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Adaptability patterns and stable cultivar selection in menthol mint (Mentha arvensis L.)
Industrial Crops and Products 50 (2013) 176–181
Contents lists available at ScienceDirect
Industrial Crops and Products journal homepage: www.elsevier.com/locate/indcrop
Adaptability patterns and stable cultivar selection in menthol mint (Mentha arvensis L.) R.K. Lal ∗ CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, U.P. 226015, India
a r t i c l e
i n f o
Article history: Received 10 May 2013 Received in revised form 2 July 2013 Accepted 4 July 2013 Keywords: Adaptability Genotype × environment interaction Mentha arvensis Multiyear Stability parameters
a b s t r a c t The investigation was carried out to determine the stability and adaptability patterns of a set of ten cultivars of Mentha arvensis L. in different years in India, namely, MAS-1, Himalaya, Gomti, Sambhaw, Kalaka, Damroo, CIMAP-Saryu, Kosi, Kushal and Saksham, in a multi- year evaluation trial across three consecutive years. In the adaptation strategy the important steps here was to study/assess the performance of menthol mint varieties in multiyear trials. It was observed in this study that three mint varieties namely, Kosi, Kushal and CIMAP Saryu showed high stability for essential oil yield over years. Additive main effects and multiplicative interaction (AMMI) modal was found most efficient and practical alternative to selection of better adapted menthol mint cultivars. Based on the AMMI model, cultivars Kosi, Kushal and CIMAP Saryu expressed the high adaptability over years due to its ability to tolerate wide environmental conditions in different years/environments. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Menthol mint (Mentha arvensis L.) is a genus of about 25 species of the family-Lamiaceae is widely used in the food, flavourings, pharmaceutical and cosmetic industries. In addition to being a popular flavouring for food, confectionery and cigarettes, natural menthol has a cooling, soothing effect on the skin and mucous membranes of the human body, making it a useful ingredient in pharmaceuticals and cosmetics. Worldwide, approximately 10,000 tonnes of natural menthol and 2000 tonnes of synthetic menthol are used by the pharmaceutical, cosmetic and cigarette industries every year (Yaseen et al., 2000; Annicchiarico, 2002; Lal, 2007, 2012). Until about 15 years ago, the bulk of the world’s corm mint came from Brazil and China. China and India subsequently overtook Brazil and, more recently, India has led the world in the production of this useful plant and its products (Lal et al., 2000; Yaseen et al., 2000). An adaptable and stable cultivar usually refers to a cultivars’s ability to perform consistently, across a wide range of years/environments (Annicchiarico, 2002). Several biometrical methods including univariate and multivariate ones have been developed to assess stability (Akc¸ura et al., 2005). Among them the most widely used are the regression coefficient (Finlay and Wilkinson, 1963) the environmental variance (Lin et al., 1986), the
∗ Correspondence address: Department of Genetics and Plant Breeding, India. Tel.: +91 522 2718523; fax: +91 522 2342666. E-mail addresses: [email protected], [email protected] 0926-6690/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.indcrop.2013.07.008
Shukla’s (1972) stability variance and Wrike’s ecovalence (1962). More recently, the AMMI stability value (ASV) based on the AMMI (Additive Main Effects and Multiplicative interactions) model’s PCA1 and PCA2 (Principal Components Axis 1 and 2 respectively) scores for each cultivar/cultivar Purchase, 1997). This AVS is in effects the distance from the coordinate point to the origin in a two dimensional scatter gram of PCA 1 scores against PCA 2 scores ˛ (Leeuvner, 2005). For testing a number of cultivars of menthol mint crop in a number of years the multi-year yield trials are the most important experiments in mint breeding programme. Accordingly, effective model of statistical analysis related to multi-year trials can help plant breeders to make faster genetic improvement in a number of statistical models. Among them AMMI model was found very powerful model for the above purpose. The practical interest of combining high levels of mean yield and yield stability has led to the development of the yield reliability concept (Eskridge, 1990; Kang and Pham, 1991), where a reliable cultivar is characterized by consistently high yield of essential oil across the years/environments (Annicchiarico, 2002). The use of a yield reliability index facilitates, cultivar selection or recommendation, as the mean yield and the yield stability are combined into a unique measure of genotype merit (Annicchiarico, 2002). Studies of cultivar by environment interactions (G × E) and stability have been reported very meagre on mint crop. However, no stability and reliability studies have been performed for menthol mint cultivars and tested together in a multiyear essential oil yield trial. The objectives of present study were to evaluate the essential oil yield of ten commercial cultivars namely, Kosi, Kushal, Saksham, Kalaka, MAS-1, Himalaya, CIMAP-Saryu, Sambhaw, Damroo
R.K. Lal / Industrial Crops and Products 50 (2013) 176–181
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Table 1 Morphological characters and composition of essential oil of menthol mint cultivars. S. No. Cultivars
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
Morphological characters of cultivars
Kosi Kushal
Light green leaves, Bushy, thin suckers Dark green, broad leaves Erect, thick suckers, tolerate high moisture in soil Sakshham Dark green, broad leaves Erect, thick suckers, Insect resistant Kalka Light green leaves, thin suckers, susceptible to leaf spot disease MAS-1 Light green leaves, very thin suckers Dark green, broad leaves Erect, thick suckers Himalaya CIMAP Saryu Light green, leathery broad leaves, Erect, thick suckers Shambhaw Light green leaves, thin suckers Damroo Dark green, leathery broad leaves, Erect, thick suckers, stem thick Gomti Dark green, broad leaves Erect, thick suckers
Essential oil compositions (content in %) Menthol Menthone Iso-menthone Neo-menthol Menthyl acetate Pulegone
Limonene
75.76 79.04
5.77 4.69
3.25 2.45
2.16 2.22
0.06 5.01
0.12 0.07
2.48 0.69
76.92
8.68
3.05
1.92
1.81
0.11
2.12
68.12
10.46
3.45
2.05
2.67
1.47
4.52
78.21 72.31 76.14
10.18 8.74 7.09
1.90 3.26 3.71
2.02 1.98 2.44
0.35 3.16 3.39
1.52 1.51 0.31
5.40 3.46 0.92
74.12 72.71
9.08 11.69
2.99 3.34
2.41 2.39
3.92 0.01
0.12 0.85
1.49 1.80
70.84
7.77
3.32
2.12
0.08
0.58
4.57
and Gomti of menthol mint (M. arvensis L) released by CSIR-CIMAP, Lucknow (India), for commercial cultivation in different years in India and to determine their stability and reliability for cultivar recommendations. 2. Materials and methods Ten cultivars of menthol mint (M. arvensis L.), namely, Kosi, Kushal, Saksham, Kalaka, MAS-1, Himalaya, CIMAP-Saryu, Sambhaw, Damroo and Gomti only released by CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, U.P. 226015, India (Table 1) for commercial cultivation were evaluated at the research farm of the Institute in the three consecutive growing years: 2005–06, 2006–07 and 2007–08 in a randomized complete block design with three replications. The suckers in pieces (size = 5 cm) were planted in 40 cm rows to rows and 5 cm pieces to pieces. The plants received normal intercultural operations, irrigation, and fertilizer applications (120 kg N, 80 kg P2 O5 , and 60 kg K2 O per hectare). Minimum and maximum night and day temperatures ranged 8–11 ◦ C to 15–17 ◦ C, respectively, during suckers planting time and from 25–30 ◦ C to 35–40 ◦ C, respectively, during harvesting time. Average rainfall during the growing season was 5–7 mm according to weather data of the Metrological Laboratory of CSIR-CIMAP, Lucknow, India. Essential oil was done in fresh herbs by hydro-distillation using Clevenger type apparatus (Clevenger, 1928). The oil composition was analyzed by GC using Varian CX-3400 instrument employing 30 m × 0.25 m SUPELCOWAX-10 capillary columns with temperature programme from 50–220 ◦ C @ 6◦ /m, initial and final temperature holds of 2 and 5 min, respectively. H2 used as carrier gas at 1 ml/min. Data were processed on AIMIL chromatography data system. Identification of constitutes based on retention data of reference compounds.
3. Results The wide variation recorded for morphological characters in different cultivars of menthol mint (Table 1). The differences in rank of cultivars in the different years/environments indicated the presence of genotype and environment (G × E) interactions (Tables 2–4). After meticulous study of Tables 5–7, some interesting findings comes out regarding the winners for examples AMMI F and AMMI I picked the same winners in year 2nd (66.67%) but they picked different winner in the year 1st (33.33%). AMMI F were ranking more to be trusted, the average loss from selecting AMMI I winners should be 12.44 or 13.79% of the grand mean. AMMI I were ranking more to be trusted, the average gain from selecting AMMI I winners would be 5.27 or 5.84 percent of the grand mean. The largest AMMI I gain of 15.80 or 17.51 percent of the grand mean occurs in the year 2nd where AMMI F picks cultivar Sambhaw but AMMI I picks cultivar Kosi instead. The values presented in Table 8 may be useful for assessing the significance of mean separations in
2.1. Statistical analysis Observations were recorded on each cultivar for the most important economic traits: essential oil yield (kg/ha) and composition of essential oil. Calculations were performed for essential oil yield/ha only using MATMODEL VERSION 3.0 programme mode: fitting AMMI Model software (Gauch, 2007) which gives outputs of AMMI and joint regression models including analysis of variance, regression coefficients, as well as genotypes and environment mean and stability.
Fig. 1. Matamodel version 3.0 mega-environments for AMMI 1 Model, cultivars, switch points, including hypothetical winners.
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Table 2 Genotype/cultivar means for AMMI I and genotype IPCA Axis 1 score for Model AMMI I. Name of the cultivars
Mean
Count
Index
Name
Mean
Count
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
90.35 95.18 92.42 96.07 84.43 95.70 89.95 92.85 88.41 76.54
3 3 3 3 3 3 3 3 3 3
4 6 2 8 3 1 7 9 5 10
Kalka Himalaya Kushal Sambhaw Sakshham Kosi CIMAP Saryu Damroo MAS-1 Gomti
96.07 95.70 95.18 92.85 92.42 90.35 89.95 88.91 84.43 76.54
3 3 3 3 3 3 3 3 3 3
Name of the cultivars
Score
Index
Name
Score
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
5.03 3.70 1.28 0.15 −2.10 −3.00 −6.05 −2.84 0.46 3.37
1 2 10 3 9 4 5 8 6 7
Kosi Kushal Gomti Sakshham Damroo Kalka MAS-1 Sambhaw Himalaya CIMAP Saryu
5.03 3.70 3.37 1.28 0.46 0.15 −2.10 −2.84 −3.00 −6.05
Grand Mean = 90.24 yield kg/ha
Table 3 Environmental means for model AMMI I and Environmental IPCA Axis 1 Scores for model AMMI I. Environments
Means
Count
Index
Name
Means
Count
EN. I (years 2005–06) EN. II (years 2006–07) EN. III (years 2007–08)
97.94 91.10 81.68
10 10 10
1 2 3
EN. I EN. II EN. III
97.94 91.10 81.68
10 10 10
Environments
Score
Index
Name
Score
EN. I (years 2005–06) EN. II (years 2006–07) EN. III (years 2007–08)
−8.57 4.41 4.16
2 3 1
EN. II EN. III EN. II
4.41 4.16 −8.57
Table 4 ANOVA Table for model AMMI 1. Source
df
MS
Probability
Treatments Genotypes Environments/years G×E IPCA 1 Residual Error
29 9 2 18 10 8 60
SS 64029.04 2906.36 3995.74 57126.94 36457.96 20668.98 97840.81
2207.90 322.93 1997.87 3173.72 3645.80 2583.62 1630.68
0.160 0.994 0.301 0.028* 0.027* 0.149
Total
89
161869.84
1818.76
Grand mean = 90.24 yield kg/ha. * P > 0.05, respectively. Table 5 Genotypes/cultivars mean for environment/year I. Environment/year I
AMMI I
Environment/year I
Var
Name
Count
Mean
AMMI I
Residual
Rank
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
54.61 71.17 89.31 103.18 110.60 129.37 148.94 124.63 92.42 55.13
54.95 71.14 89.17 102.46 110.14 129.15 149.47 124.85 92.67 55.35
−0.35 0.03 0.14 0.72 0.46 0.23 −0.53 −0.22 −0.25 −0.22
1 2 3 4 5 6 7 8 9 10
Environment/year I X = 97.94 AMMI I Gain = 0.00.
Index 7 6 8 5 4 9 3 2 10 1
AMMI I Cultivars
Mean
CIMAP Saryu Himalaya Sambhaw Kalka MAS-1 Damroo Sakshham Kushal Gomti Kosi
148.94 129.37 124.63 110.60 103.18 92.42 89.31 71.17 55.13 54.61
Index 7 6 8 5 4 9 3 2 10 1
Cultivars
AMMII
Saryu Himalaya Sambhaw MAS-1 Kalka Damroo Sakshham Kushal Gomti Kosi
149.47 129.14 124.85 110.14 102.46 92.67 89.17 71.14 55.35 54.95
R.K. Lal / Industrial Crops and Products 50 (2013) 176–181
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Table 6 Genotypes/cultivars mean for environment/year II. Environment/year II
AMMI I
Environment/year II
AMMI I
Var
Name
Count
Mean
AMMI I
Residual
Rank
Index
Cultivars
Mean
Index
Cultivars
AMMI I
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
96.15 113.92 105.81 133.47 98.66 94.63 37.61 70.17 79.45 81.16
113.40 112.38 98.92 97.60 76.02 83.30 64.13 81.19 91.80 92.28
−17.25 1.54 6.88 35.87* 22.64 11.34 −26.52 −11.02 −12.35 −11.12
1 2 3 4 5 6 7 8 9 10
1 2 3 4 10 9 6 8 5 7
Kalka Kushal Sakshham MAS-1 Kosi Himalaya Gomti Damroo Sambhaw CIMAP Saryu
133.47 113.92 105.81 98.66 96.15 94.63 81.16 79.45 70.17 37.61
1 2 3 4 10 9 6 8 5 7
Kosi Kushal Sakshham Kalka Gomti Damroo Himalaya Sambhaw MAS-1 Saryu
113.40 112.38 98.92 97.60 92.28 91.80 83.30 81.19 76.02 64.13
Environment/year II, X = 91.10; AMMI I, gain = 15.797. * P > 0.05, respectively. Table 7 Genotypes/cultivars mean for environment/year III. Environment/year III
AMMI I
Environment/year III
AMMI I
Var
Name
Count
Mean
AMMI I
Residual
Rank
Index
Cultivars
Mean
Index
Cultivars
AMMII
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
120.29 100.44 82.16 51.56 44.05 63.08 83.31 83.74 94.87 93.34
102.69 102.01 89.18 88.14 67.14 74.65 56.26 72.50 82.26 81.99
17.60 −1.57 −7.02 −36.59* −23.09 −11.57 27.05 11.24 12.60 11.35
1 2 3 4 5 6 7 8 9 10
1 2 9 10 8 7 3 6 4 5
Kosi Kushal Damroo Gomti Sambhaw CIMAP Saryu Sakshham Himalaya Kalka MAS-1
120.29 100.44 94.87 93.34 83.74 83.31 82.16 63.08 51.56 44.05
1 2 3 4 9 10 6 8 5 7
Kalka Himalaya Kushal Sambhaw Sakshham Kosi Saryu Damroo MAS-1 Gomti
102.69 102.01 89.18 88.14 82.26 81.99 74.65 72.50 67.14 56.26
Environment/year III, X = 81.68; AMMI I, gain = 0.00. * P > 0.05, respectively.
the above listing of data estimates. The average value of the maximum of N normal realizations is the first order statistic. This value times the standard error of the treatment means provides a typical indication of the largest upward bias present in the data, which is most likely to affect highest means (Table 8). The noise SS in the interaction can be estimated as G × E df times Error MS. Accordingly, the G × E SS contains approximately: G × E pattern 27774.69 or 48.62; G × E noise 29352.24 or 51.38%; G × E total 57126.94. Ordinarily, there is considerable selectivity, with pattern recovered mostly in early IPCA axis, and noise recovered mostly in late IPCA axis. Consequently, these estimates provide a rough guide for model diagnosis by keeping early axis that are mostly pattern and relegating the others to a discarded residual (Table 4, Figs. 1 and 2). 4. Discussion Development of stable and adaptable cultivars for yield, genotype × environment (G × E) interaction continuous to be a
challenging issue among mint plant breeders globally who conduct varietal performance field evaluation trials over years (Lin et al., 1986; Lal et al., 2000) or across diverse environments. The essential oil yield is highly influenced by environments and cultivar to cultivar in the mint crop. AMMI modal for genotype × environment interaction can improve the efficiency of related plant breeder’s progress towards selection of well adopted and stable cultivars in mint crop also. Stability performance should be considered an important aspect of yield trials over years/environments. To be of practical utility in a breeding or cultivar testing programme, both stability and yield (or any other trait) must be considered simultaneously so as to make selection of cultivars more precise and reliable. In mint crop cultivars also integration of stability of performance with yield through suitable measures like AMMI Modal reduces the effects of genotype × environment interaction and helped in selecting suitable cultivars of mint is a more refined manner. On the basis of stability statistics, the different cultivars can be classified as stable cultivar. The multivariate approach AMMI
Table 8 Values for assessing the significance of mean separations in the data estimates and scope, count first order and typical bias values in mint cultivars. Estimates
Data estimates % of GM
Unweighted grand mean without imputed data With 60 df the root error mean square With 3 replications the standard of treatment means Coefficient of variation of treatment means Standard error of difference between two treatment means With 60 df t.05 of 2.00 giving LSD.05
90.240 40.382 23.314 25.840 32.972 65.953
Scope
Count
First order
Typical bias
Cultivars within one environment/year Environment/year within Cultivars All treatments
10 3 30
1.539 0.846 2.043
35.88 19.73 47.63
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R.K. Lal / Industrial Crops and Products 50 (2013) 176–181
Fig. 2. A histogram for the AMMI1 residuals of mint cultivars.
model (more authentic approach than others), have capability to provide a broader inferences on adaptability. AMMI is decidedly superior, not for statistical reasons, but rather for plant breeding reasons. AMMI partitions the overall variations into genotype main effects, environmental main effects, and genotype × environmental interactions. These three sources of variation present plant breeders/researchers with different challenges and opportunities, so it is best to handle them separately, while still considering all three in an integrated manner. AMMI model is effective for several purposes: (i) understanding genotype × environment interaction, including identifying mega-environment, (ii) improving the accuracy of yield estimate, which increases the probability of successfully selecting genotypes with the highest yield and (iii) increasing the flexibility and efficiency of experimental designs (Finlay and Wilkinson, 1963). Ultimately, these advantages imply larger selection gains with pooled mean performance over years in mint crop breeding researches and more reliable recommendations in menthol mint breeding programme. All the ten cultivars of menthol mint have not expressed stable performance in all the three years except three cultivars-Kosi, Kushal and CIMAP Saryu. Therefore, the actual winner’s cultivars were Kosi, Kushal and CIMAP Saryu. Similar findings have been reported by Lal (2012) in lemongrass although an aromatic grass belongs to familyPoaceae. Notwithstanding the fact that the multivariate approach, the AMMI model is found suitable for partitioning the genotype × environment into the causes of variation. As a result a more inference is that only three cultivars namely, Kosi (Fig. 3), Kushal and CIMAP Saryu were found highly stable over years. These findings have been in consonance with lemongrass crop where, the AMMI model was able to clear-cut partitioning the genotype × environment into the causes of variation and selection of one stable cultivar over years (Lal, 2012). The final conclusion is that, based on the AMMI model, three cultivars namely, Kosi, Kushal and CIMAP Saryu showed the high adaptability and stability due to its ability to tolerate wide environmental conditions, temperature in different years. Therefore, these three cultivars are recommended for mint growing areas in northern Indian plains. Like menthol mint crop, the AMMI model is decidedly superior, not for statistical reasons, but rather for plant
Fig. 3. Cultivar Kosi of menthol mint.
breeding reasons to many crops worldwide for the stable cultivar/genotypes selection. References Akc¸ura, M., Kaya, Y., Taner, S., 2005. Genotype × environmental interactions and phenotypic stability analysis for grain yield of Durum wheat in the Central Anatolian region. Turkish Journal of Agriculture and Forestry 29, 369–375. Annicchiarico, P., 2002. Genotype × Environmental Interactions: Challenges and Opportunities for Plant Breeding and Cultivar Recommendations. FAO Plant Production and Protection Paper. FAO, Rome, pp. 174. Clevenger, J.F., 1928. Apparatus for the determinations of volatile oils. Journal of the American Pharmaceutical Association 17, 345. Eskridge, K.M., 1990. Selection of stable cultivars using a safety-first rule. Crop Science 30, 369–374. Finlay, K.W., Wilkinson, G.N., 1963. The analysis of adaptation in a plant-breeding programme. Australian Journal of Agricultural Research 14, 742–754. Gauch, H.G., 2007. MATMODEL Version 3.0: Open Source Software for AMMI and Related Analyses. Cornell University, Ithaca, NY (Crop and Soil Science). Kang, M.S., Pham, H.N., 1991. Simultaneous selection for yielding of stable crop genotypes. Agronomy Journal 83, 161–165. Lal, R.K., 2007. Stability and genotypes × environment interactions in fennel. Journal of Herbs, Spices and Medicinal Plants 13, 47–54. Lal, R.K., 2012. Stability for Oil yield and variety recommendations’ using AMMI (Additive Main Effects and Multiplicative interactions) model in Lemongrass (Cymbopogon species). Industrial Crops and Products 40, 296–301. Lal, R.K., Sharma, J.R., Sharma, S., 2000. Variability and stability pattern in economic traits of chamomile (Chamomila recutita). Journal of Medicinal and Aromatic Plant Sciences 22, 219–222.
R.K. Lal / Industrial Crops and Products 50 (2013) 176–181 ˛ Leeuvner, D.V., 2005. Genotypes × Environment Interactions for Sun Flower Hybrids in South Africa. University of Pretoia, Pretoria (M.Sc. Thesis). Lin, C.S., Binns, M.R., Lefkovitch, L.P., 1986. Stability analysis: where do we stand? Crop Science 26, 894–900. Purchase, J.L., 1997. Parametric Analysis to Describe Genotype × Environment Interaction and Yield Stability in Winter Wheat. University of Free State, Bloemfontein (Ph.D. Thesis).
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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. Zeitschrift fur Pflanzenzuchtung 47, 92–96. Yaseen, M., Tajuddin, A., Kumar, B., Kumar, S., 2000. Evaluation of menthol mint varieties under row spacing in north Indian plains. Journal of Medicinal and Aromatic Plant Sciences 22, 205–207.
Contents lists available at ScienceDirect
Industrial Crops and Products journal homepage: www.elsevier.com/locate/indcrop
Adaptability patterns and stable cultivar selection in menthol mint (Mentha arvensis L.) R.K. Lal ∗ CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, U.P. 226015, India
a r t i c l e
i n f o
Article history: Received 10 May 2013 Received in revised form 2 July 2013 Accepted 4 July 2013 Keywords: Adaptability Genotype × environment interaction Mentha arvensis Multiyear Stability parameters
a b s t r a c t The investigation was carried out to determine the stability and adaptability patterns of a set of ten cultivars of Mentha arvensis L. in different years in India, namely, MAS-1, Himalaya, Gomti, Sambhaw, Kalaka, Damroo, CIMAP-Saryu, Kosi, Kushal and Saksham, in a multi- year evaluation trial across three consecutive years. In the adaptation strategy the important steps here was to study/assess the performance of menthol mint varieties in multiyear trials. It was observed in this study that three mint varieties namely, Kosi, Kushal and CIMAP Saryu showed high stability for essential oil yield over years. Additive main effects and multiplicative interaction (AMMI) modal was found most efficient and practical alternative to selection of better adapted menthol mint cultivars. Based on the AMMI model, cultivars Kosi, Kushal and CIMAP Saryu expressed the high adaptability over years due to its ability to tolerate wide environmental conditions in different years/environments. © 2013 Elsevier B.V. All rights reserved.
1. Introduction Menthol mint (Mentha arvensis L.) is a genus of about 25 species of the family-Lamiaceae is widely used in the food, flavourings, pharmaceutical and cosmetic industries. In addition to being a popular flavouring for food, confectionery and cigarettes, natural menthol has a cooling, soothing effect on the skin and mucous membranes of the human body, making it a useful ingredient in pharmaceuticals and cosmetics. Worldwide, approximately 10,000 tonnes of natural menthol and 2000 tonnes of synthetic menthol are used by the pharmaceutical, cosmetic and cigarette industries every year (Yaseen et al., 2000; Annicchiarico, 2002; Lal, 2007, 2012). Until about 15 years ago, the bulk of the world’s corm mint came from Brazil and China. China and India subsequently overtook Brazil and, more recently, India has led the world in the production of this useful plant and its products (Lal et al., 2000; Yaseen et al., 2000). An adaptable and stable cultivar usually refers to a cultivars’s ability to perform consistently, across a wide range of years/environments (Annicchiarico, 2002). Several biometrical methods including univariate and multivariate ones have been developed to assess stability (Akc¸ura et al., 2005). Among them the most widely used are the regression coefficient (Finlay and Wilkinson, 1963) the environmental variance (Lin et al., 1986), the
∗ Correspondence address: Department of Genetics and Plant Breeding, India. Tel.: +91 522 2718523; fax: +91 522 2342666. E-mail addresses: [email protected], [email protected] 0926-6690/$ – see front matter © 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.indcrop.2013.07.008
Shukla’s (1972) stability variance and Wrike’s ecovalence (1962). More recently, the AMMI stability value (ASV) based on the AMMI (Additive Main Effects and Multiplicative interactions) model’s PCA1 and PCA2 (Principal Components Axis 1 and 2 respectively) scores for each cultivar/cultivar Purchase, 1997). This AVS is in effects the distance from the coordinate point to the origin in a two dimensional scatter gram of PCA 1 scores against PCA 2 scores ˛ (Leeuvner, 2005). For testing a number of cultivars of menthol mint crop in a number of years the multi-year yield trials are the most important experiments in mint breeding programme. Accordingly, effective model of statistical analysis related to multi-year trials can help plant breeders to make faster genetic improvement in a number of statistical models. Among them AMMI model was found very powerful model for the above purpose. The practical interest of combining high levels of mean yield and yield stability has led to the development of the yield reliability concept (Eskridge, 1990; Kang and Pham, 1991), where a reliable cultivar is characterized by consistently high yield of essential oil across the years/environments (Annicchiarico, 2002). The use of a yield reliability index facilitates, cultivar selection or recommendation, as the mean yield and the yield stability are combined into a unique measure of genotype merit (Annicchiarico, 2002). Studies of cultivar by environment interactions (G × E) and stability have been reported very meagre on mint crop. However, no stability and reliability studies have been performed for menthol mint cultivars and tested together in a multiyear essential oil yield trial. The objectives of present study were to evaluate the essential oil yield of ten commercial cultivars namely, Kosi, Kushal, Saksham, Kalaka, MAS-1, Himalaya, CIMAP-Saryu, Sambhaw, Damroo
R.K. Lal / Industrial Crops and Products 50 (2013) 176–181
177
Table 1 Morphological characters and composition of essential oil of menthol mint cultivars. S. No. Cultivars
1. 2. 3. 4. 5. 6. 7. 8. 9. 10.
Morphological characters of cultivars
Kosi Kushal
Light green leaves, Bushy, thin suckers Dark green, broad leaves Erect, thick suckers, tolerate high moisture in soil Sakshham Dark green, broad leaves Erect, thick suckers, Insect resistant Kalka Light green leaves, thin suckers, susceptible to leaf spot disease MAS-1 Light green leaves, very thin suckers Dark green, broad leaves Erect, thick suckers Himalaya CIMAP Saryu Light green, leathery broad leaves, Erect, thick suckers Shambhaw Light green leaves, thin suckers Damroo Dark green, leathery broad leaves, Erect, thick suckers, stem thick Gomti Dark green, broad leaves Erect, thick suckers
Essential oil compositions (content in %) Menthol Menthone Iso-menthone Neo-menthol Menthyl acetate Pulegone
Limonene
75.76 79.04
5.77 4.69
3.25 2.45
2.16 2.22
0.06 5.01
0.12 0.07
2.48 0.69
76.92
8.68
3.05
1.92
1.81
0.11
2.12
68.12
10.46
3.45
2.05
2.67
1.47
4.52
78.21 72.31 76.14
10.18 8.74 7.09
1.90 3.26 3.71
2.02 1.98 2.44
0.35 3.16 3.39
1.52 1.51 0.31
5.40 3.46 0.92
74.12 72.71
9.08 11.69
2.99 3.34
2.41 2.39
3.92 0.01
0.12 0.85
1.49 1.80
70.84
7.77
3.32
2.12
0.08
0.58
4.57
and Gomti of menthol mint (M. arvensis L) released by CSIR-CIMAP, Lucknow (India), for commercial cultivation in different years in India and to determine their stability and reliability for cultivar recommendations. 2. Materials and methods Ten cultivars of menthol mint (M. arvensis L.), namely, Kosi, Kushal, Saksham, Kalaka, MAS-1, Himalaya, CIMAP-Saryu, Sambhaw, Damroo and Gomti only released by CSIR-Central Institute of Medicinal and Aromatic Plants, P.O. CIMAP, Lucknow, U.P. 226015, India (Table 1) for commercial cultivation were evaluated at the research farm of the Institute in the three consecutive growing years: 2005–06, 2006–07 and 2007–08 in a randomized complete block design with three replications. The suckers in pieces (size = 5 cm) were planted in 40 cm rows to rows and 5 cm pieces to pieces. The plants received normal intercultural operations, irrigation, and fertilizer applications (120 kg N, 80 kg P2 O5 , and 60 kg K2 O per hectare). Minimum and maximum night and day temperatures ranged 8–11 ◦ C to 15–17 ◦ C, respectively, during suckers planting time and from 25–30 ◦ C to 35–40 ◦ C, respectively, during harvesting time. Average rainfall during the growing season was 5–7 mm according to weather data of the Metrological Laboratory of CSIR-CIMAP, Lucknow, India. Essential oil was done in fresh herbs by hydro-distillation using Clevenger type apparatus (Clevenger, 1928). The oil composition was analyzed by GC using Varian CX-3400 instrument employing 30 m × 0.25 m SUPELCOWAX-10 capillary columns with temperature programme from 50–220 ◦ C @ 6◦ /m, initial and final temperature holds of 2 and 5 min, respectively. H2 used as carrier gas at 1 ml/min. Data were processed on AIMIL chromatography data system. Identification of constitutes based on retention data of reference compounds.
3. Results The wide variation recorded for morphological characters in different cultivars of menthol mint (Table 1). The differences in rank of cultivars in the different years/environments indicated the presence of genotype and environment (G × E) interactions (Tables 2–4). After meticulous study of Tables 5–7, some interesting findings comes out regarding the winners for examples AMMI F and AMMI I picked the same winners in year 2nd (66.67%) but they picked different winner in the year 1st (33.33%). AMMI F were ranking more to be trusted, the average loss from selecting AMMI I winners should be 12.44 or 13.79% of the grand mean. AMMI I were ranking more to be trusted, the average gain from selecting AMMI I winners would be 5.27 or 5.84 percent of the grand mean. The largest AMMI I gain of 15.80 or 17.51 percent of the grand mean occurs in the year 2nd where AMMI F picks cultivar Sambhaw but AMMI I picks cultivar Kosi instead. The values presented in Table 8 may be useful for assessing the significance of mean separations in
2.1. Statistical analysis Observations were recorded on each cultivar for the most important economic traits: essential oil yield (kg/ha) and composition of essential oil. Calculations were performed for essential oil yield/ha only using MATMODEL VERSION 3.0 programme mode: fitting AMMI Model software (Gauch, 2007) which gives outputs of AMMI and joint regression models including analysis of variance, regression coefficients, as well as genotypes and environment mean and stability.
Fig. 1. Matamodel version 3.0 mega-environments for AMMI 1 Model, cultivars, switch points, including hypothetical winners.
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Table 2 Genotype/cultivar means for AMMI I and genotype IPCA Axis 1 score for Model AMMI I. Name of the cultivars
Mean
Count
Index
Name
Mean
Count
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
90.35 95.18 92.42 96.07 84.43 95.70 89.95 92.85 88.41 76.54
3 3 3 3 3 3 3 3 3 3
4 6 2 8 3 1 7 9 5 10
Kalka Himalaya Kushal Sambhaw Sakshham Kosi CIMAP Saryu Damroo MAS-1 Gomti
96.07 95.70 95.18 92.85 92.42 90.35 89.95 88.91 84.43 76.54
3 3 3 3 3 3 3 3 3 3
Name of the cultivars
Score
Index
Name
Score
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
5.03 3.70 1.28 0.15 −2.10 −3.00 −6.05 −2.84 0.46 3.37
1 2 10 3 9 4 5 8 6 7
Kosi Kushal Gomti Sakshham Damroo Kalka MAS-1 Sambhaw Himalaya CIMAP Saryu
5.03 3.70 3.37 1.28 0.46 0.15 −2.10 −2.84 −3.00 −6.05
Grand Mean = 90.24 yield kg/ha
Table 3 Environmental means for model AMMI I and Environmental IPCA Axis 1 Scores for model AMMI I. Environments
Means
Count
Index
Name
Means
Count
EN. I (years 2005–06) EN. II (years 2006–07) EN. III (years 2007–08)
97.94 91.10 81.68
10 10 10
1 2 3
EN. I EN. II EN. III
97.94 91.10 81.68
10 10 10
Environments
Score
Index
Name
Score
EN. I (years 2005–06) EN. II (years 2006–07) EN. III (years 2007–08)
−8.57 4.41 4.16
2 3 1
EN. II EN. III EN. II
4.41 4.16 −8.57
Table 4 ANOVA Table for model AMMI 1. Source
df
MS
Probability
Treatments Genotypes Environments/years G×E IPCA 1 Residual Error
29 9 2 18 10 8 60
SS 64029.04 2906.36 3995.74 57126.94 36457.96 20668.98 97840.81
2207.90 322.93 1997.87 3173.72 3645.80 2583.62 1630.68
0.160 0.994 0.301 0.028* 0.027* 0.149
Total
89
161869.84
1818.76
Grand mean = 90.24 yield kg/ha. * P > 0.05, respectively. Table 5 Genotypes/cultivars mean for environment/year I. Environment/year I
AMMI I
Environment/year I
Var
Name
Count
Mean
AMMI I
Residual
Rank
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
54.61 71.17 89.31 103.18 110.60 129.37 148.94 124.63 92.42 55.13
54.95 71.14 89.17 102.46 110.14 129.15 149.47 124.85 92.67 55.35
−0.35 0.03 0.14 0.72 0.46 0.23 −0.53 −0.22 −0.25 −0.22
1 2 3 4 5 6 7 8 9 10
Environment/year I X = 97.94 AMMI I Gain = 0.00.
Index 7 6 8 5 4 9 3 2 10 1
AMMI I Cultivars
Mean
CIMAP Saryu Himalaya Sambhaw Kalka MAS-1 Damroo Sakshham Kushal Gomti Kosi
148.94 129.37 124.63 110.60 103.18 92.42 89.31 71.17 55.13 54.61
Index 7 6 8 5 4 9 3 2 10 1
Cultivars
AMMII
Saryu Himalaya Sambhaw MAS-1 Kalka Damroo Sakshham Kushal Gomti Kosi
149.47 129.14 124.85 110.14 102.46 92.67 89.17 71.14 55.35 54.95
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Table 6 Genotypes/cultivars mean for environment/year II. Environment/year II
AMMI I
Environment/year II
AMMI I
Var
Name
Count
Mean
AMMI I
Residual
Rank
Index
Cultivars
Mean
Index
Cultivars
AMMI I
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
96.15 113.92 105.81 133.47 98.66 94.63 37.61 70.17 79.45 81.16
113.40 112.38 98.92 97.60 76.02 83.30 64.13 81.19 91.80 92.28
−17.25 1.54 6.88 35.87* 22.64 11.34 −26.52 −11.02 −12.35 −11.12
1 2 3 4 5 6 7 8 9 10
1 2 3 4 10 9 6 8 5 7
Kalka Kushal Sakshham MAS-1 Kosi Himalaya Gomti Damroo Sambhaw CIMAP Saryu
133.47 113.92 105.81 98.66 96.15 94.63 81.16 79.45 70.17 37.61
1 2 3 4 10 9 6 8 5 7
Kosi Kushal Sakshham Kalka Gomti Damroo Himalaya Sambhaw MAS-1 Saryu
113.40 112.38 98.92 97.60 92.28 91.80 83.30 81.19 76.02 64.13
Environment/year II, X = 91.10; AMMI I, gain = 15.797. * P > 0.05, respectively. Table 7 Genotypes/cultivars mean for environment/year III. Environment/year III
AMMI I
Environment/year III
AMMI I
Var
Name
Count
Mean
AMMI I
Residual
Rank
Index
Cultivars
Mean
Index
Cultivars
AMMII
1 2 3 4 5 6 7 8 9 10
Kosi Kushal Sakshham Kalka MAS-1 Himalaya CIMAP Saryu Sambhaw Damroo Gomti
3 3 3 3 3 3 3 3 3 3
120.29 100.44 82.16 51.56 44.05 63.08 83.31 83.74 94.87 93.34
102.69 102.01 89.18 88.14 67.14 74.65 56.26 72.50 82.26 81.99
17.60 −1.57 −7.02 −36.59* −23.09 −11.57 27.05 11.24 12.60 11.35
1 2 3 4 5 6 7 8 9 10
1 2 9 10 8 7 3 6 4 5
Kosi Kushal Damroo Gomti Sambhaw CIMAP Saryu Sakshham Himalaya Kalka MAS-1
120.29 100.44 94.87 93.34 83.74 83.31 82.16 63.08 51.56 44.05
1 2 3 4 9 10 6 8 5 7
Kalka Himalaya Kushal Sambhaw Sakshham Kosi Saryu Damroo MAS-1 Gomti
102.69 102.01 89.18 88.14 82.26 81.99 74.65 72.50 67.14 56.26
Environment/year III, X = 81.68; AMMI I, gain = 0.00. * P > 0.05, respectively.
the above listing of data estimates. The average value of the maximum of N normal realizations is the first order statistic. This value times the standard error of the treatment means provides a typical indication of the largest upward bias present in the data, which is most likely to affect highest means (Table 8). The noise SS in the interaction can be estimated as G × E df times Error MS. Accordingly, the G × E SS contains approximately: G × E pattern 27774.69 or 48.62; G × E noise 29352.24 or 51.38%; G × E total 57126.94. Ordinarily, there is considerable selectivity, with pattern recovered mostly in early IPCA axis, and noise recovered mostly in late IPCA axis. Consequently, these estimates provide a rough guide for model diagnosis by keeping early axis that are mostly pattern and relegating the others to a discarded residual (Table 4, Figs. 1 and 2). 4. Discussion Development of stable and adaptable cultivars for yield, genotype × environment (G × E) interaction continuous to be a
challenging issue among mint plant breeders globally who conduct varietal performance field evaluation trials over years (Lin et al., 1986; Lal et al., 2000) or across diverse environments. The essential oil yield is highly influenced by environments and cultivar to cultivar in the mint crop. AMMI modal for genotype × environment interaction can improve the efficiency of related plant breeder’s progress towards selection of well adopted and stable cultivars in mint crop also. Stability performance should be considered an important aspect of yield trials over years/environments. To be of practical utility in a breeding or cultivar testing programme, both stability and yield (or any other trait) must be considered simultaneously so as to make selection of cultivars more precise and reliable. In mint crop cultivars also integration of stability of performance with yield through suitable measures like AMMI Modal reduces the effects of genotype × environment interaction and helped in selecting suitable cultivars of mint is a more refined manner. On the basis of stability statistics, the different cultivars can be classified as stable cultivar. The multivariate approach AMMI
Table 8 Values for assessing the significance of mean separations in the data estimates and scope, count first order and typical bias values in mint cultivars. Estimates
Data estimates % of GM
Unweighted grand mean without imputed data With 60 df the root error mean square With 3 replications the standard of treatment means Coefficient of variation of treatment means Standard error of difference between two treatment means With 60 df t.05 of 2.00 giving LSD.05
90.240 40.382 23.314 25.840 32.972 65.953
Scope
Count
First order
Typical bias
Cultivars within one environment/year Environment/year within Cultivars All treatments
10 3 30
1.539 0.846 2.043
35.88 19.73 47.63
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Fig. 2. A histogram for the AMMI1 residuals of mint cultivars.
model (more authentic approach than others), have capability to provide a broader inferences on adaptability. AMMI is decidedly superior, not for statistical reasons, but rather for plant breeding reasons. AMMI partitions the overall variations into genotype main effects, environmental main effects, and genotype × environmental interactions. These three sources of variation present plant breeders/researchers with different challenges and opportunities, so it is best to handle them separately, while still considering all three in an integrated manner. AMMI model is effective for several purposes: (i) understanding genotype × environment interaction, including identifying mega-environment, (ii) improving the accuracy of yield estimate, which increases the probability of successfully selecting genotypes with the highest yield and (iii) increasing the flexibility and efficiency of experimental designs (Finlay and Wilkinson, 1963). Ultimately, these advantages imply larger selection gains with pooled mean performance over years in mint crop breeding researches and more reliable recommendations in menthol mint breeding programme. All the ten cultivars of menthol mint have not expressed stable performance in all the three years except three cultivars-Kosi, Kushal and CIMAP Saryu. Therefore, the actual winner’s cultivars were Kosi, Kushal and CIMAP Saryu. Similar findings have been reported by Lal (2012) in lemongrass although an aromatic grass belongs to familyPoaceae. Notwithstanding the fact that the multivariate approach, the AMMI model is found suitable for partitioning the genotype × environment into the causes of variation. As a result a more inference is that only three cultivars namely, Kosi (Fig. 3), Kushal and CIMAP Saryu were found highly stable over years. These findings have been in consonance with lemongrass crop where, the AMMI model was able to clear-cut partitioning the genotype × environment into the causes of variation and selection of one stable cultivar over years (Lal, 2012). The final conclusion is that, based on the AMMI model, three cultivars namely, Kosi, Kushal and CIMAP Saryu showed the high adaptability and stability due to its ability to tolerate wide environmental conditions, temperature in different years. Therefore, these three cultivars are recommended for mint growing areas in northern Indian plains. Like menthol mint crop, the AMMI model is decidedly superior, not for statistical reasons, but rather for plant
Fig. 3. Cultivar Kosi of menthol mint.
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