This topic gives the wide range in understanding the advances for managing the abiotic stress that occurs in the pulse crops like pigeonpea,mungbean,chickpea etc.

1. Name of Speaker : Parthvee R. Damor. Course No : PP 691
Major Advisor : Dr. A. D. Patel Date : 22/12/16
Minor Advisor : Dr. H. C. Patel Time : 14:00 hrs
Degree : Ph.D. (Plant Physiology) Reg. No : 04-2584-2015
Recent advances for management
of abiotic stress in pulse crops

2. Introduction
Overview of abiotic stress
Impact of abiotic stress on
pulses
Review of literature
Overview of work at IIPR, Kanpur
Conclusion
Future thrust

3. Introduction
 Important segments of Indian
Agriculture after cereals and oilseeds.
 Good sources of proteins and commonly
called the poor man’s meat . Pulses are an
affordable source of protein.
 Frequency of pulses consumption is
much higher. About 89 % of population in
world consume pulses at least once a
week.
 Pulse crops reported huge losses due to
abiotic (drought, high temperature, etc.)
stresses.
 Food security issues required that we learn to
understand how pulse crops may be protected
against abiotic stresses.
3

4. Present status
 India is the largest producer of pulses in
the world, with 25% share in the global
production followed by Burma, Canada and
China.
 The important pulse crops are chickpea
(48%), pigeonpea (15%), mungbean (7%),
urdbean (7%), lentil (5%) and fieldpea (5%).
 The major pulse-producing states are Madhya
Pradesh, Maharashtra, Rajasthan, Uttar Pradesh,
Karnataka, Andhra Pradesh and Gujarat which
together account for about 80% of the total
production.
Chickpea Mungbean
Urdbean
Rajmash
Lathyrus
Pigeonpea
Fieldpea
Lentil
4
However, the highest productivity in India is in
Punjab (905 kg/ha) followed by Haryana (891 kg/ha)
upto 2011-12 according to DES, DAC, Ministry of
Agriculture, Krishi Bhavan, New Delhi

5. Table 1: Area, Production & Yield
of Pulses in India
5
Years Area (In MH) Production
(In MT)
Productivity
(In Kg/Hectare)
Kharif Rabi Total Kharif Rabi Total Kharif Rabi Total
2010-11 12.32 14.08 26.40 71.20 11.12 18.24 578 789 691
2011-12 11.19 13.27 24.46 60.58 11.03 17.08 541 831 691
2012-13 99.54 13.30 23.25 59.16 12.42 18.34 594 934 789
2013-14 10.32 14.88 25.21 59.93 13.26 19.25 580 891 764
2014-15 99.98 13.55 23.55 57.31 11.42 17.15 573 843 728
2015-16# 10.31$ 13.69$ - 55.40 10.93 16.47 - - -
2016-17$ - - - 87.00 - 87.00 - - -
Note : $ : 1st Advance Esitmates.
# : 4th Advance Estimates.
As on 22.09.2016
Source : Ministry of Agriculture & Farmers welfare, Govt. of India. (ON1167) & (ON1195) &
Past Issues. (INDIASTAT)
5

6. Table 2: Area, Production And Yield Of Pulse Crops In Gujarat State For The Year 2008- 09 to 2010-11
Area Mha., Production MT, Yield kg/Ha.
TOTAL PULSES
DISTRICT
2008-2009 2009-10 2010-11
A P Y A P Y A P Y
AHMEDABAD 326 191 586 152 90 592 88 61 693
ANAND 59 37 627 61 41 672 52 34 654
BANASKANTHA 399 211 529 343 127 370 256 211 824
BHARUCH 671 464 692 760 497 654 716 658 919
DAHOD 595 472 793 669 479 716 726 631 869
DANG 101 89 881 116 90 776 97 68 701
GANDHINAGAR 57 34 596 130 83 638 42 29 690
KHEDA 53 39 736 55 30 545 56 48 857
MEHSANA 289 172 595 271 116 428 206 123 597
NARMADA 235 224 953 208 213 1024 189 166 878
NAVSARI 85 70 824 157 120 764 111 101 910
PANCHMAHAL 453 506 1117 439 419 954 389 477 1226
PATAN 420 218 519 379 106 280 369 213 577
SABARKANTHA 415 303 730 395 227 575 358 233 651
SURAT 215 207 963 156 206 1321 167 183 1096
TAPI 217 136 627 247 170 688 232 162 698
VADODARA 952 986 1036 909 872 959 939 975 1038
VALSAD 155 101 652 192 125 651 112 75 670
AMRELI 172 172 1000 95 82 863 85 70 824
BHAVNAGAR 100 65 650 62 32 516 82 68 829
JAMNAGAR 338 404 1195 278 383 1378 328 403 1229
JUNAGADH 150 167 1113 131 131 1000 203 244 1202
KUTCH 914 327 358 785 326 415 898 433 482
PORBANDAR 153 191 1248 78 79 1013 130 162 1246
RAJKOT 150 183 1220 193 135 699 205 185 902
SURENDRANAGAR 166 124 747 99 41 414 281 293 1043
GUJARAT STATE 7840 6093 777 7356 5193 706 7317 6306 862
Source: NFSM. Estimates for pulses 2012

7. Dry Grain Pulses: Its Importance
• Play diverse role in farming systems in developing countries.
Food crop (consumed as grain, green pods and
leaves) (contributes to food security and dietary
diversity goal)
Cash crop (source of income poverty goal)
Fodder crop (contributes to the productivity of
livestock system)
Rotation crop, intercrop with cereals and
root/tubers (reduces soil pathogens and provide
nitrogen environmental sustainability goal)
7

8. Food Grains Requirements: Upto 2050-51
Masood Ali and Sanjeev Gupta (2012)
Year Population
(million)
Requirement
(Mt)
Production (Mt) Import(Mt)
2000–01 1027 16.02 11.08 0.35
2004–05 1096 17.10 13.13 1.31
2009–10 1175 18.33 14.60 2.83
2020–21 1225 19.10
2050–51 1613 26.50
Table 3. Requirement, production and import of pulses in India
IIPR, Kanpur
8

9. What is Stress?
“ Mechanical force per unit area applied
to an object.”
“Stress is any adverse environmental
factor or condition that affects
normal metabolic or physiological
processes.
 It may be
PHYSICS
BIOLOGY
Biotic stress (living) Abiotic stress (non-living)
9

10. Abiotic Stress:
 Abiotic stress is defined as:
 Only 10% of the world arable land may be categorized as free
from stress.
“The negative impact of non-living factors on the living
organisms in a specific environment”
10

11. ABIOTIC STRESS
Water
stress
Temperature
stress
Salt stress
Other
abiotic
stresses
Stress due to
change in pH
Drought
stress
Water
logging
High
temp.
stress
low
temp.
stress
Low pH
i.e.
Acidity
High pH
i.e.
Alkalinity
High
velocity
wind
Heavy
metal
stress
Nutrient
stress
pollutants
Human
affairs
High
light
intensity 11

12. Fig.1: Overall Effect of Abiotic stress to Plant
Air pollution
Salinity stress
Drought stress
Temperature
stress
Light stress
Mechanical
damage
Cold stress
Vickers et al. (2009) 12

13. Complex plant response to abiotic stress
Shivangi Chamoli and A.K. Verma (2014)Pantnagar 13

14. Abiotic stress at various levels of complexity
• Cellular view
 Metabolic
 Transport
 Molecular
• The tissue and organ view:
 Meristems
 Root
 Shoot/leaf
 Flower/seed
• The whole plant view:
 Altered physiological status of plant
14

15. Growth stages of pulses at which the stress is
exerted
15

16. Impact of Abiotic stress on pulses
Environmental stress hampers the growth of pulses by disturbing normal
physiology and morphology
Pulses become more prone to oxidative damage by overproduction of
reactive oxygen species (ROS)
superoxide radicals
 hydrogen peroxide
 hydroxyl radicals.
These radicals disturb the cellular homeostasis of the cell resulting in
significant yield losses
16

17. Table 4: Importance of major abiotic stresses affecting pulse crops
Warm season pulses Cool season pulses
Stress Pigeon pea Urd bean Mung bean Chickpea Lentil
Drought ** * ** *** ***
Waterlogging *** *** *** * *
Heat * *** ** *** ***
Cold *** ** ** ** *
Salinity/alkal
inity
** * * ** **
Al toxicity ** ** ** ** **
***very important, **important, *not important
Sultana et al. (2014)BAU, Bihar 17

18. 18

19. Water Stress
Two main condition develop water
stress in plants.
1. Waterlogging
Drought stress
Waterlogging refers to the saturation of soil with water.
Soil may be regarded as waterlogged when the water
table of the groundwater is too high to conveniently permit
an anticipated activity, like agriculture. In agriculture,
various crops need air (specifically, oxygen) to a greater or
lesser depth in the soil.
Drought can be defined as the absence of rainfall or
irrigation for a period of time sufficient to deplete soil
moisture and injure plants.
19

20. Map showing drought
affected Areas In India-2016
(Source: http://www.mapsofindia.com/maps/india/drought-prone-areas.html) 20

21. Fig.2: Schematic presentation showing integrated approach of acclimation to water stress
Source:
21

22. Mechanisms of drought tolerance at different levels
Morphological mechanisms
Escape
 Escape from drought is attained through a shortened life cycle or growing season, allowing plants to reproduce before
the environment becomes dry.
Avoidance
 Drought avoidance consists of mechanisms that reduce water loss from plants, due to stomatal control of transpiration,
and also maintain water uptake through an extensive and prolific root system
Phenotypic flexibility
 Plants generally limit the number and area of leaves in response to drought stress just to cut down the water budget
at the cost of yield loss
Physiological mechanisms
Cell and tissue water conservation
Antioxidant defense
Cell membrane stability
Plant growth regulators
Compatible solutes and osmotic adjustment
Molecular mechanisms
Aquaporins Stress proteins Signaling and drought stress tolerance
22

23. Table 5: Plant water relation parameters and yield attributes at maturity of chickpea genotypes under
irrigated(I) and rainfed conditions in microplots.
Parameters Treatment HC-5 H02-36 H03-56 H04-31 H04-33 H04-45
Total dry weight
(g/plant)
Irrigated 22.13 16.40 19.12 14.49 16.47 14.88
Rainfed 25.07 17.95 18.19 14.63 15.46 13.82
LSD (P=0.05), G= 0.03,T=0.5, G×T =1.2
Root/Shoot ratio
(dry weight basis)
Irrigated 0.50 0.70 0.54 0.43 0.47 0.62
Rainfed 0.88 0.80 0.87 0.87 0.86 0.80
LSD (P=0.05), G=0.6,T=0.8,G×T =1.3
Relative water
content
Irrigated 92.0 89.9 88.3 86.2 84.3 84.1
Rainfed 82.0 82.0 80.0 72.4 78.4 77.8
LSD (P=0.05) G= 1.13, T= 0.14, G×T=3.20
Photosynthesis (mg
CO2/cm/h)
Irrigated 17.2 16.1 15.6 13.1 14.2 8.8
Rainfed 8.3 8.6 7.9 2.1 4.1 1.4
LSD (P= 0.05), G=0.05, T=0.05, G×T =0.14
Seed yield ( g/plant) Irrigated 20.6 18.5 16.8 15.2 17.3 14.3
Rainfed 16.9 14.2 13.4 11.2 13.2 12.5
LSD (P=0.05), G =0.30, T=3.14, G×T = 3.20
Haryana, India Kumar et al. (2010)
23

24. Fig 3: Rooting depth of chickpea genotypes under
irrigated (I) and rainfed (R) conditions in microplots
at full bloom stage.
Kumar et al. (2010)Haryana, India 24

25. Genotyp
es
Chlorophyll content
(SPAD values)
Net photosynthesis
rate (µmol m-2 s-1)
Stomatal conductance
[mol (H2O) m-2 s-1]
Intercellular CO2
concentration [µmol
(CO2) mol-1]
Normal WL
recovere
d
%
decline
Normal WL
recovere
d
%
decline
Normal WL
recovere
d
%
decline
Normal WL
recovere
d
%
decline
RG 188 55.67 12.96 76.72 10.57 2.31 78.15 0.23 0.11 52.56 223.48 227.31 1.71
ICP 8863 43.96 20.91 52.43 12.80 3.39 73.52 0.41 0.21 48.55 245.91 255.83 4.03
JKM 7 51.82 17.61 66.02 15.27 5.88 61.49 0.58 0.14 74.96 202.09 243.05 20.27
JP 10 43.37 18.54 57.25 11.11 1.94 82.54 0.27 0.11 61.54 230.49 261.49 13.45
C 11 50.10 20.71 58.66 9.92 2.21 77.72 0.21 0.10 51.92 191.35 222.58 16.32
ICPB
2039 56.38 19.26 65.84 15.63 6.05 61.29 0.40 0.18 55.72 254.12 264.99 4.28
ICPL
87051 57.31 23.67 58.70 15.78 7.61 51.77 0.65 0.26 59.53 256.60 264.23 2.97
ICPH
2740 57.51 18.44 67.94 9.64 2.93 69.61 0.27 0.13 54.38 194.14 200.16 3.10
ICPL
20241 49.99 13.73 72.53 21.03 7.55 64.10 0.79 0.27 65.48 312.66 325.22 4.02
ICPH
2431 68.95 17.60 74.47 13.58 3.22 76.29 0.28 0.09 66.31 206.55 223.76 8.33
ICPL
20128 52.18 19.74 62.17 17.85 6.40 64.15 0.58 0.22 61.96 244.06 259.64 6.38
KPBR 80-
2-1 59.75 21.59 63.87 19.85 8.30 58.19 0.73 0.28 61.26 305.72 321.75 5.24
Mean 53.92 18.73 64.72 14.42 4.82 68.24 0.45 0.18 59.51 238.93 255.83 7.51
SEm± 1.66 0.60 1.42 1.32 0.42 2.30 0.03 0.02 3.34 13.54 10.21 0.40
LSD(p ≤
0.05) 3.45 1.23 3.02 2.73 0.88 4.78 0.05 0.03 6.92 28.08 21.18 0.83
Table 6 : Chlorophyll content, net photosynthetic rate, stomatal conductance, intercellular CO2 concentration after 8 days of
recovery from waterlogging (WL) in pigeon pea genotypes
Meena et al. (2015)Madhya Pradesh, India 25

26. Well watered Water stressed Genotype Water Genotype
×water
DICC8156 DICC8172 DICC8156 DICC8172
Foliage dry weight (g per
plant)
87.8 ± 5.8 93.7 ± 3.7 40.1 ± 6.0 41.3 ± 2.0 NS *** NS
Seed yield (g per plant) 31.4 ± 1.1 35.6 ± 1.1 4.6 ± 0.5 5.5 ± 0.2 * *** NS
Harvest index 0.36 ± 0.02 0.38 ± 0.00 0.12 ± 0.02 0.13 ± 0.00 NS *** NS
Flowers (per plant) 174 ± 7 230 ± 25 86 ± 10 170 ± 24 ** ** NS
Aborted flowers (per
plant)
31 ± 4 54 ± 12 36 ± 5 98 ± 17 ** * NS
Percentage of flower
abortion
18 ± 2 23 ± 3 42 ± 4 58 ± 5 * *** NS
Total pods (per plant) 142 ± 3 177 ± 15 50 ± 7 71 ± 13 ** *** NS
Abscised pods (per plant) 17 ± 3 18 ± 2 11 ± 0 15 ± 3 NS NS NS
Percentage of abscised
pods
12 ± 2 10 ± 0 23 ± 3 21 ± 2 NS ** NS
Filled pods (per plant) 112 ± 2 130 ± 5 25 ± 3 31 ± 1 ** *** NS
Empty pods (per plant) 13 ± 2 28 ± 8 14 ± 4 25 ± 9 * NS NS
Percentage of empty pods 9 ± 1 15 ± 3 27 ± 4 32 ± 8 NS ** NS
No. of Seeds (per plant) 126 ± 5 188 ± 6 28 ± 4 38 ± 3 *** *** **
Mean seed weight (mg per
seed)
266 ± 14 189 ± 1 168 ± 7 145 ± 7 ** *** **
Table 7 : Foliage dry weight, seed yield, harvest index, yield components, percentage flower abortion, percentage abscised pods, and percentage
empty pods in well-watered and water-stressed genotypes of chickpea, DICC8156 and DICC8172, at physiological maturity
Pang et al. (2016)York, Western Australia
Data are means ±SE (n=3). *P<0.05; **P<0.01; ***P<0.001; NS, no significant difference
26

27. Phenophase
of imposing
DS
DSI STI MP
IPL-406 HUL-57 IPL-406 HUL-57 IPL-406 HUL-57
Mid-
vegetative
0.67 0.31 22.75 38.02 4.99 6.21
Flower
initiation
0.87 0.58 16.89 29.20 4.53 5.58
Pod
formation
1.03 0.88 12.64 19.50 4.21 4.88
SE± LSD
(P ≤ 0.05)
SE±• LSD
(P ≤ 0.05)
SE±• LSD
(P ≤ 0.05)
Genotype 0.01 0.04*** 0.41 1.30*** 0.04 0.13***
Phenophase 0.01 0.05*** 0.50 1.59*** 0.05 0.16***
Genotype ×
phenophase
0.02 0.07** 0.71 2.25*** 0.07 0.22**
*** Significant at P ≤ 0.001.
** Significant at P ≤ 0.01.
† Irrigation was withheld at specific phenophase till the plants experienced one cycle of permanent
wilting; thereafter, plants were kept at normal supply of water till maturity. DSI – drought susceptibility
index; STI – stress tolerance index; MP – mean productivity.
Table 8: Drought indices in two genotypes of lentil
Mishra et al. (2016)Varanasi, India 27

28. Fig 4: Specific leaf nitrogen (SLN) content (a) and nitrogen harvest index (NHI) (b) in two genotypes of lentil under well watered (WW, 1)
and drought stress (DS, 2) imposed at specific phenophase of growth. Values are means ― SE (n = 6) of pooled data of two years experiment.
Least significant differences (LSD) values for SLN: treatment 0.003***, genotype 0.003***, phenophase NS; NHI: treatment 0.004***,
genotype 0.004***, phenophase 0.005***. ***P ≤ 0.001, NS – not significant at P ≤ 0.05.
Mishra et al. (2016)Varanasi, India 28

29. Characterizing root trait variability in chickpea (Cicer arietinum L.) germplasm
Chickpea (Cicer arietinum L.) is an important legume
crop but its sustainable production is challenged by
predicted climate changes, which are likely to increase
production limitations and uncertainty in yields.
Characterizing the variability in root architectural traits
in a core collection of chickpea germplasm will provide
the basis for breeding new germplasm with suitable root
traits for the efficient acquisition of adaptation to
drought stress.
This study used a semi-hydroponic phenotyping system
for assessing root trait variability across 270 chickpea
genotypes.
Chen et al. (2016)Perth, Australia
29

30. Methodology
Plant material and root phenotyping system
A collection of chickpea (Cicer arietinum L.) genotypes from 29 countries consisting of 270 genotypes
(including two wild relatives of chickpea C. echinospermum) – primarily landraces with a few
advanced cultivars and breeding materials – was used in this study. Root phenotyping was carried
out using a novel semi-hydroponic phenotyping system( RBD)
Plant growth conditions
Fig 5: chickpea plants grown in the semi-hydroponic phenotyping platform
Root-related traits
It was calculated based on taproot length increments
for the growth period (35 d)
30

31. Table 9 . Description of measured traits in a chickpea core collection grown in a novel semi-hydroponic phenotyping system
31
33

32. Trait Minimum Maximum Mean Median Std. Deviation CV* P value*
TRL_z1 17.0 80.0 55.7 55.6 11.7 0.21 <0.001
TRL_z2 2.67 36.3 16.4 16.0 5.97 0.37 0.042
TRL 38.3 105 72.1 72.2 12.2 0.17 0.001
RL 305 3824 1175 1078 453 0.42 <0.001
BL 267 3765 1103 1004 447 0.44 <0.001
BN 23.1 764 188 159 105 0.66 <0.001
ABL 4.11 14.0 6.93 6.85 1.32 0.21 <0.001
RA 94.8 1027 319 294 123 0.42 <0.001
RV 2.36 22.03 6.95 6.38 2.75 0.43 <0.001
RD 0.68 1.07 0.87 0.87 0.06 0.07 <0.001
SRL 32.5 264 65.7 58.7 27.2 0.46 <0.001
BLR_tap 6.62 77.8 15.6 14.4 6.63 0.46 <0.001
BD 0.57 15.7 2.61 2.28 1.52 0.67 <0.001
BI 0.08 0.24 0.16 0.15 0.03 0.20 <0.001
RTD 1.27 9.87 3.05 3.05 0.82 0.27 <0.001
RL_top 140 923 440 426 122 0.29 <0.001
BL_top 120 903 420 406 122 0.30 <0.001
RD_top 0.77 1.09 0.92 0.92 0.06 0.06 <0.001
RL_s2 71.6 868 426 574 158 0.28 <0.001
RD_s2 0.64 1.00 0.82 0.82 0.06 0.08 <0.001
RL_s3 21.1 827 309 431 273 0.63 <0.001
RD_s3 0.62 1.05 0.86 0.86 0.08 0.09 <0.001
RL_sub 144 1575 735 647 378 0.58 <0.001
BL_sub 126 1497 683 597 372 0.62 <0.001
RD_sub 0.64 1.03 0.84 0.84 0.07 0.08 <0.001
RLR_top/sub 0.23 2.22 0.70 0.65 0.30 0.46 <0.001
BLR_top/sub 0.23 2.63 0.73 0.67 0.33 0.49 <0.001
RGR 1.10 3.00 2.06 2.06 0.35 0.17 0.001
RM 119 370 198 190 61.8 0.32 <0.001
SM 81.9 1006 329 297 142 0.48 <0.001
RMR 0.19 1.55 0.68 0.68 0.21 0.31 0.275
SH 8.23 30.0 16.8 17.0 4.26 0.25 <0.001
LBN 10.0 55.7 13.6 13.3 3.64 0.27 0.710
* Traits with coefficients of variation (CVs) ≥0.3 appear in bold type. Probability values (P) were based upon a GLM multivariate analysis of 270 genotypes and appear in bold if <0.01 and italic if <0.05
Table 10: Descriptive statistics of 33 measured traits (30 root traits, and three shoot traits) in 270 chickpea genotypes grown in a semi-
hydroponic phenotyping platform

33. Fig 6: Dendrogram showing clustering patterns of 17 selected root traits with
CVs ≥0.3 among 270 chickpea genotypes grown in a semihydroponic
phenotyping platform.
Conclusion:-
This study identified a wide variation in root system architectural traits across
270 genotypes of chickpea. These selected 17 root traits can be further used as a
promising tool for selecting superior drought tolerant genotype in chickpea.
33
15
2
•Root length ratio
•Branch length ratio
•Root mass ratio
•Branch density
•Total root volume
•Taproot length zone2
•Branch length over taproot
•Specific root length
•Topsoil root length
•Topsoil branch length
•Total branch number
•Root mass
•Root length section 3 (40 cm beyond)
•Total root area
•Subsoil branch length
•Total root length
•Total branch length

34. QTL-seq for rapid identification of candidate genes for 100-seed weight and root/total plant
dry weight ratio under rainfed conditions in chickpea
• Terminal drought is a major constraint to
chickpea productivity.
• Two component traits responsible for
reduction in yield under drought stress
include reduction in seeds size and root
length/root density.
• With an objective of identifying candidate
genomic regions responsible for 100SDW
and RTR, the QTL-seq approach was
adopted.
• Comprehensive analysis revealed four and
five putative candidate genes associated
with 100SDW and RTR, respectively and
validated using CAPS/dCAPS markers.
Singh et al. (2016)ICRISAT, Hyderabad 34

35. Experimental procedures
ICC 4958
×
ICC 1882
High 100 SDW
High RTR
Low 100 SDW
Low RTR
RIL population- ICCRIL03, 262 lines
Construction of pool
-Bulk were prepared for 100SDW and RTR based on the precise phenotyping data
obtained for five years(2005-09) and 2 years (2005 & 2007)
100 SDW
15 RILS with
high mean
phenotypic
value
15 RILS with
low mean
phenotypic
value
RTR
15 RILS with
high mean
phenotypic
value
15 RILS with
low mean
phenotypic
value
35Cont…

36.  Construction of libraries and Illumina sequencing
A total of five Illumina libraries
4- from the bulks
1- ICC4968 drought tolerant parent
 Construction of reference-based assembly (using inbuilt BWA aligner)
 Calculation of SNP-index
• QTL seq pipeline, developed by Iwate Biotechnology Research Center, Japan was used for calculating SNP-index.
Table 12: Identification of SNPs in putative candidate genes for total dry root weight to total plant dry weight ratio (RTR)
Table 11: Identification of SNPs in putative candidate genes for 100-seed weight (100SDW)
36

37. Validation of identified candidate SNPs
Fig 8:Validation of candidate gene-based markers for
RTR. Two gene-based markers Ca_04586_13666705
(dCAPS) and Ca_04586_13666728 (dCAPS)
associated with RTR
Fig 7:Validation of candidate gene-based markers for
100SDW. Two gene-based markers
Ca_04364_11311944 (CAPS) and
Ca_04607_13822453 (dCAPS) associated with
100SDW
Conclusion: This study revealed four and five putative candidate genes associated
with 100SDW (seed weight) and RTR (root trait ratio). Thus, the identified genomic
regions and genes may be useful for molecular breeding for chickpea improvement.
37

38. Temperature stress
Temperature stress
High Temperature
(Heat stress)
Low Temperature
(Cold stress)
Low Temperature
High Temperature
38

39. 1) Cold stress
 Cold-related stress can be defined in terms of either chilling (between 0°C and
12°C) or freezing or below 0°C without snow cover.
Stress by cold temperature
Low temperature stress
T> 0 ◦C: Chilling
T< 0 ◦C: Frost
Stress by freeze dehydration
•Membrane viscosity
•Retarded metabolism
•Delayed energy dessipation,
leading to radical formation
and oxidative stress
•Protoplast volume shrinkage upon
extracellular ice formation
•Negative turgor
•Concentration of cellular solutes
•Change of membrane potentials
Mechanism of cold stress
39

40. Damage to membrane and cell due to ice formation
Freezing
Cell A
Cell BCell B
Cell A
Intracellular water Intercellular water
Ice crystals
Cell rupture
Loss in membrane integrity
40

41.  Heat stress
• Two types of heat stress
according to the interaction
of time and temperature:
(i) Heat shock (lethal
temperatures from a few
minutes to a few hours)
(ii)Moderate heat (higher than
optimum temperatures
during the growing season).
Mechanism of plant tolerance to heat
stress
4141

42. Table 13: Comparison of growth and yield traits in chickpea genotype ICCV 9029 under
warm (glasshouse; control) and cold (field) conditions
Parameters Control Cold stressed
Plant height at 60 DAS (cm) 51.9 ± 1.8 33.4 ± 1.5
Flowering time (days) 37.8 ± 1.5 59.7 ±1.6
Flowering duration (days) 63.6 ± 1.5 65.3 ± 1.8 NS
Podding time (days) 48.2 ± 1.8 93.6 ± 3.2
Podding duration (days) 62.4 ± 1.9 49.2 ± 2.3
Time to pod maturity (days) 92 ± 3.2 120 ± 2.7
Time to crop maturity (days) 113 ± 2.6 138 ± 2.8
Pod set (%) 44.4 ± 0.8 35.5 ± 1.3
Pod retention (%) 44 ± 2.4 58.9 ± 2.2
No. of pods per plant 4.4 ± 0.7 14.4 ± 1.3
Average pod weight (g) 1.0 ± 0.1 3.2 ± 0.3
No. of seeds per plant 4.0 ± 0.7 15.6 ± 1.2
One-seeded pods per plant 2.8 ± 0.6 10.0 ± 1.4
Two-seeded pods per plant 1.5 ± 0.17 2.8 ± 0.34
Seed yield per plant (g) 0.6 ± 0.11 2.7 ± 0.4
Average seed weight (g) 0.18 ± 0.02 0.18 ± 0.03 NS
Chandigarh, India Kumar et al. (2010)
42
Cont…

43. Fig 9: Morphological and reproductive damage due to cold – A: Growth pattern under warm
and cold conditions; B: Anthocyanin accumulation in stressed plants (arrow); C: Anthocyanin
accumulation in leaves (arrow); D: Burning of leaf tips (arrow); E: Floral dimorphism; F: Normal
flower setting pod (arrow); G and H: Floral abortion (arrows); I: Pod abortion (arrow); J: Normal
pod set.
43

44. Parameter Flowering Stage Podding Stage
SML 868 SML 668 SML 868 SML 668
NS LS NS LS NS LS NS LS
Leaf temp (◦
C)
32.2 ± 0.23 36.6 ± 0.18 34.6 ± 0.18 38.6 ± 0.21 33.4 ± 0.20 37.7 ± 0.17 32.4 ± 0.18 37.3 ± 0.20
Chlorophy
ll
fluorescen
ce (Fv/Fm
ratio)
0.76 ± 0.04 0.61 ± 0.03 0.78 ± 0.03 0.56 ± 0.04 0.77 ± 0.03 0.58 ± 0.02 0.75 ± 0.03 0.54 ± 0.03
Chlorophy
ll (mg g−1
dw)
16.3 ± 1.6 10.3 ± 1.3 17.4 ± 1.3 11.4 ± 1.4 17.8 ± 1.2 10.8 ± 1.5 17.1 ± 1.2 11.5 ± 1.4
Leaf
relative
water
content
(%)
85.4 ± 2.1 76.2 ± 1.6 83.4 ± 1.5 74.1 ± 1.4 84.5 ± 1.6 74.5 ± 1.4 85.3 ± 1.8 73.5 ± 1.6
Stomatal
conductan
ce (mmol
m−2 s−1 )
331.4 ± 6.1 111.2 ± 5.2 372.6 ± 6.4 93.4 ± 4.7 324.5 ± 6.8 99.3 ± 5.9 356.8 ± 6.2 90.4 ± 5.6
Table 14: Leaf traits in normal-sown (NS) and late-sown (LS) plants at flowering and podding stage in mungbean
genotypes in response to heat stress.
Kaur et al. (2015)Chandigarh, India Cont…
44

45. Parameter SML 868 SML 668
Normal-sown Late-sown Normal-sown Late-sown
Pollen viability
(%)
78.4 ± 3.5 45.6 ± 3.1 74.3 ± 3.8 51.3 ± 3.3
Pollen
germination
(%)
73.3 ± 4.2 51.2 ± 3.2 75.3 ± 3.8 48.4 ± 3.3
Pollen load (1-
5 scale)
4.6 ± 0.44 3.1 ± 0.21 4.2 ± 0.48 2.8 ± 0.31
Stigma
receptivity (1-5
scale)
4.4 ± 0.38 2.9 ± 0.31 4.7 ± 0.33 2.4 ± 0.34
LSD (P < 0.05): Pollen viability [Interaction (sowing × genotypes)]: 9.3, Pollen germination
[Interaction (sowing × genotypes)]: 2.6, Pollen load [Interaction (sowing × genotypes)]: 0.54, Stigma
receptivity [Interaction (sowing × genotypes)]: 1.1.
Table 15: Reproductive function in normal-sown (NS) and late-sown (LS) plants at flowering and
podding stage in mungbean genotypes in response to heat stress.
45Cont…

46. Fig 10: Some symptoms on heat stress on
mungbean genotype SML 668. A: necrotic spots,
B: leaf rolling, C: shrivelled pods, D: Scorching of
leaves and early maturity.
Fig 11: Effects of heat stress on pollen grains of SML 668. A:
Pollen grains from normal-sown plants, B: Pollen grains from
heat-stressed plants showing poor stain indicating loss of
viability. C: High germination% in pollen grains from normal-
sown plants D: poor pollen germination in heat-stressed
plants, E: SEM pictures of normal pollen from normal-sown
plants, F: SEM pictures of shriveled pollen from heat-stressed
plants.
46
Cont…

47. Fig 12: Pollen load and stigma receptivity in SML 668 genotype. A: High number of pollen
grains of stigma surface, high stigma receptivity, indicated by dark stain in normal-sown plants,
B: shriveled stigma, less pollen grains and poor stigma receptivity, indicated by weak stain in
heat-stressed plants. C: SEM pictures of close of stigma in normal-sown plants, D: Shriveled
stigma in heat-stressed plants. 47

48. Temperature (ºC)
Seasons Growth Stages Min. Max. Average
Cool season Vegetative Stage 14.4 33.2 24.4
Flowering Stage 10.2 30.4 21.2
Pod setting Stage 8.4 29.7 19.3
Total crop growth
period
8.4 33.2 21.9
Warm season Vegetative Stage 19.5 39.4 30.3
Flowering Stage 15.7 41.7 30.3
Pod setting Stage 18.0 39.6 28.8
Total crop growth
period
15.7 41.7 29.9
Table 16 : Temperatures at different phenophases of blackgram during cool and warm season
Anitha et al. (2016)Hyderabad, India Cont…
48
Identification of Attributes Contributing to High Temperature Tolerance in
Blackgram (Vigna mungo L. Hepper) Genotypes

49. Genotypes Plant height (cm) No. of branches Days to 50 % Flowering No. of clusters/pl No. of pods/pl
CS WS % Red CS WS % Red CS WS Difference CS WS % Red CS WS % Red
IC 281987 31.67 18.83 40.53 3.33 2.00 40.00 35.5 33.5 2.00 18.34 9.00 50.94 43.33 15.33 64.62
IC 282009 29.33 18.68 36.32 5.00 3.78 24.47 35.5 33.67 1.83 17.20 15.00 12.79 42.24 33.00 21.87
IC 343947 19.34 19.00 1.76 3.67 3.33 9.09 34.17 31.5 2.67 16.04 7.33 54.27 41.33 16.33 60.48
IC 343952 25.67 19.20 25.19 4.00 3.00 25.00 34.83 32.5 2.33 18.25 11.67 36.06 43.17 19.67 54.44
IC 398971 37.00 19.53 47.23 3.82 2.33 38.86 41.67 41.33 0.34 18.34 17.33 5.51 43.33 32.33 25.38
IC 436519 30.67 18.83 38.59 3.82 2.67 30.13 36 32.67 3.33 14.44 14.33 0.72 39.17 24.33 37.87
IC 436610 30.33 20.09 33.78 5.00 3.82 23.67 35.5 34.17 1.33 17.10 17.00 0.57 42.53 33.67 20.8
IC 436652 34.33 18.31 46.66 5.67 3.50 38.24 35.33 33.17 2.16 16.62 9.00 45.85 41.63 17.33 58.36
IC 436720 28.00 19.83 29.19 3.55 3.33 6.10 32.67 32.5 0.17 16.67 13.58 18.54 38.72 28.00 27.69
IC 436753 33.33 18.41 44.76 5.33 4.00 25.00 36.33 33.17 3.16 16.65 9.00 45.96 41.71 23.67 43.26
IC 519805 24.33 20.16 17.16 5.00 3.68 26.33 35.5 34.17 1.33 13.58 10.33 23.89 38.72 23.00 40.60
IC 587751 23.67 19.48 17.69 3.75 3.33 11.11 38.33 32.83 5.50 18.09 10.00 44.73 43.30 11.00 74.59
IC 587752 27.67 19.19 30.63 3.50 2.67 23.81 36.5 33.5 3.00 18.53 9.00 51.43 43.30 13.67 68.43
IC 587753 22.33 19.16 14.21 5.33 3.33 37.50 34.67 34 0.67 15.67 13.68 12.68 38.62 31.67 18.00
PU-19 36.67 19.51 46.80 3.67 3.50 4.55 36 33 3.00 25.00 16.36 34.55 41.35 40.00 3.26
LBG-20 27.00 20.05 25.73 5.00 4.00 20.00 37.5 34 3.50 20.06 11.67 41.85 45.06 26.00 42.29
T-9 20.67 18.12 12.31 3.33 2.67 20.00 33.5 30.17 3.33 13.19 12.33 6.47 39.64 22.00 44.50
Mean 28.35 19.20 29.9 4.28 3.23 23.8 35.85 33.52 2.3 17.28 12.15 28.63 41.60 24.18 41.56
Min 19.34 18.12 1.76 3.33 2.00 4.55 32.67 30.17 0.17 13.19 7.33 0.57 38.62 11.00 3.26
Max 37.00 20.16 47.23 5.67 4.00 40.00 41.67 41.33 5.50 25.00 17.33 54.27 45.06 40.00 74.59
CS: cool season; WS: warm season; % Red- % of reduction during warm season over cool season
Table 17: Yield and yield contributing characters in seventeen blackgram genotypes in cool and warm season and % of reduction
Anitha et al. (2016)Hyderabad, India 49

50. Salinity
Stress
“A soil is saline when the electrical conductivity (EC) of saturated soil extract is >
4ds/m and a soil is sodic when the sodium adsorption ratio (SAR) is >15ds/m.”
 These types of soils are particularly common in arid and semiarid regions of West
and Central Asia, and Australia.
50

51. Fig 14: Percent change in moisture, succulence, relative growth rate (RGR) and specific shoot length (SSL) of Cajanus cajan under
increasing salinity treatments. Different letters represent significant differences at p<0.05.
Tayyab et al. (2016)Karachi, Pakistan 52

52. Fig 15: Reproductive growth parameters including
number of flowers, pod, seeds and seed weight of
Cajanus cajan under increasing salinity treatments.
Different letters represent significant differences at
p<0.05.
Fig 16: Leaf pigments including chlorophyll a,
chlorophyll b, total chlorophyll and carotenoids of
Cajanus cajan under increasing salinity treatments.
Different letters represent significant differences at
p<0.05.
Karachi, Pakistan Tayyab et al. (2016)53

53. Overview of a project at IIPR Kanpur (2015)
Physiological studies at IIPR Kanpur to understand mechanisms and
genetics of heat tolerance in chickpea
Heat tolerant lines: ICCV 92944, ICC 15614, ICC 1205, ICC 8950 and
ICC 1356;
Heat sensitive lines: ICC 4567, ICC 5912 and ICC 10685.
Studied the following physiological traits:
1. Membrane stability index
2. Pollen germination in respect to high temperature
3. Potential damage of photosynthesis due to high temperature
4. Sucrose synthase in developing grains
5. Photoperiodic response of genotypes
Validation of pollen tolerance to high temperature
54

54. 1. Membrane stability index
2. Pollen germination in respect to high temperature
Heat tolerant Lines
Heat sensitive line
T 39 ◦C
Fig 17: Pollen germination 55

55. Fig 18: Effect of high temperature on pollen tube growth in heat tolerant and
sensitive lines
56

56. Fig 19: Fluorescence images of heat sensitive (L) and heat tolerant line (R)
3. Potential damage of photosynthesis due to high temperature
57

57. 4. Sucrose synthase in developing grains of heat tolerant and sensitive lines grown at
high temperature late sown condition. (HT = Heat tolerant; HS= Heat sensitive)
Fig 20: Sucrose synthase activity (left) and pod weight equivalent to 100 seed
weight at different developmental stages
Genotype Hundred Seed weight (g) Sucrose Synthase activity
(μg /g /h)
ICCV 92944 (HT) 27.0 10.60
ICC 1205 (HT) 19.0 7.51
ICC 15614 (HT) 16.0 6.13
ICC 5912 (HS) 14.0 5.90
ICC 4567 (HS) 23.0 7.00
ICC 10685 (HS) 13.0 3.35
58

58. Fig 21: Photo-thermo-insensitivity of heat tolerant genotype ICCV 92944
5. Photoperiodic response of genotypes
59

59. Validation of pollen tolerance to high
temperature
• Extreme heat sensitive genotype of chickpea ICC 10685 and
heat tolerant genotype ICCV 92944. Reciprocal crosses were
made.
• ICCV 92944 x ICC 10685
• ICC 10685 x ICCV 92944
• The un-opened flowers of both the genotypes were treated at
35◦C for 2 hours in BOD incubator on moist filter paper in a
petri dish. The treated pollens were applied on the stigma tips
of emasculated flowers of ICCV 92944 and ICC 10685.
• Out of fifty crosses, maximum seeds were obtained from the
cross made between ICC 10685 X ICCV 92944 (70%), while
less than 1% seed sets were observed in the cross ICCV 92944
x ICC 10685 60

60. Fig 22: The past success in management of abiotic stress is encouraging.
Instability in yield decreased from 13.6% to 5.5% due to the adoption of
abiotic stress resistant varieties
Source: Pulses Production Scenario - Policy Brief 26 May 2013
61

61. Conclusion
• The abiotic stresses in pulses are governed by the important
physiological, biochemical and yield contributing factors such
as, photosynthetic rate, relative water content, membrane
injury index, plant height, flower drop, root : shoot ratio,
specific leaf area, chlorophyll content, drought susceptible
index, drought tolerant efficiency, total grain yield, harvest
index, proline and protein.
• Studying these characters in pulses, help in developing
resistance mechanism against these abiotic stresses.
• Molecular and functional genomics approaches like QTL-seq
helps in managing the various abiotic stress like drought stress.
62

62. Future Thrust
 For improving breeding efficiency, there is a need to identify specific
physiological, biochemical and molecular characteristics that may improve
yields under abiotic stresses.
 In pulses, proper characterization of abiotic stresses into its different
components at physiological, genetic and molecular levels is not well
understood, and only limited information is available in pulses.
 However, some efforts have been initiated and there is a need to emphasis
on some important generic traits including earliness, leaf morphology
(wax/pubescence, posture/rolling), seed hardiness, pollen viability and
germination, receptivity of stigma, pigments (chl a:b, carotenoids),
antioxidant, cool canopy, harvest index and stay green trait which are
considered to be associated with different mechanisms operating for abiotic
stress tolerance.
63

63. 63