per
plant in that order .

26.  The genotype means have wide differences for all the
characters except, 50 % flowering and maturity.
 The CVe for different traits was in a range 1.04 (DFF)
to 15.02 (CPP) indicating a high degree of precision in
the investigation
 Very low difference in the magnitude of PCV and GCV
for the characters DFF, DM, PH, TSW indicated that
they were less influenced by the environment
 High heritability coupled with high GA for 1000-Seed
Weight indicated the role of additive gene action.

27.  Eight clusters were obtained by following Tocher’s method. Out
of the 52 genotypes, 19 were grouped in Cluster I and 12 in
Cluster II
 Three clusters to VI, VII and VIII were comprised of single
genotype
 The assessment of intra and intercluster divergence revealed that
cluster V was most divergent from all other Clusters
 DFF being the greatest contributor to total divergence with
average D2 of (44.68 %) and also the highest rank (lowest value
6.98)
 As a supplement to D2, canonical analysis was carried out by
calculation of Z1 (contribution 65 %) and z2 (contribution 14.3
%)

28. Cluster Composition Of 52 Genotypes On The Basis Of
D2 Analysis
Cluster
No. of
genotypes
Name of the elite linseed genotypes
I 19
T-397, OLC-10 B ,OL-98-14-3, OLC-15 , OLC-51 ,
V2K3-99-71-1, LCK-9930, RLC-93 , OML-3, JAWAHAR,
OL-98-13-1A, NL-157, RLC-95, OL-98-15-2, V2K3-99-70-1, LCK-2108, NL-119,
OLC-10A, JLT-32
II 12
OL-98-15-3, PADMINI A, V1K2-99-48, INDIRAALSI, RLC-74,
V1-K2-99-57, V1-K2-99-90, JLT-62, OL-98-14-2,SLS-51,
KARTIK, SUVRA
III 12
SLS-52, V1-K1-99-44, OLC-11, SWETA, V2-K3-99-54-1,
LMS-17-2K, NDL-204,OL-98-6-4, OL-98-7-3, NDL-205,
OL-98-7-1, KIRAN
IV 4 GARIMA, OL-98-7-4, NL-97, LMS-47-2K
V 2 OL-98-13-2, OL-98-13-1B
VI 1 OL-98-6-2
VII 1 V1K1-99-40
VIII 1 PADMINI B

29. MULTIVARIATE CLUSTER ANALYSIS

30. MULTIVARIATE ANALYSIS OF GENETIC DIVERGENCE
 D2 values for all the 1326
combinations ranged from 4.34 to
604.68.
Highest Divergence Lowest Divergence
OL-98-7-4 and V2K3-99-71-1
604.68
T-397 and OLC-10B
4.34
OL-98-7-4 and OML-3
564.51
JLT-32 and Indira Alsi 5.57
OLC-15 and Garima
551.75
Padmini A and OL-98-15-3
6.53

32. • According to the joint recommendation by Food and
Agriculture Organization and World Health
Organization (FAO/WHO) committee, the ideal ω-
6/ω-3 ratio should be between 5:1 and 10:1.
• A lower ratio of ω-6/ω-3 FAs is more desirable in
reducing the risk of many chronic diseases of high
prevalence in Western societies, as well as in the
developing countries.

33. • Therefore, to promote normal growth and development as well as to
maintain good human health, it is essential to rectify the imbalance in the
ω-6/ω-3 ratio by restoring sources of ω-3 FAs in the diet.
• There are few agricultural sources of high ALA (ω-3 FA), such as green
leafy vegetables, chia, perilla, hemp, flax, purslane etc.
• However, flaxseed with its high level of ALA and ω-6/ω-3 ratio of 0.3
to1.0 can help to restore the ω-6 and ω-3 FA balance in the human body .

35. FUTURE LINE OF WORK
• Superior lines can be used as genetic stock in breeding programme.
• Genotypes which are genetically diverse, having complimentary characters
can
be used as parents for further breeding programme.
• The promising genotypes should also be screened for resistance against
various
pest and diseases in artificial epiphytic condition.
• The genetic diversity among the germplasm lines needs to be assessed
using
molecular markers.
• The potential ALA content of linseed is up to 66 percent, so the elite lines can
be
subjected to induced mutagenesis for enhancing ALA content.

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