




































 Agricultural Science; Vol. 1, No. 1; 2019 
ISSN 2690-5396   E-ISSN 2690-4799 

https://doi.org/10.30560/as.v1n1p18 

 18 Published by IDEAS SPREAD 
 

Evaluation of Drought Tolerance Indices and Nitrogen Fertilization 
for Some Groundnut (Arachis Hypogaea L.) Genotypes 

Iancu Paula1, Păniță Ovidiu1 & Soare Marin1 

1 Faculty of Agronomy, University of Craiova, Romania 
Correspondence: Ovidiu Păniță, Faculty of Agronomy, University of Craiova, Libertății Street, No. 19, Romania. 
E-mail: ovixfp@yahoo.com 
 
Received: November 7, 2019   Accepted: December 2, 2019   Online Published: December 23, 2019 
 
Abstract 
Water is essential to maximize crop yield and quality. This natural resource has assumed huge importance, 
especially in the warmest areas, where drought and environmental degradation has affected agricultural production. 
In order to identify drought tolerance of some groundnut genotypes and to investigate the relationships between 
seed yield, quality and drought tolerance indices a study was made using 10 promising genotypes. The experiment 
was carried out during 2014-2017 and sowed under randomized block design with four replicates. It included three 
factors: two levels of irrigation (a1 – non - irrigated and a2 - irrigated), two levels of fertilization (b1 – non-fertilized 
and b2 - 100 active Nitrogen/ha) and genotype (C1-C10). Seed yield depending on the influence of the factor, varied 
from 535.95 Kg/ha (non-irrigated) to 2020.95 Kg/ha (irrigated); from 1055.30 Kg/ha (non-fertilized) to 1501 
Kg/ha (fertilized) and from 1111.30 Kg/ha to 1388 Kg/ha depending on genotype. Same influence factors for 
protein content varied from 25.65% (irrigated) to 28.61% (non-irrigated); from 26.33% (non-fertilized) to 27.93% 
(fertilized) and from 25.59% to 28.52% depending on genotype. Stress susceptibility index (SSI) varied from 0.964 
to 1.040; Stress Tolerance Index (STI) from 0.138 to 0.435; Mean Productivity (MP) from 883.5 to 1616.0; 
Geometric Mean Productivity (GMP) from 750.3 to 1332.7; Tolerance index (TOL) from 933.0 to 1844.0; 
Harmonic Mean (HM) from 637.2 to 1099.0; Yield Index (YI) 0.777 to 1.308 and Yield Stability Index (YSI) from 
0.236 to 0.309. High values of SSI, STI, YI, DI, RDI and SSPI indicate drought tolerance and those variants present 
high stability.  
Keywords: fertilization, irrigation, PCA analysis, sandy soils 
1. Introduction 
Groundnut is a self-pollinating species and an annual herbaceous legume crop (Adinya et al., 2010). They have 
the potential to fix atmospheric nitrogen at the rate of 21 to 206 kg/ha annually in soils through root nodule 
bacterium. They belongs to the genus Rhizobium, thus improves soil fertility (Yakubu et al., 2010). The amount 
of N-fixed in nodulated legumes is highly variable due to environmental conditions such as: solar irradiance 
(Izaguirre-Mayoral & Sinclair, 2009, pp. 807-818), drought (Sinclair & Vadez, 2012, pp. 501-512), soil 
temperature Divito & Sadras, 2014, pp. 161–171) or other deficiencies. 
Nitrogen is an important element for efficient production of groundnut. Adequate supply of nitrogen fertilizer is 
essential for obtaining better plants growth and yield. An application of 10kgN/ha at the time of sowing is 
recommended for soils with moderate to low nitrogen (Fagbemigun & Oguntola, 2019, pp. 86-94). Lack of 
nitrogen is observed when leaves turn into yellow and eventually, the plant’s growth stops. In other cases, too 
much nitrogen is provided for the plant, it normally leads to watering of protoplasm and brittleness of the plant 
itself which would result in becoming vulnerable to diseases and pests (Awadalla & Abbas, 2017, pp. 40-46).  
Fertilizers and variety represents adequate agricultural practices to increase yield and quality to groundnut crop 
(Iancu Paula et al., 2014). The selection of high yielding genotypes is important for any crop productivity per unit 
area (Seadh, S.E. et al., 2017). 
Although groundnuts are known to be more tolerant to drought stress than most other related plant species (Wan 
et al., 2014), drought seems to become one of the important abiotic stresses for crop productivity. High 
temperatures from the summer months can destroy many of the heat-sensitive species. Groundnuts are plants that 
grow on large areas in warm regions but may be affected by drought in certain phases of growth such as flowering 
and pods formation. 



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Groundnut consumption is in continuous increase in Romania so adapting or creating new resistant/tolerance 
varieties is an important theme for researchers. Also, high yielding and of quality genotypes are preferred in the 
context of climate change. So, given the economic potential of groundnut, optimal fertilizer use, appropriate crop 
and soil fertility management practices could enhance productivity, food security and income of smallholder 
farmers from South region. Groundnut research experiences are set up in highly variable, low to medium rainfall 
and poor soil. Generally, the historical average annual rainfall is below 500 mm (occasionally 700 mm). In 
agricultural policy terms, this region is considered to be less favored area (Soare et al., 2016).  
The aim of this study is to investigate growth and yield response of groundnut genotypes as influenced by nitrogen 
fertilizer and irrigation.  
2. Method 
To evaluate yield and its quality, ten groundnut genotypes subjected to the influence of two irrigation levels and 
two different doses of Nitrogen, in a field experiment was conducted at Tamburesti Research Station, of University 
of Craiova, Romania, during 2014-2017, located at latitude of 44°1'40'' N, longitude 23°56'9'' E. The sandy soil 
contains 6-8% physical clay. The depth of the phreatic water is approximately at 7m from the surface of dunes. 
The difference of the levels between dunes and interdunes varies between 2- m. The quantity of humus is low (0.3-
0.5% at the sand of dune and 0.6-1.2 at the sand of interdune). The reaction of these sands varies from weak acid 
till neutral (D.H. = 6.3-7.1), while the total capacity of cation exchange is reduced (3-5m is at 100/g soil in the 
dune and 5-7m is at 100/g soil at interdune). The sands are very poor in nitrogen and phosphor and mediocre 
supplied with potassium (0.03-0.05% total nitrogen; 2-5 mg/100 g soil phosphor assimilable and approximately 
12 mg/100g soil assimilable potassium) (sand analysis made in Chemistry Laboratory of Faculty of Agronomy). 
The experiment was carried out during 2014-2017 and sowed in randomized block design with three replicates. It 
included three factors: two levels of irrigation (a1 – non - irrigated and a2 - irrigated), two levels of fertilization (b1 
– non-fertilized and b2 - 100 active Nitrogen/ha) and genotype (C1-C10). Data were statistically analyzed and means 
were compared by least significant differences (LSD), P=0.05. 
Drought tolerance indices were calculated using the formulas: 
Stress susceptibility index (SSI) = (1- Ys/Yp) / (1- (Ys/Yp) 
Tolerance (TOL) = Yp -Ys 

Mean productivity (MP) = (Yp-Ys) / 2 
Geometric mean productivity (GMP) = Yp − Ys 
Stress tolerance index (STI) = (Ys x Yp) / Yp

2 
Yield index (YI) = Ys / Ys 

Yield stability index (YSI) = Ys / Yp 
Harmonic mean (HM) = (2xYsxYp) / (Yp+Ys) 
Sensitivity drought index (SDI) = (Yp-Ys) / Yp 

Drought resistance index (DI) = Ys
2 / (𝑌s x Yp) 

Relative drought index (RDI) = (Ys/Yp) / (Ys/Yp) 
Stress susceptibility percentage index (SSPI) = (Yp-Ys) x 100 / (2 x Yp) 
In order to analyze the yield potential under irrigation or drought conditions, the Yp values were considered the 
values of the AxBxC interaction from A2 level (irrigation), being of a2bici type. The Ys values were considered the 
values of the AxBxC interaction from A1 level (drought), being of a1bici type. Correlation analysis yield, protein 
content and drought tolerance indices was performed to determine the best drought-tolerant genotypes and indices. 
Principal component analysis (PCA) was performed based on the analyzed indices. Both correlation and PCA were 
performed by IBM SPSS Version 2011 and MS Office Excel 2016.  
3. Results and Discussions 
Agriculture uses 11% of the world’s land surface for crop production. It also uses 70% of all water withdrawn 
from aquifers, streams and lakes (FAO, 2011). For increasing agricultural yield it must use rationally doses of 
fertilizer as well as research for the possibility of water supplying. 
Tamburesti Research Station is often subjected to unpredictable periods of water deficit and high temperatures in 
various stages of plants development. Mostly, the climate of the region is arid, characterized by cold winters and 



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hot/dry summers. Three of the four experimentation years (2014-2017) were considered with drought, average 
temperatures being of 26°C and 400mm rain water, with 4 degrees above, respective 300mm under the average of 
the last 30 years. 
Factor A: Analysis of yield under the influence of this factor, indicate that the mean of the irrigated variants 
recorded significant differences compared to the average of non-irrigated variants. In case of protein content, the 
average of variants in non-irrigated registered significant differences compared to the average of irrigation variants 
(table 1). It can see that drought can lead to a substantial decline in yield and this reduction depends on the genotype. 
Water stress causes a significant reduction in groundnut lines pod yield/ha and other characteristics (Nassar et al., 
2018), so that water availability is a critical factor for a successful groundnut production. 
Factor B: Analysis of yield from the average of the fertilized variants showed significant differences compared to 
the mean of non-fertilized variants. In the case of protein content, also the average of fertilized variants recorded 
significant differences compared to the mean of the non-fertilized variants. 
 
Table 1. Factor A analysis influence on yield and protein content 

            
Factor 

Factor Level  

A B 

Yield (kg/ha) Protein (%) Yield (kg/ha) Protein (%) 

First level 535.95+85.641b 28.61+4.82a 1055.30+599.83b 26.33+2.05b 
Second level 2020.95+405.976a 25.65+1.08b 1501.60+912.34a 27.93+1.70a 
Mean 1278.45+245.809 27.13+2.95 1278.45+756.09 27.13+1.87 
LSD 5 % 35.70 2.61 76.440 0.673 

*Mean followed by similar letters in each column, are not significantly different at the 5% level of probability. 
 
Applying nitrogen fertilizer dose of N90 twice, before sowing and in vegetation, leads to the obtaining of a very 
significant increase of production 1321 kg/ha (Dima et al., 2013). Same authors reported a protein content ranging 
from 21.3% in the control variant unfertilized and 23.9% in the variant fertilized with N60P60K60 and nitrogen 
was given 1/3 at sowing + 2/3 in vegetation. The effects of N fertilization in oil seeds increase protein content but 
also have an adverse effect on oil content (Maheswari et al., 2017). 
Romania is being placed in the north limit of cultivation areal of groundnut, where the interaction genotype x 
environment is very high, making difficult the identification of some cultivars easily adaptable to the sudden 
change of temperature which appears along vegetation period and to different levels of ensuring the heat factor 
from one year to another (Soare and Iancu, 2011). 
As concern the method of irrigation, it seems that the application of micro-irrigation in groundnut has shown that 
the technique results in high water use efficiency, saves water, reduces fertilization requirement, provides better 
quality crop and higher pods yield (Jeetendra, K.S. et all., 2016).  
Factor C: Analysis on yield of this factor leaded to a best result by genotype C10 which, along with the second 
genotype C9, recorded significant differences compared to the last 7 classified genotypes. In the analysis of factor 
C influence on protein content, the first classified genotype, C1, shows significant differences compared to all 
other analyzed genotypes (table 2). 
 
 
 
 
 
 
 
 
 



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Table 2. Factor C analysis on yield and protein content 

          Index
C level 

Yield (kg/ha) Protein (%) 

C1 1111.75+742.76 f 28.52+2.33 a 
C2 1215.50+809.22 e 27.75+2.09 b 
C3 1232.25+813.72 de 27.50+2.18 bc

C4 1246.25+826.87 cde 27.34+1.90 bcd

C5 1275.75+831.99 cd 27.24+1.88 cd

C6 1281.25+834.08 cd 27.05+2.04 de

C7 1304.25+844.81 bc 26.92+1.97 def

C8 1351.25+857.26 ab 26.78+2.10 e 
C9 1378.25+861.46 a 26.55+1.95 f 
C10 1388.00+872.16 a 25.59+0.99 f 
Mean 1278.45+829.43  27.12+1.94 
LSD 5 % 58.357  0.443  

*Mean followed by similar letters in each column, are not significantly different at the 5% level of probability 
 
Referring to the analysis of the influence of factors AxB on yield, the differences between the variants are 
significant, the best result being obtained by a2b2 variant, fertilized and irrigated. The last classified variant is 
a1b1, non-fertilized and non-irrigated variant. In the case of protein content, the differences between variants are 
significant, the best result being realized by a1b2 variant, non-irrigated and fertilized. The last classified variant is 
a2b1, non-fertilized and irrigated (table 3). Ghanbari et al., 2011, reported that yield, plant growth and nutrient 
uptake reduces under conditions of drought. Junjittakarn et al., 2013 sustain that water regimes can significantly 
affects nutrient uptakes of peanut, but selection of genotypes for high nutrient uptakes could be done under in any 
water regimes because the interactions between genotype and water regimes were not significant, showing the 
consistency of the nutrient uptakes across water regimes. 
 
Table 3. Factors A and B interaction analysis influence on yield and protein content 

            Indices 
Factors level 

Yield (kg/ha) Protein (%) 

            A level 
B level 

a1 a2 a1 a2 

b1 470.40+38.63d 1640.20+151.27b 27.96+1.64b 24.69+0.57d 
b2 601.50+74.49c 2401.70+141.62a 29.25+1.45a 26.61+0.39c 
Mean 1278.45+101.50 27.13+1.01 
LSD 5 % 108.102  0.952  

*Mean followed by similar letters in each column, are not significantly different at the 5% level of probability 
 
In the case of the analysis of the AxC interaction factor influence on the yield, between the first three variants 
(a2C10, a2C9 and a2C8), genotypes with high potential under irrigation, there were not found significant differences, 
first two differentiating significant from the last 17 ranked variants. The last variant (a1c1), C10 genotype under 
irrigation, recorded significant negative differences compare with the first 12 ranked variants. In the case of protein 
content, the first ranked variant (a1c1), C1 genotype under irrigation, recorded significant differences compare with 
all others variants. The last two ranked variants (a2c9 and a2c10) recorded significant differences compare with the 
first 14 ranked variants (table 4). 
 



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Table 4. Factors A and C interaction analysis influence on yield and protein content 

         Indices
Factors level 

Yield (kg) Protein (%) 

         A level
C level 

a1 a2 a1 a2 

c1 466.00+91.09j 1757.50+452.39f 30.61+0.97a 26.45+0.84fghi 
c2 493.50+85.07ij 1937.50+426.98e 29.43+1.32b 26.09+1.11fghi 
c3 507.00+68.67hij 1957.50+435.46de 29.13+1.77bc 25.89+1.02fghi 
c4 508.00+58.23hij 1984.50+439.02cde 28.88+1.20cd 25.82+0.97ghij 
c5 527.00+59.20ghij 2024.50+416.96cde 28.75+1.21cd 25.74+0.96hijk 
c6 530.00+60.91ghij 2032.50+415.08cd 28.56+1.62cde 25.54+1.07ijk 
c7 552.00+80.28ghi 2056.50+453.41bc 28.38+1.50de 25.47+1.13ijk 
c8 577.50+93.79gh 2125.00+413.66ab 28.31+1.59de 25.26+1.27jk 
c9 600.00+105.64g 2156.50+409.71a 27.96+1.43e 25.15+1.28k 
c10 598.50+114.14g 2177.50+405.56a 26.08+0.57fghi 25.12+1.14k 
Mean 1278.450+254.26 27.13+1.20 
LSD 5 % 82.529  0.627  

*Mean followed by similar letters in each column, are not significantly different at the 5% level of probability 
 
In the case of the analysis of the BxC interaction factors influence on the yield, between the first four ranked 
variants (b2c10, b2c9, b2c8 and b2c7) there were no statistical differences, the first two differentiating significant from 
the last 16 ranked variants. The last ranked variants (b1c1) recorded significant negative differences compare with 
all others genotypes (table 5). Concerning the protein content, the first ranked variant (b2c1) recorded significant 
differences compare with all others differences, except with the next two ranked variants (b2c3 and b2c3). The last 
ranked variants (b1c10) recorded significant negative differences compare with the first 18 ranked variants. 
 
Table 5. Factors B and C interaction analysis influence on yield and protein content 

            Indices 
Factors level 

Yield (kg/ha) Protein (%) 

            B level 
C level 

b1 b2 b1 b2 

c1 883.50+513.685i 1340.00+728.60d 28.170+2.815 bcde 28.880+1.951 a

c2 991.50+513.68h 1439.50+908.20c 26.750+1.919 gh 28.765+1.875 ab

c3 1017.50+616.25h 1447.00+969.77c 26.520+1.769 hi 28.490+2.235abc

c4 1028.50+618.72h 1464.00+981.43bc 26.475+1.800 hi 28.220+1.715bcde

c5 1061.50+635.69gh 1490.00+993.11bc 26.425+1.880 hijk 28.060+1.632cde

c6 1068.50+640.01fgh 1494.00+1001.54bc 26.200+2.237 hijk 27.900+1.577cdef

c7 1069.00+643.32fgh 1539.50+1004.00ab 26.085+2.190 ijk 27.760+1.450def

c8 1125.50+643.81efg 1577.00+1011.35ab 25.840+2.261 jk 27.725+1.584ef

c9 1147.50+687.56ef 1609.00+1010.80a 25.695+2.224 kl 27.405+1.312fg

c10 1160.00+708.47e 1616.00+1001.45a 25.115+1.129l 26.075+0.590ijk

Mean 1278.450+1008.88 27.128+1.81
LSD 5 % 82.529 0.627 

*Mean followed by similar letters in each column, are not significantly different at the 5% level of probability 



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Table 6 indicate the influence of the 3 factors on yield and the first ranking variants are the most productive 
genotypes, C7, C8, C9 and C10, under irrigation and with fertilization, those ones differentiating significantly from 
all other variants, except the next three ranked under them. The last ranking variants are all without fertilization 
and irrigation in order of their yield potential.  
 
Table 6. Analysis of influence of the factors A, B and C interaction on yield and protein content 

             Indices 
Factors level 

Yield (kg/ha) Protein (%) 

              A level
BXC level 

a1 a2 a1 a2 

b1c1 417.00+29.4418 1350.00+77.1112 30.64+1.201 25.70+0.2715-16

b1c2 432.00+55.4318 1551.00+84.8711 28.40+1.005-7 25.10+0.1716-17

b1c3 455.00+60.6217-18 1580.00+64.3710 28.05+0.836-8 24.99+0.3316-18

b1c4 457.00+20.7817-18 1600.00+173.2110 28.00+1.066-9 24.95+0.0916-18

b1c5 478.00+31.1816-18 1645.00+40.739-10 27.95+1.326-9 24.90+0.3616-18

b1c6 482.00+38.4616-18 1655.00+51.969-10 27.82+2.156-9 24.58+0.1417-19

b1c7 483.00+22.5216-18 1655.00+74.329-10 27.68+2.046-9 24.49+0.4317-19

b1c8 500.00+17.3216-18 1751.00+88.338-9 27.57+1.947-10 24.11+0.1918-19

b1c9 505.00+12.1216-18 1790.00+127.588 27.39+1.918-11 24.00+0.3419 
b1c10 508.00+59.7716-18 1825.00+21.707-8 27.35+0.198-11 24.10+0.3118-19

b2c1 515.00+112.5816-18 2165.00+112.586 30.57+0.951 27.19+0.208-12

b2c2 555.00+60.6215-17 2324.00+60.625 30.45+0.431 27.08+0.299-13

b2c3 559.00+45.7315-17 2335.00+108.735 30.20+1.911-2 26.78+0.2910-14

b2c4 559.00+15.5915-17 2369.00+105.594-5 29.76+0.401-3 26.68+0.2910-14

b2c5 576.00+24.2515-16 2404.00+240.253-5 29.54+0.072-3 26.58+0.2911-15

b2c6 578.00+48.5015-16 2410.00+408.502-5 29.30+0.523-4 26.50+0.2611-15

b2c7 621.00+36.3714-15 2458.00+360.371-4 29.07+0.023-5 26.45+0.3212-15

b2c8 655.00+60.6214-15 2499.00+60.621-3 29.05+0.973-5 26.40+0.2612-15

b2c9 695.00+25.9814 2523.00+25.981-2 28.52+0.714-6 26.29+0.2713-15

b2c10 702.00+20.7813 2530.00+20.781 26.02+0.9014-15 26.13+0.2314-15

Mean 1278.78+46.92 27.16+0.65 
LSD 5 % 116.714 0.900 

*Mean followed by similar numbers in each column, are not significantly different at the 5% level of probability 
 
Regarding the influence of the three factors on the protein content, the first ranking variants are the ones of the C1 
genotype with fertilization and no fertilization, respectively C2, C3 and C4 genotypes variants with fertilization. 
The last two variants are the ones of the C9 and C10 genotypes with no fertilization and under irrigation. 
Drought indices are considered a measure to provide information about drought based on loss of yield in drought 
conditions in comparison to normal conditions and are used for screening drought tolerant genotypes. In order to 
analyze the yield potential both under irrigation or drought conditions, the Yp values were considered the values 
of the AxBxC interaction from A2 level (irrigation), being of a2bici type. The Ys values were considered the values 
of the AxBxC interaction from A1 level (drought), being of a1bici type. The values are shown in table 7. 
Thus, the MP, GMP and HM show the yield potential under irrigation or drought conditions. In the comparative 
analysis, based on the absolute value of those indices it can be seen the variants with the highest yield potential 
both under irrigation and in drought conditions, high values emphasizing the variants with highest potential. TOL, 



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YSI and SDI show the drought tolerance, in the comparative analysis based on the values of those indices, being 
able to identify the variants with the highest yield stability, lowest values indicated them. SSI, STI, YI, DI, RDI 
and SSPI show the drought tolerance of each variant reported on the average of the all variants, high values 
showing variants with high stability. 
 
Table 7. Analysis of drought indexes values 

     Index 
 
Variants Y

s (
a 1

b i
c i)

 

Y
p (

a 2
b i

c i)
 

P s
 (a

1b
ic i

) 

P p
  

(a
2b

ic i
) 

SS
I 

TO
L 

M
P 

G
M

P 

ST
I 

Y
I 

Y
SI

 

H
M

 

SD
I 

D
I 

RD
I 

SS
PI

 

aib1c1 417.0 1350.0 30.6 25.7 0.941 933.0 883.5 750.3 0.138 0.777 0.309 637.2 0.691 0.240 1.163 23.1 

aib1c2 432.0 1551.0 28.4 25.1 0.982 1119.0 991.5 818.6 0.164 0.805 0.279 675.8 0.721 0.224 1.049 27.7 

aib1c3 455.0 1580.0 28.1 25.0 0.969 1125.0 1017.5 847.9 0.176 0.848 0.288 706.5 0.712 0.244 1.085 27.8 

aib1c4 457.0 1600.0 28.0 25.0 0.973 1143.0 1028.5 855.1 0.179 0.852 0.286 710.9 0.714 0.243 1.076 28.3 

aib1c5 478.0 1645.0 28.0 24.9 0.966 1167.0 1061.5 886.7 0.193 0.891 0.291 740.8 0.709 0.259 1.094 28.9 

aib1c6 482.0 1655.0 27.8 24.6 0.965 1173.0 1068.5 893.1 0.195 0.898 0.291 746.6 0.709 0.262 1.097 29.0 

aib1c7 483.0 1655.0 27.7 24.5 0.964 1172.0 1069.0 894.1 0.196 0.900 0.292 747.8 0.708 0.263 1.099 29.0 

aib1c8 500.0 1751.0 27.6 24.1 0.973 1251.0 1125.5 935.7 0.214 0.932 0.286 777.9 0.714 0.266 1.075 31.0 

aib1c9 505.0 1790.0 27.4 24.0 0.977 1285.0 1147.5 950.8 0.221 0.941 0.282 787.8 0.718 0.266 1.063 31.8 

aib1c10 508.0 1825.0 27.4 24.1 0.983 1317.0 1166.5 962.9 0.227 0.947 0.278 794.8 0.722 0.264 1.048 32.6 

aib2c1 515.0 2165.0 30.6 27.2 1.038 1650.0 1340.0 1055.9 0.273 0.960 0.238 832.1 0.762 0.228 0.896 40.8 

aib2c2 555.0 2324.0 30.5 27.1 1.036 1769.0 1439.5 1135.7 0.316 1.034 0.239 896.0 0.761 0.247 0.899 43.8 

aib2c3 559.0 2335.0 30.2 26.8 1.036 1776.0 1447.0 1142.5 0.320 1.042 0.239 902.0 0.761 0.249 0.902 43.9 

aib2c4 559.0 2369.0 29.8 26.7 1.040 1810.0 1464.0 1150.8 0.324 1.042 0.236 904.6 0.764 0.246 0.889 44.8 

aib2c5 576.0 2404.0 29.5 26.6 1.035 1828.0 1490.0 1176.7 0.339 1.073 0.240 929.3 0.760 0.257 0.902 45.2 

aib2c6 578.0 2410.0 29.3 26.5 1.035 1832.0 1494.0 1180.2 0.341 1.077 0.240 932.4 0.760 0.258 0.903 45.3 

aib2c7 621.0 2458.0 29.1 26.5 1.018 1837.0 1539.5 1235.5 0.374 1.157 0.253 991.5 0.747 0.292 0.952 45.4 

aib2c8 655.0 2499.0 29.1 26.4 1.005 1844.0 1577.0 1279.4 0.401 1.221 0.262 1037.9 0.738 0.320 0.987 45.6 

aib2c9 695.0 2523.0 28.5 26.3 0.986 1828.0 1609.0 1324.2 0.429 1.295 0.275 1089.8 0.725 0.357 1.037 45.2 

aib2c10 702.0 2530.0 26.0 26.1 0.984 1828.0 1616.0 1332.7 0.435 1.308 0.277 1099.0 0.723 0.363 1.045 45.2 

Mean 536.6 2021.0 28.7 25.7 0.995 1484.4 1278.8 1040.4 0.273 1.000 0.269 847.0 0.731 0.267 1.013 36.7 

Max 702.0 2530.0 30.6 27.2 1.040 1844.0 1616.0 1332.7 0.435 1.308 0.309 1099.0 0.764 0.363 1.163 45.6 

Min 417.0 1350.0 26.0 24.0 0.941 933.0 883.5 750.3 0.138 0.777 0.236 637.2 0.691 0.224 0.889 23.1 

Std. dev. 82.5 409.0 1.3 1.1 0.032 334.7 242.9 181.8 0.094 0.154 0.023 137.0 0.023 0.038 0.088 8.3 

 
Analyzing the correlation coefficients values for the drought tolerance indices, it can be seen that some of them 
show the same thing, because of the high correlation values between them. Those types of correlation with values 
almost equal with 1 or -1 were found between: YI and Ys; SSI and YSI; SSI and SDI; SSI and RDI; TOL and SSPI; 
YSI and SDI; YSI and RDI and between SDI and RDI. 
The yield recorded under irrigation conditions (Yp) is in very strong correlation with the next indices: Ys, SSI, 
TOL, MP, GMP, STI, Yi, HM, SDI and SSPI. The correlation between Yp and Ys suppose that the genotypes with 



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high potential under irrigation conditions obtain the highest yield values on drought. Ys is in high strong correlation 
with: TOL, MP, GMP, STI, HM, DI and SSPI. 
The indices that show high yield potential under irrigation conditions are in high positive correlation between them. 
There are strongly negative correlations between indices that show yield potential and indices that show yield 
stability on drought (table 8).  
 
Table 8. Analysis of correlations between drought indices 

 
Ys 

(a1bici) 

Yp 

(a2bici) 

Ps 

(a1bici)

Pp 

(a2bici) 
SSI TOL MP GMP STI YI YSI HM SDI DI RDI 

Yp (a2) 0.919               

Ps (a1) -0.058 0.238              

Pp (a2) 0.551 0.759 0.715             

SSI 0.467 0.776 0.575 0.790            

TOL 0.876 0.995 0.305 0.791 0.832           

MP 0.943 0.998 0.190 0.732 0.732 0.986          

GMP 0.974 0.984 0.110 0.681 0.654 0.962 0.994         

STI 0.982 0.974 0.097 0.679 0.614 0.948 0.987 0.998        

Yi 1.000 0.919 -0.058 0.551 0.467 0.876 0.943 0.974 0.982       

YSI -0.467 -0.776 -0.575 -0.790 -1.000 -0.832 -0.732 -0.654 -0.614 -0.467      

HM 0.995 0.954 0.015 0.612 0.553 0.920 0.972 0.992 0.995 0.995 -0.553     

SDI 0.467 0.776 0.575 0.790 1.000 0.832 0.732 0.654 0.614 0.467 -1.000 0.553    

DI 0.841 0.559 -0.439 0.125 -0.084 0.476 0.614 0.697 0.729 0.841 0.084 0.782 -0.084   

RDI -0.467 -0.776 -0.575 -0.790 -1.000 -0.832 -0.732 -0.654 -0.614 -0.467 1.000 -0.553 -1.000 0.084  

SSPI 0.876 0.995 0.305 0.791 0.832 1.000 0.986 0.962 0.948 0.876 -0.832 0.920 0.832 0.476 -0.832

*P 5 %=0.44 
 
Significant positive correlations among YS and (YP, STI, YI, MP, YSI, GMP and HM), YP and (TOL, YR, STI, 
YI, MP, GMP and HM) reported others authors (Abejide et al., 2017). Same authors concluded that drought 
tolerance indices such as STI, MP, GMP, YI and HM which showed significantly high positive correlations with 
yield in both stressed and non-stressed conditions are good indicators which can be used for the screening and 
selection of drought tolerant genotypes also in Bambara groundnut. Also, Ilker et al., 2011 concluded that MP, 
GMP and STI values are convenient parameters to select high yielding wheat genotypes both in stress and non-
stress conditions.  
PCA analysis: Concerning the PCA analysis, the first component reaches over 74% from total variance, while the 
second component reaches over 21% from total variance. Together they have more than 95% from total variance. 
The first component shows the yield potential both under irrigation and under drought conditions and low stability 
of the yield, the indices that quantify this potential being DI, YI, HM, GMP, STI, MP, SDI, SSI and SSPI. The 
second component shows the variants with high protein content both under irrigation or drought conditions, the 
indices that quantify this being YSI and RDI. 
The correlation coefficients values of the two components and the analyzed indices are shown in table 9. All 
indices have at least 1 positive value for the correlation with the two components. In the case of the first component, 
12 of the analyzed indices are in very high positive correlation, while only two indices, YSI and RDI, are in very 
high negative correlation with the second component. 
 



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Table 9. Variation of correlation coefficients values between the two components and the analyzed indices 

 
Ei

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In the case of the second component, 9 of the analyzed indices have positive values, from which only DI is in 
strongly positive correlation with these one. Concerning the indices that are in negative correlation with the second 
component, only the correlation between one and Ps has a high negative value.  
The variants ranking according to components score is shown in table 10 and figure 1. 
 
Table 10. The variants ranking according to components score based on PCA analysis 

The component sign 
Index

Variants 
Yield (kg/ha) Protein (%) 

C1 C2 
ai 

bici 

a1bici (Ys)

 

a2bici (Yp) 

 

Yp-Ys 

(%) 

a1bici (Ys)

(%) 

a2bici (Yp) 

(%) 

+ + 

aib2C7 621.0014-15 2458.001-4 74.74 29.073-5 26.4512-15 
aib2C8 655.0014-15 2499.001-3 73.79 29.053-5 26.4012-15 
aib2C9 695.0014 2523.001-2 72.45 28.524-6 26.2913-15 
aib2C10 702.0013 2530.001 72.25 26.0214-15 26.1314-15 

Mean 668.25 2502.5 73.31 28.17 26.32 

+ - 

aib2C1 515.0016-18 2165.006 76.21 30.571 27.198-12 
aib2C2 555.0015-17 2324.005 76.12 30.451 27.089-13 
aib2C3 559.0015-17 2335.005 76.06 30.201-2 26.7810-14 
aib2C4 559.0015-17 2369.004-5 76.40 29.761-3 26.6810-14 
aib2C5 576.0015-16 2404.003-5 76.04 29.542-3 26.5811-15 
aib2C6 578.0015-16 2410.002-5 76.02 29.303-4 26.5011-15 

Mean 557 2334.5 76.14 29.97 26.80 

- - 

aib1C1 417.0018 1350.0012 69.11 30.641 25.7015-16 
aib1C2 432.0018 1551.0011 72.15 28.40-7 25.1016-17 
aib1C3 455.0017-18 1580.0010 71.20 28.056-8 24.9916-18 
b1C4 457.0017-18 1600.0010 71.44 28.006-9 24.9516-18 

Mean 440.25 1520.25 70.97 28.77 25.19 

- + 

aib1C5 478.0016-18 1645.009-10 70.94 27.956-9 24.9016-18 
aib1C6 482.0016-18 1655.009-10 70.88 27.826-9 24.5817-19 
aib1C7 483.0016-18 1655.009-10 70.82 27.686-9 24.4917-19 
aib1C8 500.0016-18 1751.008-9 71.44 27.577-10 24.1118-19 
aib1C9 505.0016-18 1790.008 71.79 27.398-11 24.0019 
aib1C10 508.0016-18 1825.007-8 72.16 27.358-11 24.1018-19 

Mean 492.67 1720.17 71.34 27.63 24.36 
*Mean followed by similar numbers in each column, are not significantly different at the 5% level of probability 
 
Principal component analysis accounted 95.57% with the first PC of 74.38 % whereas the second PC of 21.19%. 
Regarding the variants ranking, the variants that have both components with high values are the variants where 
there were cropped C7 to C10 genotypes and there were applied the fertilization, those ones proving under irrigation 
and drought conditions the highest yield potential and the lowest drought tolerance and high protein content on 
drought and the lowest protein content under irrigation. 



as.ideasspread.org   Agricultural Science Vol. 1, No. 1; 2019 

 27 Published by IDEAS SPREAD 
 

The variants with first component with high value and second component with low value are the variants where 
there were cropped C1 to C6 genotypes and there were applied the fertilization, those ones proving under irrigation 
conditions high yield potential and on drought conditions low yield potential, low yield drought tolerance and the 
highest protein content on drought and low protein content under irrigation. 
The variants that have both components with low values are the variants where there were cropped C1 to C4 
genotypes and there were not applied fertilization, those ones proving under irrigation and drought conditions the 
lowest yield potential and the highest drought tolerance and the highest protein content. The variants with first 
component with low value and second component with high value are the variants where there were cropped C5 
to C10 genotypes and there were not applied fertilization, proving under drought conditions the low yield potential 
and high yield potential under irrigation and medium protein content both under irrigation and drought conditions 
and also good yield drought tolerance. 
In another experiment with winter wheat, principal component analysis was found of 96.063% from the variance 
which indicated limited variation in the response to reduced N fertilization and vice versa (Iancu Paula et al. 2019). 
Others authors also observed that the rank of genotypes for some studied traits under water stress changes from 
that under well watering conditions (Nassar et al. 2018).  
 

 
Figure 1. Biplot for drought or combine effect of all factors 

 
4. Conclusions 
For groundnut crops, water support is the most important factor, then fertilization and nitrogen factors. Some 
computed indices for the drought tolerance have very high values of the correlation coefficients, which proves that 
those ones are similar in determining the drought tolerance.  
The yield under irrigation (Yp) is in positive correlation with the next indices: Ys, SSI, TOL, MP, GMP, STI, Yi, 
HM, SDI and SSPI. 
The high correlation between Yp and Ys means that the genotypes with high yield potential under irrigation 
conditions have also high yield potential under drought conditions compare with the ones with low potential under 
irrigation. 
The indices that indicate high yield potential under irrigation conditions are in high correlation between them.  
On the PCA analysis, the first component shows the variants that have the highest yield potential both under 
irrigation or drought conditions and low tolerance under drought, those indices being: DI, YI, HM, GMP, STI, MP, 

aib1C1

aib1C2

aib1C3 aib1C4

aib1C5
aib1C6
aib1C7

aib1C8
aib1C9

aib1C10

aib2C1

aib2C2
aib2C3 aib2C4

aib2C5

aib2C6

aib2C7

aib…

aib2C9

aib2C10

YI

Yp

Ps

Pp
TOL

MP

GMP
STIYs

Y…

HM

SDI
SSI

DI

R…

SSPI

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

-1.8 -1.3 -0.8 -0.3 0.3 0.8 1.3

Co
m

po
ne

nt
 2

 (2
1.

19
 %

)

Component 1 (74.38 %)



as.ideasspread.org   Agricultural Science Vol. 1, No. 1; 2019 

 28 Published by IDEAS SPREAD 
 

SDI, SSI and SSPI. The second component shows the variants with high protein content both under irrigation or 
drought conditions, the indices that quantify this being YSI and RDI. 
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    /HRV (Za stvaranje Adobe PDF dokumenata najpogodnijih za visokokvalitetni ispis prije tiskanja koristite ove postavke.  Stvoreni PDF dokumenti mogu se otvoriti Acrobat i Adobe Reader 5.0 i kasnijim verzijama.)
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    /NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken die zijn geoptimaliseerd voor prepress-afdrukken van hoge kwaliteit. De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.)
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    /ENU (Use these settings to create Adobe PDF documents best suited for high-quality prepress printing.  Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.)
  >>
  /Namespace [
    (Adobe)
    (Common)
    (1.0)
  ]
  /OtherNamespaces [
    <<
      /AsReaderSpreads false
      /CropImagesToFrames true
      /ErrorControl /WarnAndContinue
      /FlattenerIgnoreSpreadOverrides false
      /IncludeGuidesGrids false
      /IncludeNonPrinting false
      /IncludeSlug false
      /Namespace [
        (Adobe)
        (InDesign)
        (4.0)
      ]
      /OmitPlacedBitmaps false
      /OmitPlacedEPS false
      /OmitPlacedPDF false
      /SimulateOverprint /Legacy
    >>
    <<
      /AddBleedMarks false
      /AddColorBars false
      /AddCropMarks false
      /AddPageInfo false
      /AddRegMarks false
      /ConvertColors /ConvertToCMYK
      /DestinationProfileName ()
      /DestinationProfileSelector /DocumentCMYK
      /Downsample16BitImages true
      /FlattenerPreset <<
        /PresetSelector /MediumResolution
      >>
      /FormElements false
      /GenerateStructure false
      /IncludeBookmarks false
      /IncludeHyperlinks false
      /IncludeInteractive false
      /IncludeLayers false
      /IncludeProfiles false
      /MultimediaHandling /UseObjectSettings
      /Namespace [
        (Adobe)
        (CreativeSuite)
        (2.0)
      ]
      /PDFXOutputIntentProfileSelector /DocumentCMYK
      /PreserveEditing true
      /UntaggedCMYKHandling /LeaveUntagged
      /UntaggedRGBHandling /UseDocumentProfile
      /UseDocumentBleed false
    >>
  ]
>> setdistillerparams
<<
  /HWResolution [2400 2400]
  /PageSize [612.000 792.000]
>> setpagedevice

