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cultivars for root yield in Ashwagandha (Withania somnifera L.)
Industrial Crops and Products 77 (2015) 648–657
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Industrial Crops and Products journal homepage: www.elsevier.com/locate/indcrop
Quantification of adaptability and stability among genotypes/cultivars for root yield in Ashwagandha (Withania somnifera L.) R.K. Lal ∗ CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, UP 220 015, India
a r t i c l e
i n f o
Article history: Received 14 April 2015 Received in revised form 8 September 2015 Accepted 13 September 2015 Available online 30 September 2015 Keywords: Adaptability Bio compounds Coefficient of variation Multivariate Stability
a b s t r a c t Ashwagandha (Withania somnifera L.), is one of the very important medicinal plant in Ayurveda since ancient times. It is a native of Mediterranean region grows wildly in arid and semi arid parts of India. Under the germplasm enhancement programme, thirty genetic stocks/cultivars of ashwagandha originated from selective divergence belongs to eight states of India (U.P., M.P., Rajasthan, Maharashtra, Kerala, J and K., A.P. and W.B.) were evaluated in the four consecutive years for the estimation of stability/adaptability. Using the AMMI model, ashwagandha genetic stocks namely, W 20, W 1 (cv. Pratap), W 2, W 3 (cv. Chetak), W 4 and W 6 (cv.Poshita) were expressed the high adaptability and stability for root yield over years. Therefore, above six selected genetic stocks/varieties recommended for commercial cultivation in India on large scale. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Ashwagandha (Withania somnifera L.), is belongs to the family‘Solanaceae’ a medicinal plants whose roots have been utilized in traditional Indian system of medicine, Ayarveda and Unani scince long. It is cultivated for its dry roots in arid and semi arid parts in India. It is a potential cash crop for greening the dry land zone and making the waste land productive. Its roots rich in withanoloides and alkaloides, which are used in preventing system of medicine as anti hepatoxic, anti inflammatory and sedative, etc. The roots of ashwagandha are also used for treating tumoures, rheumatic pain, nervous disorders and epilepsy. Besides above it has also antistress effects, anticancer activity, stimulates immune system and improve memory. Withaferin-A is therapeutically active withalolide reported to be present in leaves. Ashwagandha plants either tall type (wild) or with medium height having very hard and fibrous roots with inferior quality or dwarf and medium dwarf Manasa/Nagori type having very soft and pencil thickness roots with better quality types (Lal et al., 2012). It categorized under shrub with plant height reaches up to approximately 70–170 cm. It is cultivated over an area of 12,000 ha with a production of 2000 tones in India, while the annual demand is about 9000 tones requiring more its cultivation (Lal et al., 2012). Due to it drought tolerant capacity and rich in many bio-compounds, ashwagandha being in cultiva-
∗ Fax: +91 0522 2342666. E-mail address: [email protected] http://dx.doi.org/10.1016/j.indcrop.2015.09.035 0926-6690/© 2015 Elsevier B.V. All rights reserved.
tion in Madhya Pradesh, Rajasthan, Uttar Pradesh, Karnataka and West Bengal states of the India. The reports on ashwagandha genotypes for year × interactions (G × E) by use of AMMI Model related to stability/adaptability are very limited. It is felt need to develop stable variety for high root yield of better quality. Therefore, the objectives of present study were, to evaluate the dry root yield of thirty genetic stocks/cultivars across the four years in India and to estimate their stability/adaptability for cultivars/varieties recommendations for large area cultivation in India.
2. Materials and methods Thirty genotypes from indigenous collections of Ashwagandha (W. somnifera L.), collected/developed from eight different states of India like (Rajasthan, Maharashtra, Uttar Pradesh, Madhya Pradesh, Kerala, Jammu and Kashmir, West Bengal and Andhra Pradesh) used the materials for the experiments (Table 1). All genetic stocks/cultivars were evaluated at CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, U.P. PIN 226 015 (India) research farm in the four continuous years: 2009–2010, 2010–2011, 2011–2012 and 2012–2013 in a randomized block design with three replicates. Seed sown crop plants were maintained in 30 cm rows to row and 10 cm at plants to plant distances. The fertilizer applied as 60 N:40 P2 O5 :40 K2 O kg per hectare in the crop. Plants were uprooted after 150 days after sowing. Dried root yield was obtained on fresh root drying in semi shade conditions.
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Table 1 Genotypes origin, codes and means for AMMI I in Withania somnifera. S.No.
Accessions codes
Genotypes/accessions
Origin/places of collection
Mean
Count
Index
Name
Mean
Count
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W-1 W-2 W-3 W-4 W-5 W-6 W-7 W-8 W-9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
Variety CIMAP Pratap (released in the year 2011) Sagar-1 Variety CIMAP Chetak (released in the year 2011) BPL POYEL Variety Poshita (realesed in 1998) AGR-7 AGR-1-1 AGR-1-2 AGR-1-3 AGR-1-4 AGR-6 Sagar-2 NGR-1 MNAS NGR-9 NGR-1 NGR-2 NGR-3 NGR-4 NGR-5 Nagori NGR-8 NGR-9 NGR-10 NGR-11 NGR-12 NGR-13 NGR-14 NGR-15
CSIR-CIMAP, Lucknow, (India) Sagar, Madhya Predesh (India) CSIR-CIMAP, Lucknow, (India) Bhopal, Madhya Predesh (India) Palode (Kerala) CSIR-CIMAP, Lucknow, (India) Agra, U.P. (India) Pune, Maharashtra (India) Bharatpur, Rajasthan (India) Jammu (J and k) Fatahpur, U.P. (India) Agra, U.P. (India) Sagar, Madhya Predesh (India) Kota, Rajasthan (India) Manasa, Madhya Predesh (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Hyderabad, A.P. (India) Sagar, Madhya Predesh (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Krishnanagar, West Bengal (India) Agra, U.P., (North India)
91.43 67.12 96.86 93.29 13.98 95.33 16.66 85.07 87.67 81.87 84.17 94.59 47.54 6.68 81.99 82.06 87.11 83.68 83.73 160.69 82.48 84.68 7.18 7.67 10.67 8.04 8.50 8.33 6.80 7.83
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
20. 3. 6. 12. 4. 1. 9. 17. 8. 22. 11. 19. 18. 21. 16. 15. 10. 2. 13. 7. 5. 25. 27. 28. 26. 30. 24. 23. 29. 14.
W-20 W-3 W-4 W-12 W-4 W-1 W-9 W-17 W-8 W-22 W-11 W-19 W=18 W-21 W=16 W-15 W-10 W-2 W-13 W-7 W-5 W-25 W-27 W-28 W-26 W-30 W-24 W-23 W-29 W-14
160.69 96.86 95.33 94.59 93.29 91.43 87.67 87.11 85.07 84.68 84.17 83.73 83.68 82.48 82.06 81.99 81.87 67.12 47.54 16.66 13.98 10.67 8.50 8.33 8.04 7.83 7.67 7.18 6.80 6.68
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
Grand mean = 59.123 root yield ql/ha.
Statistical analysis: The calculations for stability parameter were workout for dry root yield ql/ha by the use of software for MATMODEL VERSION 3.0 on Additive main effects and multiplicative interactions model (Gauch, 2007), 3. Results and discussion The meticulous study of means, index and analysis of variance (ANOVA) reflected the presence of significant and high variability in the genotypes/cultivars of ashwagandha (Tables 1 and 2). The environmental mean and IPCA axis 1 score indicated that environment I was very favorable for dry root yield = 187.728 ql/ha followed by the environment II (24.678 ql/ha) and least root yield produced in environment III = 11.15 ql/ha, respectively (Table 3). This was also well reflected by IPCA axis 1 score = 4.369 for the genetic stock W-9 followed by 4.361score of W-18 and 4.359 for the genetic stock W19, respectively (Table 4). The least value for root yield was noted for the genotype W-7 with score = −5.956. The deviations in mean and rank of genotypes in all the four years also clearly indicated the presence of high G × E interactions (Tables 5–7). In the terms of the winners percent in the all four environments/years the 25 % same winners picked by AMMI F and AMMI I in the 1st year while 75% different winners selected in the 3rd year. Selected mean loss of AMMI 0 winners = 12.775 i.e. 21.608% of total mean. The mean to select AMMI 0 winners = 51.158 i.e. 86.529% of total mean. The highest AMMI 0 = 69.267 i.e. 117.158% of the total mean reflected by the environment 3rd where AMMI F selected W 1 variety CIMAP Pratap a newly released variety by CSIR-CIMAP, Lucknow in the year 2011 (Lal et al., 2012) but AMMI 0 selected W 20 also as winner. For the estimation of the significance and separation of means was also important for selection of stable genotypes as reflected by the high value = 196.096% of the total mean (Table 9). Mean value of normal (N) and the S.E. were also indicated the nature and amount of variability and bias present in ashwagandha genetic stocks for dry dry root yield (Tables 4–8). These
Fig. 1. Mata model version 3.0 mega-environments for AMMI 1 Model, cultivars, switchpoints, including hypothetical winners in Withania somnifera.
values were also useful for estimating the separation of means in the experiments over years. These were weighted grand mean without input data = 59.123 with 240 degree of freedom the root error mean square 200.809 with replicated in thrice, treatment means S.E. = 115.937 and C.V. for treatments 196.096% of genotypic mean (GM). The S.E.D. between two treatments = 163.960, 240 df t(0.5) % of 1.97 at LSD(0.5) = 322.922 (Table 9, Figs. 1 and 2). The AMMI
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R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
Table 2 Analysis of variance table for AMMI I model in Withania somnifera. Source of variation
df
Sum of square
Mean sum of square
Probability
Treatments Genotypes Environments/years GXE IPCA 1 Residual Error Total
119 29 3 87 31 56 240 359
4046515.36 611932.44 1994030.16 1440552.77 1263392.09 177160.67 9677796.72 13724312.08
34004.33 21101.12 664676.72 16558.08 40754.58 3163.58 40324.15 38229.28
0.852 0.980 0.000*** 0.999 0.457 1.000
Grand mean = 59.13 root yield ql/ha; large residuals exceeding by a the value 3.291 = ***.
Table 3 Environmental means and IPCA Axis 1 Scores in AMMI I model in Withania somnifera. S. No.
Environments
Means
Count
Score
Index
Years
Score
1. 2. 3. 4.
ENV. I (year 2009–2010) ENV. II (years 2010–2011) ENV.III (years 2011–2012) ENV.IV (years 2012–2013)
187.72 24.67 11.15 12.96
30 30 30 30
22.054 −6.826 −7.719 −7.509
1 2 4 3
ENV. I (years 2009–2010) ENV. II (years 2010–2011) ENV.IV (years 2012–2013) ENV.III (years 2011–2012)
22.054 −6.826 −7.509 −7.719
Grand mean = 59.123 root yield ql/ha; ENV = year.
Table 4 Scores of IPCA axis 1 Scores in Withania somnifera. S. No.
Genetic stocks
Scores
Index
Genetic stocks
Scores
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
1.951 −0.173 3.957 4.085 −5.919 4.061 −5.956 4.356 4.369 3.204 4.329 4.317 −1.301 −5.824 4.337 4.347 4.206 4.361 4.359 1.175 4.317 4.203 −5.879 −5.891 −5.806 −5.859 −5.806 −5.798 −5.628 −5.892
9 18 19 8 16 15 11. 12. 21. 17. 22. 4. 6. 3. 10. 1. 20. 2. 13. 28. 25. 27. 14. 29. 26. 23. 24. 30. 5. 7.
W- 9 W-18 W-19 W- 8 W-16 W-15 W-11 W-12 W-21 W-17 W-22 W- 4 W- 6 W- 3 W-10 W- 1 W-20 W- 2 W-13 W-28 W-25 W-27 W-14 W-29 W-26 W-23 W-24 W-30 W- 5 W- 7
4.369 4.361 4.359 4.356 4.347 4.337 4.329 4.317 4.317 4.206 4.203 4.085 4.061 3.957 3.204 1.951 1.175 −0.173 −1.301 −5.798 −5.806 −5.806 −5.824 −5.628 −5.859 −5.879 −5.891 −5.892 −5.919 −5.956
residual value = 187.69 was maximum for count 4 followed by 6.257 with count 5 (Table 10). Estimation of stability and adaptability patterns were also workout and reported by many workers in number of other crops like wheat, maize, etc over the environments/years ˛ (Finlay and Wilkinson, 1963; Purchase, 1997; Leeuvner, 2005; Lal, 2007). But my study is a new and unique on ashwagandha crop using AMMI Model. It is evident from the results that the distributions of ashwagandha genetic stocks/cultivars in the all the four years were also very impressive and well distributed (Figs. 3–6). The predicted data on high root yield was clearly indicated about the nature and amount of stability present in the genetic stocks over the years. High root yield stability usually indicates about the ability of genotypes for their consistent performance across a wide
range of years. Many biometrical methods like univariate and multivariate methods are available to estimate the stability (Lin et al., 1986; Purchase, 1997; Eskridge, 1990; Annicchiarico, 2002). In the AMMI model, the regression coefficient and environmental variance were the most viable tools for the estimation of stability and adaptability as reported by (Wrike, 1962; Shukla, 1972; Gauch, 2007). In the first year the highest AMMI value (318.403) expressed by the genetic stock W-12 followed by W-20 = 315.192 and W-6 = 313.481 in order. While the genetic stock W = 23 were least = 6.105 AMMI I value. The value of environment mean was = 187.716 with root mean square residual = 22.184. In the second year the AMMI I value was for W-20 = 118.216 followed by W-1 = 43.648 and for W-3 = 35.390, respectively. The Lowest AMMI I value was recorded for the genetic stock W-14 = 11.979 against environ-
Table 5 Genotypes means in the first year in Withania somnifera. Genoty-pes
Count
Data
AMMI I
Residuals
Rank
Index
Genotype name
Data
Index
Genotype name
AMMI 1
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
263.333 192.067 312.767 312.000 12.100 313.600 13.933 310.000 313.933 281.367 308.500 318.533 147.667 7.000 306.533 306.833 308.667 308.767 308.733 310.000 306.567 306.200 6.233 6.500 11.333 7.500 9.167 9.167 7.000 6.667
263.053 191.886 312.720 311.964 12.011 313.481 13.902 309.723 312.614 281.128 308.241 318.403 147.435 6.840 306.237 306.530 308.457 308.462 308.446 315.192 306.377 305.967 6.105 6.329 11.222 7.403 9.040 9.052 6.865 6.484
0.080 0.180 0.046 0.035 0.089 0.119 0.032 0.277 0.319 0.238 0.259 0.131 0.231 0.160 0.297 0.303 0.209 0.305 0.287 −5.192 0.290 0.234 0.128 0.171 0.111 0.098 0.127 0.114 0.135 0.182
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
12. 6. 9. 3. 4. 8. 20. 18. 19. 17. 11. 16. 21. 15. 22. 10. 1. 2. 13. 7. 5. 25. 28. 27. 26. 29. 14. 30. 29. 23.
W-12 W- 6 W- 9 W- 3 W- 4 W- 8 W-20 W-18 W-19 W-17 W-11 W-16 W-21 W-15 W-22 W-10 W- 1 W- 2 W-13 W- 7 W- 5 W-25 W-28 W-27 W-26 W-29 W-14 W-30 W-29 W-23
318.533 313.600 313.933 312.767 312.000 310.000 310.000 308.767 308.733 308.667 308.500 306.833 306.567 306.533 306.200 281.367 263.333 192.067 147.667 13.933 12.100 11.333 9.167 9.167 7.500 7.000 7.000 6.667 7.000 6.233
12. 20. 6. 3. 9. 4. 8. 18. 17. 19. 11. 16. 21. 15. 22. 10. 1. 2. 13. 7. 5. 25. 28. 27. 26. 29. 14. 30. 24. 23.
W-12 W-20 W- 6 W- 3 W- 9 W- 4 W-8 W-18 W-17 W-19 W-11 W-16 W-21 W-15 W-22 W-10 W- 1 W- 2 W-13 W- 7 W-5 W-25 W-28 W-27 W-26 W-29 W-14 W-30 W-24 W-23
318.403 315.192 313.481 313.481 312.614 311.964 309.723 308.462 308.457 308.446 308.241 306.530 306.377 306.237 305.967 281.128 263.053 191.886 147.435 13.902 12.011 11.222 9.052 9.040 7.403 6.865 6.840 6.484 6.329 6.105
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S.No.
First year mean = 187.716, gain = 0.0001: root mean2 residual = 22.184.
651
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R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
Table 6 Genotypes mean in the second year for Withania somnifera. S.No.
Genotypes
Count
data
AMMI I
Residual
Rank
Index
Genotype name
Data
Index
Genotype name
AMMI 1
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
41.167 27.300 31.833 28.900 16.267 27.333 20.867 10.833 11.800 16.600 10.667 26.000 13.333 6.167 7.000 6.833 15.600 8.333 9.167 313.933 7.833 13.167 8.000 7.200 12.000 9.833 9.167 9.167 7.000 6.667
43.648 33.843 35.390 30.954 19.927 33.158 22.856 20.877 23.387 25.537 20.157 30.663 21.968 11.979 17.929 17.926 23.942 19.456 19.515 118.216 18.550 21.527 12.861 13.425 15.839 13.584 13.677 13.455 12.124 13.595
−2.482 −6.543 −3.557 −2.054 −3.661 −5.825 −1.989 −10.043 −11.587 −8.937 −9.490 −4.663 −8.634 −5.813 −10.929 −11.092 −8.342 −11.122 −10.348 195.717*** −10.716 −8.359 −4.861 −6.225 −3.839 −3.751 −4..511 −4.289 −5.124 −6.929
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
20. 1. 3. 4. 6. 2. 12. 7. 10. 5. 17. 13. 22. 25. 9. 8. 11. 26. 19. 27. 28. 18. 23. 21. 24. 15. 29. 16. 30. 14.
W-20 W- 1 W- 3 W- 4 W- 6 W- 2 W-12 W-7 W-10 W-5 W-17 W-13 W-22 W-25 W- 9 W- 8 W-11 W-26 W-19 W-27 W-28 W-18 W-23 W-21 W-24 W-15 W-29 W-16 W-30 W-14
313.933 41.167 31.833 28.900 27.333 27.300 26.000 20.867 16.600 16.267 15.600 13.333 13.167 12.000 11.800 10.833 10.667 9.833 9.167 9.167 9.167 8.333 8.000 7.833 7.200 7.000 7.000 6.833 6.667 6.167
20. 1. 3. 2. 6. 4. 12. 10. 17. 9. 7. 13. 22. 8. 11. 5. 19. 18. 21. 15. 16. 25. 27. 30. 26. 28. 23. 24. 29. 14.
W-20 W- 1 W- 3 W- 2 W- 6 W- 4 W-12 W-10 W-17 W- 9 W- 7 W-13 W-22 W- 8 W-11 W- 5 W-19 W-18 W-21 W-15 W-16 W-25 W-27 W-30 W-26 W-28 W-24 W-23 W-29 W-14
118.216 43.648 35.390 33.843 33.158 30.954 30.663 25.537 23.942 23.387 22.856 21.968 21.527 20.877 20.157 19.927 19.515 19.456 18.550 17.929 17.926 15.839 13.677 13.595 13.584 13.455 13.425 12.861 12.124 11.979
Second year mean = 24.666, gain = 0.00001: large residuals exceeding a factor = 3.291 marked with *** assuming 0.1% of the residuals.
Table 7 Mean of the third year and response to AMMI effects in Withania somnifera. S. Nos
Genotypes
counts
Data
AMMI I
Residuals
Ranks
Index
Genotype name
data
Index
Genotype name
AMMI
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
31.667 24.567 13.333 13.100 12.367 11.900 12.667 9.767 13.267 13.667 8.333 16.500 14.167 7.333 6.767 7.167 9.000 8.800 8.900 9.333 7.167 9.933 6.833 8.967 10.667 6.833 8.500 7.333 6.200 8.500
28.391 20.484 18.341 13.790 11.701 16.016 14.662 3.471 5.969 9.159 2.175 13.292 9.616 3.668 0.540 0.527 6.670 2.045 2.107 103.652 1.179 4.257 4.599 5.174 7.511 5.304 5.350 5.121 3.816 5.344
23.276 4.083 −5.008 −1.690 0.665 −2.116 −1.996 6.296 7.297 4.507 5.559 3.208 4.551 3.666 6.227 6.639 2.329 6.755 6.793 −94.319*** 5.988 5.676 2.234 3.793 3.156 1.529 3.150 2.213 2.384 3.156
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
1 2 12 13 6 10 3 9 7 5 4 25 22 8 20 17 24 19 18 27 30 11 28 14 16 21 26 23 15 29
W- 1 W- 2 W-12 W-13 W- 6 W-10 W- 3 W- 9 W- 7 W- 5 W- 4 W-25 W-22 W- 8 W-20 W-17 W-24 W-19 W-18 W-27 W-30 W-11 W-28 W-14 W-16 W-21 W-26 W-23 W-15 W-29
31.667 24.567 16.500 14.167 11.900 13.667 13.333 13.267 12.667 12.367 13.100 10.667 9.933 9.767 9.333 9.000 8.967 8.900 8.800 8.500 8.500 8.333 7.333 7.333 7.167 7.167 6.833 6.833 6.767 6.200
20. 1. 2. 3. 6. 7. 4. 12. 5. 13. 10. 25. 17. 9. 27. 30. 26. 24. 28. 23. 22. 29. 14. 8. 11. 19. 18. 21. 16. 17.
W-20 W- 1 W- 2 W- 3 W- 6 W- 7 W- 4 W-12 W-5 W-13 W-10 W-25 W-17 W- 9 W-27 W-30 W-26 W-24 W-28 W-23 W-22 W-29 W-14 W- 8 W-11 W-19 W-18 W-21 W-16 W-17
103.652 28.391 20.484 18.341 16.016 14.662 13.790 13.292 11.701 9.616 9.159 7.511 6.670 5.969 5.350 5.344 5.304 5.174 5.121 4.599 4.257 3.816 3.668 3.471 2.175 2.107 2.045 1.179 0.540 0.527
Year third mean = 11.151, AMMI gain = 75.262: ***– residuals effect 3.291 with normality = 0.1%.
ment/year II mean = 24.67. In the year III the genetic stock W-20, index 20 = 103.65, W-1 = 28.391 and W-2 = 20.484 AMMI I value. The least AMMI I value expressed by the genetic stock W-17 = 0.527 with year mean 11.15 and AMMI gain = 75.262, respectively. In the
year IV, the AMMI I value was again high for the genetic stocks W-20 = 105.71 followed by W-1 genotype (30.61) and W-2 (22.25) while, the least was W-16 (3.250) against year IV mean 12.959 and AMMI gain = 75.098. Therefore, the genotypes W-20 with W-1 are
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Table 8 Mean and AMMI I values in the fourth year for Withania somnifera. S.Nos.
Genotypes
Count
Data
AMMI
Residuals
ranks
Index
Genotype name
Data
Index
Genotype name
AMMI
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
29.733 24.533 29.500 20.167 15.167 26.500 19.167 9.667 12.667 15.833 9.167 17.333 15.000 6.233 7.667 7.400 15.167 8.833 8.100 9.500 8.333 9.400 7.667 8.000 8.667 8.000 7.167 7.667 7.000 9.500
30.609 22.254 20.982 16.458 12.260 18.679 15.214 6.196 8.697 11.642 5.494 16.009 11.148 4.247 3.261 3.250 9.363 4.771 4.832 105.707 3.895 6.949 5.167 5.739 8.094 5.876 5.933 5.705 4.395 5.909
-0.875 2.279 8.518 3.709 2.906 7.821 3.953 3.471 3.969 4.192 3.673 1.325 3.852 1.987 4.406 4.149 5.803 4.062 3.268 −96.207*** 4.438 2.450 2.499 2.261 0.572 2.124 1.234 1.961 2.605 3.591
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
1. 3. 6. 2. 4. 7. 12. 10. 17. 5. 13. 9. 8. 20. 30. 22. 11. 18. 25. 21. 19. 26. 24. 28. 15. 23. 16. 27. 29. 14.
W- 1 W- 3 W- 6 W- 2 W- 4 W- 7 W-12 W-10 W-17 W- 5 W-13 W- 9 W- 8 W-20 W-30 W-22 W-11 W-18 W-25 W-21 W-19 W-26 W-24 W-28 W-15 W-23 W-16 W-27 W-29 W-14
29.733 29.500 26.500 24.533 20.167 19.167 17.333 15.833 15.167 15.167 15.000 12.667 9.667 9.500 9.500 9.400 9.167 8.833 8.667 8.333 8.100 8.000 8.000 7.667 7.667 7.667 7.400 7.167 7.000 6.233
20. 1. 2. 3. 6. 4. 12. 7. 5. 10. 13. 17. 9. 25. 22. 8. 27. 30. 26. 24. 28. 11. 23. 19. 18. 29. 14. 21. 15. 16.
W-20 W- 1 W- 2 W- 3 W- 6 W- 4 W-12 W- 7 W- 5 W-10 W-13 W-17 W- 9 W-25 W-22 W- 8 W-27 W-30 W-26 W-24 W-28 W-11 W-23 W-19 W-18 W-29 W-14 W-21 W-15 W-16
105.707 30.609 22.254 20.982 18.679 16.458 16.009 15.214 12.260 11.642 11.148 9.363 8.697 8.094 6.949 6.196 5.933 5.909 5.876 5.739 5.705 5.494 5.167 4.832 4.771 4.395 4.247 3.895 3.261 3.250
Environments IV and mean = 12.958, gain from AMMI = 75.098: *** – residuals exceeding by a factor3.291 are with normality 0.1%.
Table 9 Separation of means with typical bias in Withania somnifera. S. No.
Estimates
Scope
Count
First order
Typical bias
Genotypes
Years/environments
1.
GEN with one ENV
30
2.043
216.632
30
4
ENV within one GEN
4
1.029
119.343
30
4
3. 4.
Genotype and environment Environment and genotype TRT Details of estimates
120 With 240 degree of freedom
0.572 (3 reps.)
298.199 C.V. (mean)
– SED (mean)
5.
Estimates% of GM
All TRT Unweighted grand mean without imputed data 59.123
200.809
115.917
196.096 % of GM
163.960
– Df = 240 1.96995 (t0.05 %) Lsd0.05 322.992
2.
GEN = genotypes; ENV = environment/years; TRT = treatments; GM = grand mean.
Fig. 2. A AMMI I performance of genotypes in all four environments/years of Withania somnifera.
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R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
Table 10 AMMI1 residuals values, count and histogram for Withania somnifera genotypes. Interval
Maximum
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
6.25662 12.51324 18.76986 25.02648 31.2831 37.53972 43.79634 50.05296 56.30958 62.5662 68.82282 75.07944 81.33606 87.59269 93.84931 100.1059 106.3626 112.6192 118.8758 125.1324 131.389 137.6457 143.9023 150.1589 156.4155 162.6721 168.9288 175.1854 181.442 187.6986
Count
Histogram
5 1 4 5 27 17 10 22 0 0 0 1 0 1 4 9 2 0 0 0 11 0 0 0 0 0 0 0 0 1
********** ** ******** ********** ************************************************** ******************************** ******************* *****************************************
** ** ******** ***************** ****
*********************
**
200 187.716 180
160.691
160
140 Pooled mean 120 ENV MEAN 100 91.425
96.858 93.292 95.333
80
94.592 87.667 85.067 84.167 81.867
Linear (Pooled mean)
87.108 84.675 83.725 82.47 5 82.058 83.683 81.992
67.117 60 47.542 40 24.665
20
13.975 8 12.95 11.151
16.658 10.667 8.5 8.333 7.667 8.042 7.183 6.8 7.833
6.683
0 0
5
10
15
20
25
30
35
Fig. 3. Performance of pooled AMMI I and environments/years of 30 genotypes of Withania somnifera.
eligible for selection as stable genetic stocks along with other four genetic stocks namely, W-2, W-3, W-4 and W-6. Nevertheless, I have attempted to compare thirty different genetic stocks/cultivars of ashwagandha by applying AMMI model for stable root yield across the years. In brief the different genotypes of ashwagandha identified as stable genotype were W 20, W 1 (cv. Pratap), W 2, W 3 (cv. Chetak), W 4 and W 6 (cv.
Poshita) over the years/environments (Tables 5–8). The multivariate approach, the Additive Main Effects and Multiplicative interactions (AMMI model) is found clearly suitable/efficient model for partitioning the Genotype × Environment into the causes of variation in ashwagandha crops also. It is clearly depicted from the study that out of thirty genotypes/cultivars of ashwagandha six genotypes/cultivars were found highly stable for dry root yield
R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
655
200
ENV1 180
W20
160
140
120
Pooled mean
100 W3
W5
W4
W1
ENV MEAN
W12 W9 W8
W17 W11 W10
80
W16 W15
W19
W18
W22 W21
W2 60
W13 40
ENV II 20 W7 W5 ENV III
W26
W24
ENV IV W14
W23
W25
W28
W30
W27
W29
0 0
5
10
15
20
25
30
35
Fig. 4. Distribution of genotypes in environments/years of Withania somnifera.
performance of over years. Our findings were in consonance with other research worker’s worked on other crops like wheat, maize, ˛ etc. (Kang and Pham, 1991; Leeuvner, 2005, Lal et al., 2007, 2012). Selection of stable ashwagandha genotypes for dry root yield is a challenging job for any plant breeder especially, for estimation of G × E in the field trials over years. It is proved from my experiment results that the AMMI model is a good statistical method for the selection of the stable genetic stocks as well as to increase the plant breeder selection efficiency and/or breeding strategies. Which also facilitate the cultivar recommendation (the most important information) i.e. depends upon on the response and comparison between, genotypes of the crops.
Notwithstanding, based on the study results and application of the Additive Main Effects and Multiplicative Interactions model, out of thirty, six genotypes namely, W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W 4 and W 6 (cv. Poshita) were the highest performer for root yield and stability. Among the six stable selections, three genetic stocks/cultivars, namely W6 cv, Poshita was release as variety in the year, 1998 followed by W 1 cv. Pratap and w3 cv. Chetak (Nagori ashwagandha) released in the year 2011 for commercial cultivation for both North and South India. Therefore, all these six genotypes/cultivars, namely W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W4 and W6 (cv. Poshita) are recommended for commercial cultivation in larger areas.
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R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
Fig. 5. Plants of variety: CIMAP Pratap finger printing with OPJ primers of Withania somnifera.
Fig. 6. Plants of variety: CIMAP Chetak finger printing with OPJ primers of Nagauri Withania somnifera.
4. Conclusions
References
In the final conclusions by the use of AMMI model, out of thirty the six genotypes/cutivars of aswagandha namely, W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W 4 and W 6 were indicated high stable dry root yield over the years/environments. Therefore, above mentioned all the six genetic stocks/cultivars are recommended for cultivation on large scale.
Annicchiarico, P., 2002. Genotype × Environmental interactions; Challenges and opportunities for Plant Breeding and Cultivar Recommendations. FAO Plant Production and Protection Paper. 174, FAO, Rome. Eskridge, K.M., 1990. Selection of stable cultivars using a safety-first rule. Crop Sci. 30, 369–374. Finlay, K.W., Wilkinson, G.N., 1963. The analysis of adaptation in a plant—breeding programme. Aust. J. Agric. Res. 14, 742–754.
R.K. Lal / Industrial Crops and Products 77 (2015) 648–657 Gauch, H.G., 2007. MATAMODEL Version 3.0: Open Source Software for Ammi and Related Analyses, Crop and Soil Science. Cornell University, Ithaca, NY, pp. 14853. Kang, M.S., Pham, H.N., 1991. Simultaneous selection for yielding of stable crop genotypes. Agron. J. 83, 161–165. Lal, R.K., 2007. Stability and genotypes × environment interactions in Fennel. J. Herbs Spices Med. Plants 13, 47–54. Lal, R.K., Chandra, R., Chauhan, H.S., Misra, H.O., Sangwan, R.S., Gupta, M.M., Verma, R.K., Singh, A.K., Yadav, A.K., Dhawan, O.P., Kalra, A., Bahl, J.R., Singh, H.P., Gupta, A.K., Rai, S.K., Kumar, B., Dubey, B., Jhang, T., Singh, S., Singh, V.R., Panday, R., Bagchi, G.D., Sarkar, S., Singh, Smita, 2012. Registration of a new high yielding variety CIMAP-PRATAP of Ashwagandha [Withania somnifera (L.) Dunal] suitable for cultivation in drought prone areas of India. J. Med. Aromat. Plant Sci. 34, 178–182.
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˛ Leeuvner, D.V., 2005. Genotypes × Environment Interactions for Sun Flower Hybrids in South Africa. MSc. Thesis) University of Pretoia, Pretoria. Lin, C.S., Binns, M.R., Lefkovitch, L.P., 1986. Stability analysis: where do we stand? Crop Sci. 26, 894–900. Purchase, J.L., 1997. Parametric Analysis to Describe Genotype × Environment Interaction and Yield Stability in Winter Wheat. Ph.D. Thesis), University of Free State, Bloemfontein. Shukla, G.K., 1972. Some statistical aspects of partitioning genotypes—environmental components of variability. Heredity 29, 237–245. Wrike, G., 1962. v¨ ber eine method zur Erfassuny der ökologischen Streubreite in Feldversuchen. Z. Pflanzenz¨vchtg 47, 92–96.
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Industrial Crops and Products journal homepage: www.elsevier.com/locate/indcrop
Quantification of adaptability and stability among genotypes/cultivars for root yield in Ashwagandha (Withania somnifera L.) R.K. Lal ∗ CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, UP 220 015, India
a r t i c l e
i n f o
Article history: Received 14 April 2015 Received in revised form 8 September 2015 Accepted 13 September 2015 Available online 30 September 2015 Keywords: Adaptability Bio compounds Coefficient of variation Multivariate Stability
a b s t r a c t Ashwagandha (Withania somnifera L.), is one of the very important medicinal plant in Ayurveda since ancient times. It is a native of Mediterranean region grows wildly in arid and semi arid parts of India. Under the germplasm enhancement programme, thirty genetic stocks/cultivars of ashwagandha originated from selective divergence belongs to eight states of India (U.P., M.P., Rajasthan, Maharashtra, Kerala, J and K., A.P. and W.B.) were evaluated in the four consecutive years for the estimation of stability/adaptability. Using the AMMI model, ashwagandha genetic stocks namely, W 20, W 1 (cv. Pratap), W 2, W 3 (cv. Chetak), W 4 and W 6 (cv.Poshita) were expressed the high adaptability and stability for root yield over years. Therefore, above six selected genetic stocks/varieties recommended for commercial cultivation in India on large scale. © 2015 Elsevier B.V. All rights reserved.
1. Introduction Ashwagandha (Withania somnifera L.), is belongs to the family‘Solanaceae’ a medicinal plants whose roots have been utilized in traditional Indian system of medicine, Ayarveda and Unani scince long. It is cultivated for its dry roots in arid and semi arid parts in India. It is a potential cash crop for greening the dry land zone and making the waste land productive. Its roots rich in withanoloides and alkaloides, which are used in preventing system of medicine as anti hepatoxic, anti inflammatory and sedative, etc. The roots of ashwagandha are also used for treating tumoures, rheumatic pain, nervous disorders and epilepsy. Besides above it has also antistress effects, anticancer activity, stimulates immune system and improve memory. Withaferin-A is therapeutically active withalolide reported to be present in leaves. Ashwagandha plants either tall type (wild) or with medium height having very hard and fibrous roots with inferior quality or dwarf and medium dwarf Manasa/Nagori type having very soft and pencil thickness roots with better quality types (Lal et al., 2012). It categorized under shrub with plant height reaches up to approximately 70–170 cm. It is cultivated over an area of 12,000 ha with a production of 2000 tones in India, while the annual demand is about 9000 tones requiring more its cultivation (Lal et al., 2012). Due to it drought tolerant capacity and rich in many bio-compounds, ashwagandha being in cultiva-
∗ Fax: +91 0522 2342666. E-mail address: [email protected] http://dx.doi.org/10.1016/j.indcrop.2015.09.035 0926-6690/© 2015 Elsevier B.V. All rights reserved.
tion in Madhya Pradesh, Rajasthan, Uttar Pradesh, Karnataka and West Bengal states of the India. The reports on ashwagandha genotypes for year × interactions (G × E) by use of AMMI Model related to stability/adaptability are very limited. It is felt need to develop stable variety for high root yield of better quality. Therefore, the objectives of present study were, to evaluate the dry root yield of thirty genetic stocks/cultivars across the four years in India and to estimate their stability/adaptability for cultivars/varieties recommendations for large area cultivation in India.
2. Materials and methods Thirty genotypes from indigenous collections of Ashwagandha (W. somnifera L.), collected/developed from eight different states of India like (Rajasthan, Maharashtra, Uttar Pradesh, Madhya Pradesh, Kerala, Jammu and Kashmir, West Bengal and Andhra Pradesh) used the materials for the experiments (Table 1). All genetic stocks/cultivars were evaluated at CSIR-Central Institute of Medicinal and Aromatic Plants, Lucknow, U.P. PIN 226 015 (India) research farm in the four continuous years: 2009–2010, 2010–2011, 2011–2012 and 2012–2013 in a randomized block design with three replicates. Seed sown crop plants were maintained in 30 cm rows to row and 10 cm at plants to plant distances. The fertilizer applied as 60 N:40 P2 O5 :40 K2 O kg per hectare in the crop. Plants were uprooted after 150 days after sowing. Dried root yield was obtained on fresh root drying in semi shade conditions.
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Table 1 Genotypes origin, codes and means for AMMI I in Withania somnifera. S.No.
Accessions codes
Genotypes/accessions
Origin/places of collection
Mean
Count
Index
Name
Mean
Count
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W-1 W-2 W-3 W-4 W-5 W-6 W-7 W-8 W-9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
Variety CIMAP Pratap (released in the year 2011) Sagar-1 Variety CIMAP Chetak (released in the year 2011) BPL POYEL Variety Poshita (realesed in 1998) AGR-7 AGR-1-1 AGR-1-2 AGR-1-3 AGR-1-4 AGR-6 Sagar-2 NGR-1 MNAS NGR-9 NGR-1 NGR-2 NGR-3 NGR-4 NGR-5 Nagori NGR-8 NGR-9 NGR-10 NGR-11 NGR-12 NGR-13 NGR-14 NGR-15
CSIR-CIMAP, Lucknow, (India) Sagar, Madhya Predesh (India) CSIR-CIMAP, Lucknow, (India) Bhopal, Madhya Predesh (India) Palode (Kerala) CSIR-CIMAP, Lucknow, (India) Agra, U.P. (India) Pune, Maharashtra (India) Bharatpur, Rajasthan (India) Jammu (J and k) Fatahpur, U.P. (India) Agra, U.P. (India) Sagar, Madhya Predesh (India) Kota, Rajasthan (India) Manasa, Madhya Predesh (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Hyderabad, A.P. (India) Sagar, Madhya Predesh (India) Kota, Rajasthan (India) Kota, Rajasthan (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Sagar, Madhya Predesh (India) Krishnanagar, West Bengal (India) Agra, U.P., (North India)
91.43 67.12 96.86 93.29 13.98 95.33 16.66 85.07 87.67 81.87 84.17 94.59 47.54 6.68 81.99 82.06 87.11 83.68 83.73 160.69 82.48 84.68 7.18 7.67 10.67 8.04 8.50 8.33 6.80 7.83
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
20. 3. 6. 12. 4. 1. 9. 17. 8. 22. 11. 19. 18. 21. 16. 15. 10. 2. 13. 7. 5. 25. 27. 28. 26. 30. 24. 23. 29. 14.
W-20 W-3 W-4 W-12 W-4 W-1 W-9 W-17 W-8 W-22 W-11 W-19 W=18 W-21 W=16 W-15 W-10 W-2 W-13 W-7 W-5 W-25 W-27 W-28 W-26 W-30 W-24 W-23 W-29 W-14
160.69 96.86 95.33 94.59 93.29 91.43 87.67 87.11 85.07 84.68 84.17 83.73 83.68 82.48 82.06 81.99 81.87 67.12 47.54 16.66 13.98 10.67 8.50 8.33 8.04 7.83 7.67 7.18 6.80 6.68
4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4
Grand mean = 59.123 root yield ql/ha.
Statistical analysis: The calculations for stability parameter were workout for dry root yield ql/ha by the use of software for MATMODEL VERSION 3.0 on Additive main effects and multiplicative interactions model (Gauch, 2007), 3. Results and discussion The meticulous study of means, index and analysis of variance (ANOVA) reflected the presence of significant and high variability in the genotypes/cultivars of ashwagandha (Tables 1 and 2). The environmental mean and IPCA axis 1 score indicated that environment I was very favorable for dry root yield = 187.728 ql/ha followed by the environment II (24.678 ql/ha) and least root yield produced in environment III = 11.15 ql/ha, respectively (Table 3). This was also well reflected by IPCA axis 1 score = 4.369 for the genetic stock W-9 followed by 4.361score of W-18 and 4.359 for the genetic stock W19, respectively (Table 4). The least value for root yield was noted for the genotype W-7 with score = −5.956. The deviations in mean and rank of genotypes in all the four years also clearly indicated the presence of high G × E interactions (Tables 5–7). In the terms of the winners percent in the all four environments/years the 25 % same winners picked by AMMI F and AMMI I in the 1st year while 75% different winners selected in the 3rd year. Selected mean loss of AMMI 0 winners = 12.775 i.e. 21.608% of total mean. The mean to select AMMI 0 winners = 51.158 i.e. 86.529% of total mean. The highest AMMI 0 = 69.267 i.e. 117.158% of the total mean reflected by the environment 3rd where AMMI F selected W 1 variety CIMAP Pratap a newly released variety by CSIR-CIMAP, Lucknow in the year 2011 (Lal et al., 2012) but AMMI 0 selected W 20 also as winner. For the estimation of the significance and separation of means was also important for selection of stable genotypes as reflected by the high value = 196.096% of the total mean (Table 9). Mean value of normal (N) and the S.E. were also indicated the nature and amount of variability and bias present in ashwagandha genetic stocks for dry dry root yield (Tables 4–8). These
Fig. 1. Mata model version 3.0 mega-environments for AMMI 1 Model, cultivars, switchpoints, including hypothetical winners in Withania somnifera.
values were also useful for estimating the separation of means in the experiments over years. These were weighted grand mean without input data = 59.123 with 240 degree of freedom the root error mean square 200.809 with replicated in thrice, treatment means S.E. = 115.937 and C.V. for treatments 196.096% of genotypic mean (GM). The S.E.D. between two treatments = 163.960, 240 df t(0.5) % of 1.97 at LSD(0.5) = 322.922 (Table 9, Figs. 1 and 2). The AMMI
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Table 2 Analysis of variance table for AMMI I model in Withania somnifera. Source of variation
df
Sum of square
Mean sum of square
Probability
Treatments Genotypes Environments/years GXE IPCA 1 Residual Error Total
119 29 3 87 31 56 240 359
4046515.36 611932.44 1994030.16 1440552.77 1263392.09 177160.67 9677796.72 13724312.08
34004.33 21101.12 664676.72 16558.08 40754.58 3163.58 40324.15 38229.28
0.852 0.980 0.000*** 0.999 0.457 1.000
Grand mean = 59.13 root yield ql/ha; large residuals exceeding by a the value 3.291 = ***.
Table 3 Environmental means and IPCA Axis 1 Scores in AMMI I model in Withania somnifera. S. No.
Environments
Means
Count
Score
Index
Years
Score
1. 2. 3. 4.
ENV. I (year 2009–2010) ENV. II (years 2010–2011) ENV.III (years 2011–2012) ENV.IV (years 2012–2013)
187.72 24.67 11.15 12.96
30 30 30 30
22.054 −6.826 −7.719 −7.509
1 2 4 3
ENV. I (years 2009–2010) ENV. II (years 2010–2011) ENV.IV (years 2012–2013) ENV.III (years 2011–2012)
22.054 −6.826 −7.509 −7.719
Grand mean = 59.123 root yield ql/ha; ENV = year.
Table 4 Scores of IPCA axis 1 Scores in Withania somnifera. S. No.
Genetic stocks
Scores
Index
Genetic stocks
Scores
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
1.951 −0.173 3.957 4.085 −5.919 4.061 −5.956 4.356 4.369 3.204 4.329 4.317 −1.301 −5.824 4.337 4.347 4.206 4.361 4.359 1.175 4.317 4.203 −5.879 −5.891 −5.806 −5.859 −5.806 −5.798 −5.628 −5.892
9 18 19 8 16 15 11. 12. 21. 17. 22. 4. 6. 3. 10. 1. 20. 2. 13. 28. 25. 27. 14. 29. 26. 23. 24. 30. 5. 7.
W- 9 W-18 W-19 W- 8 W-16 W-15 W-11 W-12 W-21 W-17 W-22 W- 4 W- 6 W- 3 W-10 W- 1 W-20 W- 2 W-13 W-28 W-25 W-27 W-14 W-29 W-26 W-23 W-24 W-30 W- 5 W- 7
4.369 4.361 4.359 4.356 4.347 4.337 4.329 4.317 4.317 4.206 4.203 4.085 4.061 3.957 3.204 1.951 1.175 −0.173 −1.301 −5.798 −5.806 −5.806 −5.824 −5.628 −5.859 −5.879 −5.891 −5.892 −5.919 −5.956
residual value = 187.69 was maximum for count 4 followed by 6.257 with count 5 (Table 10). Estimation of stability and adaptability patterns were also workout and reported by many workers in number of other crops like wheat, maize, etc over the environments/years ˛ (Finlay and Wilkinson, 1963; Purchase, 1997; Leeuvner, 2005; Lal, 2007). But my study is a new and unique on ashwagandha crop using AMMI Model. It is evident from the results that the distributions of ashwagandha genetic stocks/cultivars in the all the four years were also very impressive and well distributed (Figs. 3–6). The predicted data on high root yield was clearly indicated about the nature and amount of stability present in the genetic stocks over the years. High root yield stability usually indicates about the ability of genotypes for their consistent performance across a wide
range of years. Many biometrical methods like univariate and multivariate methods are available to estimate the stability (Lin et al., 1986; Purchase, 1997; Eskridge, 1990; Annicchiarico, 2002). In the AMMI model, the regression coefficient and environmental variance were the most viable tools for the estimation of stability and adaptability as reported by (Wrike, 1962; Shukla, 1972; Gauch, 2007). In the first year the highest AMMI value (318.403) expressed by the genetic stock W-12 followed by W-20 = 315.192 and W-6 = 313.481 in order. While the genetic stock W = 23 were least = 6.105 AMMI I value. The value of environment mean was = 187.716 with root mean square residual = 22.184. In the second year the AMMI I value was for W-20 = 118.216 followed by W-1 = 43.648 and for W-3 = 35.390, respectively. The Lowest AMMI I value was recorded for the genetic stock W-14 = 11.979 against environ-
Table 5 Genotypes means in the first year in Withania somnifera. Genoty-pes
Count
Data
AMMI I
Residuals
Rank
Index
Genotype name
Data
Index
Genotype name
AMMI 1
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
263.333 192.067 312.767 312.000 12.100 313.600 13.933 310.000 313.933 281.367 308.500 318.533 147.667 7.000 306.533 306.833 308.667 308.767 308.733 310.000 306.567 306.200 6.233 6.500 11.333 7.500 9.167 9.167 7.000 6.667
263.053 191.886 312.720 311.964 12.011 313.481 13.902 309.723 312.614 281.128 308.241 318.403 147.435 6.840 306.237 306.530 308.457 308.462 308.446 315.192 306.377 305.967 6.105 6.329 11.222 7.403 9.040 9.052 6.865 6.484
0.080 0.180 0.046 0.035 0.089 0.119 0.032 0.277 0.319 0.238 0.259 0.131 0.231 0.160 0.297 0.303 0.209 0.305 0.287 −5.192 0.290 0.234 0.128 0.171 0.111 0.098 0.127 0.114 0.135 0.182
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
12. 6. 9. 3. 4. 8. 20. 18. 19. 17. 11. 16. 21. 15. 22. 10. 1. 2. 13. 7. 5. 25. 28. 27. 26. 29. 14. 30. 29. 23.
W-12 W- 6 W- 9 W- 3 W- 4 W- 8 W-20 W-18 W-19 W-17 W-11 W-16 W-21 W-15 W-22 W-10 W- 1 W- 2 W-13 W- 7 W- 5 W-25 W-28 W-27 W-26 W-29 W-14 W-30 W-29 W-23
318.533 313.600 313.933 312.767 312.000 310.000 310.000 308.767 308.733 308.667 308.500 306.833 306.567 306.533 306.200 281.367 263.333 192.067 147.667 13.933 12.100 11.333 9.167 9.167 7.500 7.000 7.000 6.667 7.000 6.233
12. 20. 6. 3. 9. 4. 8. 18. 17. 19. 11. 16. 21. 15. 22. 10. 1. 2. 13. 7. 5. 25. 28. 27. 26. 29. 14. 30. 24. 23.
W-12 W-20 W- 6 W- 3 W- 9 W- 4 W-8 W-18 W-17 W-19 W-11 W-16 W-21 W-15 W-22 W-10 W- 1 W- 2 W-13 W- 7 W-5 W-25 W-28 W-27 W-26 W-29 W-14 W-30 W-24 W-23
318.403 315.192 313.481 313.481 312.614 311.964 309.723 308.462 308.457 308.446 308.241 306.530 306.377 306.237 305.967 281.128 263.053 191.886 147.435 13.902 12.011 11.222 9.052 9.040 7.403 6.865 6.840 6.484 6.329 6.105
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S.No.
First year mean = 187.716, gain = 0.0001: root mean2 residual = 22.184.
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Table 6 Genotypes mean in the second year for Withania somnifera. S.No.
Genotypes
Count
data
AMMI I
Residual
Rank
Index
Genotype name
Data
Index
Genotype name
AMMI 1
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
41.167 27.300 31.833 28.900 16.267 27.333 20.867 10.833 11.800 16.600 10.667 26.000 13.333 6.167 7.000 6.833 15.600 8.333 9.167 313.933 7.833 13.167 8.000 7.200 12.000 9.833 9.167 9.167 7.000 6.667
43.648 33.843 35.390 30.954 19.927 33.158 22.856 20.877 23.387 25.537 20.157 30.663 21.968 11.979 17.929 17.926 23.942 19.456 19.515 118.216 18.550 21.527 12.861 13.425 15.839 13.584 13.677 13.455 12.124 13.595
−2.482 −6.543 −3.557 −2.054 −3.661 −5.825 −1.989 −10.043 −11.587 −8.937 −9.490 −4.663 −8.634 −5.813 −10.929 −11.092 −8.342 −11.122 −10.348 195.717*** −10.716 −8.359 −4.861 −6.225 −3.839 −3.751 −4..511 −4.289 −5.124 −6.929
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
20. 1. 3. 4. 6. 2. 12. 7. 10. 5. 17. 13. 22. 25. 9. 8. 11. 26. 19. 27. 28. 18. 23. 21. 24. 15. 29. 16. 30. 14.
W-20 W- 1 W- 3 W- 4 W- 6 W- 2 W-12 W-7 W-10 W-5 W-17 W-13 W-22 W-25 W- 9 W- 8 W-11 W-26 W-19 W-27 W-28 W-18 W-23 W-21 W-24 W-15 W-29 W-16 W-30 W-14
313.933 41.167 31.833 28.900 27.333 27.300 26.000 20.867 16.600 16.267 15.600 13.333 13.167 12.000 11.800 10.833 10.667 9.833 9.167 9.167 9.167 8.333 8.000 7.833 7.200 7.000 7.000 6.833 6.667 6.167
20. 1. 3. 2. 6. 4. 12. 10. 17. 9. 7. 13. 22. 8. 11. 5. 19. 18. 21. 15. 16. 25. 27. 30. 26. 28. 23. 24. 29. 14.
W-20 W- 1 W- 3 W- 2 W- 6 W- 4 W-12 W-10 W-17 W- 9 W- 7 W-13 W-22 W- 8 W-11 W- 5 W-19 W-18 W-21 W-15 W-16 W-25 W-27 W-30 W-26 W-28 W-24 W-23 W-29 W-14
118.216 43.648 35.390 33.843 33.158 30.954 30.663 25.537 23.942 23.387 22.856 21.968 21.527 20.877 20.157 19.927 19.515 19.456 18.550 17.929 17.926 15.839 13.677 13.595 13.584 13.455 13.425 12.861 12.124 11.979
Second year mean = 24.666, gain = 0.00001: large residuals exceeding a factor = 3.291 marked with *** assuming 0.1% of the residuals.
Table 7 Mean of the third year and response to AMMI effects in Withania somnifera. S. Nos
Genotypes
counts
Data
AMMI I
Residuals
Ranks
Index
Genotype name
data
Index
Genotype name
AMMI
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
31.667 24.567 13.333 13.100 12.367 11.900 12.667 9.767 13.267 13.667 8.333 16.500 14.167 7.333 6.767 7.167 9.000 8.800 8.900 9.333 7.167 9.933 6.833 8.967 10.667 6.833 8.500 7.333 6.200 8.500
28.391 20.484 18.341 13.790 11.701 16.016 14.662 3.471 5.969 9.159 2.175 13.292 9.616 3.668 0.540 0.527 6.670 2.045 2.107 103.652 1.179 4.257 4.599 5.174 7.511 5.304 5.350 5.121 3.816 5.344
23.276 4.083 −5.008 −1.690 0.665 −2.116 −1.996 6.296 7.297 4.507 5.559 3.208 4.551 3.666 6.227 6.639 2.329 6.755 6.793 −94.319*** 5.988 5.676 2.234 3.793 3.156 1.529 3.150 2.213 2.384 3.156
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
1 2 12 13 6 10 3 9 7 5 4 25 22 8 20 17 24 19 18 27 30 11 28 14 16 21 26 23 15 29
W- 1 W- 2 W-12 W-13 W- 6 W-10 W- 3 W- 9 W- 7 W- 5 W- 4 W-25 W-22 W- 8 W-20 W-17 W-24 W-19 W-18 W-27 W-30 W-11 W-28 W-14 W-16 W-21 W-26 W-23 W-15 W-29
31.667 24.567 16.500 14.167 11.900 13.667 13.333 13.267 12.667 12.367 13.100 10.667 9.933 9.767 9.333 9.000 8.967 8.900 8.800 8.500 8.500 8.333 7.333 7.333 7.167 7.167 6.833 6.833 6.767 6.200
20. 1. 2. 3. 6. 7. 4. 12. 5. 13. 10. 25. 17. 9. 27. 30. 26. 24. 28. 23. 22. 29. 14. 8. 11. 19. 18. 21. 16. 17.
W-20 W- 1 W- 2 W- 3 W- 6 W- 7 W- 4 W-12 W-5 W-13 W-10 W-25 W-17 W- 9 W-27 W-30 W-26 W-24 W-28 W-23 W-22 W-29 W-14 W- 8 W-11 W-19 W-18 W-21 W-16 W-17
103.652 28.391 20.484 18.341 16.016 14.662 13.790 13.292 11.701 9.616 9.159 7.511 6.670 5.969 5.350 5.344 5.304 5.174 5.121 4.599 4.257 3.816 3.668 3.471 2.175 2.107 2.045 1.179 0.540 0.527
Year third mean = 11.151, AMMI gain = 75.262: ***– residuals effect 3.291 with normality = 0.1%.
ment/year II mean = 24.67. In the year III the genetic stock W-20, index 20 = 103.65, W-1 = 28.391 and W-2 = 20.484 AMMI I value. The least AMMI I value expressed by the genetic stock W-17 = 0.527 with year mean 11.15 and AMMI gain = 75.262, respectively. In the
year IV, the AMMI I value was again high for the genetic stocks W-20 = 105.71 followed by W-1 genotype (30.61) and W-2 (22.25) while, the least was W-16 (3.250) against year IV mean 12.959 and AMMI gain = 75.098. Therefore, the genotypes W-20 with W-1 are
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Table 8 Mean and AMMI I values in the fourth year for Withania somnifera. S.Nos.
Genotypes
Count
Data
AMMI
Residuals
ranks
Index
Genotype name
Data
Index
Genotype name
AMMI
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
W- 1 W- 2 W- 3 W- 4 W- 5 W- 6 W- 7 W- 8 W- 9 W-10 W-11 W-12 W-13 W-14 W-15 W-16 W-17 W-18 W-19 W-20 W-21 W-22 W-23 W-24 W-25 W-26 W-27 W-28 W-29 W-30
3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
29.733 24.533 29.500 20.167 15.167 26.500 19.167 9.667 12.667 15.833 9.167 17.333 15.000 6.233 7.667 7.400 15.167 8.833 8.100 9.500 8.333 9.400 7.667 8.000 8.667 8.000 7.167 7.667 7.000 9.500
30.609 22.254 20.982 16.458 12.260 18.679 15.214 6.196 8.697 11.642 5.494 16.009 11.148 4.247 3.261 3.250 9.363 4.771 4.832 105.707 3.895 6.949 5.167 5.739 8.094 5.876 5.933 5.705 4.395 5.909
-0.875 2.279 8.518 3.709 2.906 7.821 3.953 3.471 3.969 4.192 3.673 1.325 3.852 1.987 4.406 4.149 5.803 4.062 3.268 −96.207*** 4.438 2.450 2.499 2.261 0.572 2.124 1.234 1.961 2.605 3.591
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30.
1. 3. 6. 2. 4. 7. 12. 10. 17. 5. 13. 9. 8. 20. 30. 22. 11. 18. 25. 21. 19. 26. 24. 28. 15. 23. 16. 27. 29. 14.
W- 1 W- 3 W- 6 W- 2 W- 4 W- 7 W-12 W-10 W-17 W- 5 W-13 W- 9 W- 8 W-20 W-30 W-22 W-11 W-18 W-25 W-21 W-19 W-26 W-24 W-28 W-15 W-23 W-16 W-27 W-29 W-14
29.733 29.500 26.500 24.533 20.167 19.167 17.333 15.833 15.167 15.167 15.000 12.667 9.667 9.500 9.500 9.400 9.167 8.833 8.667 8.333 8.100 8.000 8.000 7.667 7.667 7.667 7.400 7.167 7.000 6.233
20. 1. 2. 3. 6. 4. 12. 7. 5. 10. 13. 17. 9. 25. 22. 8. 27. 30. 26. 24. 28. 11. 23. 19. 18. 29. 14. 21. 15. 16.
W-20 W- 1 W- 2 W- 3 W- 6 W- 4 W-12 W- 7 W- 5 W-10 W-13 W-17 W- 9 W-25 W-22 W- 8 W-27 W-30 W-26 W-24 W-28 W-11 W-23 W-19 W-18 W-29 W-14 W-21 W-15 W-16
105.707 30.609 22.254 20.982 18.679 16.458 16.009 15.214 12.260 11.642 11.148 9.363 8.697 8.094 6.949 6.196 5.933 5.909 5.876 5.739 5.705 5.494 5.167 4.832 4.771 4.395 4.247 3.895 3.261 3.250
Environments IV and mean = 12.958, gain from AMMI = 75.098: *** – residuals exceeding by a factor3.291 are with normality 0.1%.
Table 9 Separation of means with typical bias in Withania somnifera. S. No.
Estimates
Scope
Count
First order
Typical bias
Genotypes
Years/environments
1.
GEN with one ENV
30
2.043
216.632
30
4
ENV within one GEN
4
1.029
119.343
30
4
3. 4.
Genotype and environment Environment and genotype TRT Details of estimates
120 With 240 degree of freedom
0.572 (3 reps.)
298.199 C.V. (mean)
– SED (mean)
5.
Estimates% of GM
All TRT Unweighted grand mean without imputed data 59.123
200.809
115.917
196.096 % of GM
163.960
– Df = 240 1.96995 (t0.05 %) Lsd0.05 322.992
2.
GEN = genotypes; ENV = environment/years; TRT = treatments; GM = grand mean.
Fig. 2. A AMMI I performance of genotypes in all four environments/years of Withania somnifera.
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Table 10 AMMI1 residuals values, count and histogram for Withania somnifera genotypes. Interval
Maximum
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30
6.25662 12.51324 18.76986 25.02648 31.2831 37.53972 43.79634 50.05296 56.30958 62.5662 68.82282 75.07944 81.33606 87.59269 93.84931 100.1059 106.3626 112.6192 118.8758 125.1324 131.389 137.6457 143.9023 150.1589 156.4155 162.6721 168.9288 175.1854 181.442 187.6986
Count
Histogram
5 1 4 5 27 17 10 22 0 0 0 1 0 1 4 9 2 0 0 0 11 0 0 0 0 0 0 0 0 1
********** ** ******** ********** ************************************************** ******************************** ******************* *****************************************
** ** ******** ***************** ****
*********************
**
200 187.716 180
160.691
160
140 Pooled mean 120 ENV MEAN 100 91.425
96.858 93.292 95.333
80
94.592 87.667 85.067 84.167 81.867
Linear (Pooled mean)
87.108 84.675 83.725 82.47 5 82.058 83.683 81.992
67.117 60 47.542 40 24.665
20
13.975 8 12.95 11.151
16.658 10.667 8.5 8.333 7.667 8.042 7.183 6.8 7.833
6.683
0 0
5
10
15
20
25
30
35
Fig. 3. Performance of pooled AMMI I and environments/years of 30 genotypes of Withania somnifera.
eligible for selection as stable genetic stocks along with other four genetic stocks namely, W-2, W-3, W-4 and W-6. Nevertheless, I have attempted to compare thirty different genetic stocks/cultivars of ashwagandha by applying AMMI model for stable root yield across the years. In brief the different genotypes of ashwagandha identified as stable genotype were W 20, W 1 (cv. Pratap), W 2, W 3 (cv. Chetak), W 4 and W 6 (cv.
Poshita) over the years/environments (Tables 5–8). The multivariate approach, the Additive Main Effects and Multiplicative interactions (AMMI model) is found clearly suitable/efficient model for partitioning the Genotype × Environment into the causes of variation in ashwagandha crops also. It is clearly depicted from the study that out of thirty genotypes/cultivars of ashwagandha six genotypes/cultivars were found highly stable for dry root yield
R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
655
200
ENV1 180
W20
160
140
120
Pooled mean
100 W3
W5
W4
W1
ENV MEAN
W12 W9 W8
W17 W11 W10
80
W16 W15
W19
W18
W22 W21
W2 60
W13 40
ENV II 20 W7 W5 ENV III
W26
W24
ENV IV W14
W23
W25
W28
W30
W27
W29
0 0
5
10
15
20
25
30
35
Fig. 4. Distribution of genotypes in environments/years of Withania somnifera.
performance of over years. Our findings were in consonance with other research worker’s worked on other crops like wheat, maize, ˛ etc. (Kang and Pham, 1991; Leeuvner, 2005, Lal et al., 2007, 2012). Selection of stable ashwagandha genotypes for dry root yield is a challenging job for any plant breeder especially, for estimation of G × E in the field trials over years. It is proved from my experiment results that the AMMI model is a good statistical method for the selection of the stable genetic stocks as well as to increase the plant breeder selection efficiency and/or breeding strategies. Which also facilitate the cultivar recommendation (the most important information) i.e. depends upon on the response and comparison between, genotypes of the crops.
Notwithstanding, based on the study results and application of the Additive Main Effects and Multiplicative Interactions model, out of thirty, six genotypes namely, W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W 4 and W 6 (cv. Poshita) were the highest performer for root yield and stability. Among the six stable selections, three genetic stocks/cultivars, namely W6 cv, Poshita was release as variety in the year, 1998 followed by W 1 cv. Pratap and w3 cv. Chetak (Nagori ashwagandha) released in the year 2011 for commercial cultivation for both North and South India. Therefore, all these six genotypes/cultivars, namely W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W4 and W6 (cv. Poshita) are recommended for commercial cultivation in larger areas.
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R.K. Lal / Industrial Crops and Products 77 (2015) 648–657
Fig. 5. Plants of variety: CIMAP Pratap finger printing with OPJ primers of Withania somnifera.
Fig. 6. Plants of variety: CIMAP Chetak finger printing with OPJ primers of Nagauri Withania somnifera.
4. Conclusions
References
In the final conclusions by the use of AMMI model, out of thirty the six genotypes/cutivars of aswagandha namely, W 20, W 1 (cv. Pratap), W2, W3 (cv. Chetak), W 4 and W 6 were indicated high stable dry root yield over the years/environments. Therefore, above mentioned all the six genetic stocks/cultivars are recommended for cultivation on large scale.
Annicchiarico, P., 2002. Genotype × Environmental interactions; Challenges and opportunities for Plant Breeding and Cultivar Recommendations. FAO Plant Production and Protection Paper. 174, FAO, Rome. Eskridge, K.M., 1990. Selection of stable cultivars using a safety-first rule. Crop Sci. 30, 369–374. Finlay, K.W., Wilkinson, G.N., 1963. The analysis of adaptation in a plant—breeding programme. Aust. J. Agric. Res. 14, 742–754.
R.K. Lal / Industrial Crops and Products 77 (2015) 648–657 Gauch, H.G., 2007. MATAMODEL Version 3.0: Open Source Software for Ammi and Related Analyses, Crop and Soil Science. Cornell University, Ithaca, NY, pp. 14853. Kang, M.S., Pham, H.N., 1991. Simultaneous selection for yielding of stable crop genotypes. Agron. J. 83, 161–165. Lal, R.K., 2007. Stability and genotypes × environment interactions in Fennel. J. Herbs Spices Med. Plants 13, 47–54. Lal, R.K., Chandra, R., Chauhan, H.S., Misra, H.O., Sangwan, R.S., Gupta, M.M., Verma, R.K., Singh, A.K., Yadav, A.K., Dhawan, O.P., Kalra, A., Bahl, J.R., Singh, H.P., Gupta, A.K., Rai, S.K., Kumar, B., Dubey, B., Jhang, T., Singh, S., Singh, V.R., Panday, R., Bagchi, G.D., Sarkar, S., Singh, Smita, 2012. Registration of a new high yielding variety CIMAP-PRATAP of Ashwagandha [Withania somnifera (L.) Dunal] suitable for cultivation in drought prone areas of India. J. Med. Aromat. Plant Sci. 34, 178–182.
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˛ Leeuvner, D.V., 2005. Genotypes × Environment Interactions for Sun Flower Hybrids in South Africa. MSc. Thesis) University of Pretoia, Pretoria. Lin, C.S., Binns, M.R., Lefkovitch, L.P., 1986. Stability analysis: where do we stand? Crop Sci. 26, 894–900. Purchase, J.L., 1997. Parametric Analysis to Describe Genotype × Environment Interaction and Yield Stability in Winter Wheat. Ph.D. Thesis), University of Free State, Bloemfontein. Shukla, G.K., 1972. Some statistical aspects of partitioning genotypes—environmental components of variability. Heredity 29, 237–245. Wrike, G., 1962. v¨ ber eine method zur Erfassuny der ökologischen Streubreite in Feldversuchen. Z. Pflanzenz¨vchtg 47, 92–96.