Morphological Assessment of Rose Species and Variants Using

International Journal of Chemical Studies 2018; 6(2): 3277-3282

Abhay Kumar Gaurav Abhay Kumar Gaurav, Namita, DVS Raju, Markandey Singh, Sapna ICAR-Indian Agricultural Panwar and Gaurav Kumar Vani Research Institute, New Delhi, India Abstract Namita The present study was done to evaluate thirty-one rose species and cultivars based on morphological ICAR-Indian Agricultural characters. India is a hotspot of wild rose species, major being R. brunonii, R. moschata, R. multiflora Research Institute, New Delhi, and R. cathayensis R. macrophylla, R. webbiana). Every species has some of the special traits which can India be used for development of new cultivars suitable for specific purposes. Morphological data were recorded as per PPV& FRA guidelines and principal component analysis was done based on score data. DVS Raju It extracts all important variables in the form of different components. Major variables observed during ICAR-DFR, Pune, Maharashtra, India assessment were plant growth habit, the shape of prickles, leaflet shape and size, leaf serration and shape of stipules. All five components were named after observing the variables of the particular component. Markandey Singh PCA biplot was constructed between different components, species having positive value on both X and ICAR-Indian Agricultural Y axis were recommended as suitable for a particular purpose. Some species such as R. banksiae, R. Research Institute, New Delhi, macrophylla, R. odorata, R. tomentosa, R. glutinosa, R. multiflora, Rose Sherbat and Dr Huey were India found to be suitable for breeding cultivars having better water use efficiency, radiation use efficiency and growth dimension. Sapna Panwar ICAR-Indian Agricultural Keywords: rose, multivariate analysis, PCA, wild species Research Institute, New Delhi, India Introduction Gaurav Kumar Vani Roses are one of the most beautiful creations of nature. They are grown all around the world JNKVV, Jabalpur, Madhya for their beautiful flowers. It belongs to family Rosaceae which include approximately 120 Pradesh, India species distributed in the Northern Hemisphere (Wissemann, 2003) [14]. Striking feature of rose diversity is the availability of variation in almost all visible morphological characters.

Diversity can be observed with respect to growth habit, plant spread, leaf type, leaf shape, leaf colour, stem colour, prickle characteristics (such as presence or absence, curvature, colour, density etc.), stipule, floral characteristics (Colour, fragrance, number of petals etc.). Asia is one of the major gene centres where the majority of the wild rose species are found. India is also a hotspot for roses (Duthie, 1971; Bamber, 1976; Hooker, 1978, Tejaswini, and Prakash, [4, 2, 13] 2005) , with as many as sixteen species and four hybrid species has been reported to be growing wild in various phytogeographical zones of India (Pal, 1966; Rathore and Umesh, 1992) [6, 7]. Western Himalaya leads with six wild species viz. R. brunonii, R. moschata, R. multiflora and R. cathayensis R. macrophylla and R. webbiana (Singh et al., 2017) [12]. This wealth of indigenous germplasm is important source of many important traits such as perpetual

flowering, winter hardiness fragrance, colour, thornlessness, scented foliage etc. Many wild species have been evolved to survive under abiotic stresses such as droughts, extreme heat and cold and biotic stresses such as insects, pests, and diseases (Tejaswini, and Prakash, 2005) [13]. These germplasm need to protect from the untimely loss and have to evaluate in order to utilized in rose breeding programs. Native species such as Rosa brunonii, R. macrophylla, R. moschata, R. spinossisima, R. rubiginosa, R. wichuraiana can help in breeding new cultivars

suitable for local agro-ecological conditions. The present work was done to study to evaluate rose species and cultivars for their usefulness in the breeding program based on morphological traits.

Correspondence Abhay Kumar Gaurav Materials and Methods ICAR-Indian Agricultural Thirty-one rose species and cultivars were collected from ICAR-IARI, New Delhi, ICAR- Research Institute, New Delhi, NBPGR, Regional Station, Shimla, and ICAR-IARI, Regional Station Katrain, (Table 1). India Twenty-one species, five cultivar and five wild species of unknown origin were collected. ~ 3277 ~ International Journal of Chemical Studies

The observations were recorded for eighteen vegetative some variables (Four) were uniform throughout the characters. Traits assessed in the study were; plant growth genotypes, they were not included for further analysis; only habit, anthocyanin coloration of young shoots and their hue, fourteen sets of the variable were used for Principal presence or absence of prickles, its colour, curvature, leaf components analysis (Revelle, 2017) [8]. It extracts all colour, glossiness of adaxial surface, leaf pubescence, leaflet important variables in the form of different components. All serration of margin, terminal leaflet: length and breadth, the variables of a component was reinterpreted and remaining terminal leaflet: shape of the blade, tip, and base and type of the categories was done logically to keep focus on research stipule. As most of the species didn’t flower at the place of (Coolen, 2008; Sharma, 2014) [3, 11]. Here the loading value of work, floral data were not recorded. Scoring was done as per first five components was further analyzed. Any variables Rose DUS guidelines given (Authority, P.P.V.F.R., 2012) [1]. having value more than 0.5 is good enough to explain For the characters which were not included in PPV&FRA, diversity in a component. Based on loading value in each such as presence or absence of prickles on the shoot, the component, a variable having value ≥0.5 were selected and a shape of terminal leaflet blade and type of stipule, a scoring remaining of component was done. PCA was plotted between pattern was created similar to DUS guidelines (Rathore and two components; component 1 vs component 2, component 2 Umesh, 1992) [7] and further analysis was done (Table 2). As vs. component 3 and so on.

Table 1: List of rose genotypes used for morphological characterization

S. No Species name Accession no./ Identification no Source 1 Rosa nitida × R. rugosa EC 035571 ICAR-IARI, New Delhi 2 R. slancensis EC 037349 ICAR-IARI, New Delhi 3 R. indica major EC 129073 ICAR-IARI, New Delhi 4 R. macrophylla IC 564816 ICAR-IARI, New Delhi 5 R. brunonii IC 564794 ICAR-IARI, New Delhi 6 R. wichuraiana EC 033173 ICAR-IARI, New Delhi 7 R. moschata EC 018586 ICAR-IARI, New Delhi 8 R. tomentosa EC 032911 ICAR-IARI, New Delhi 9 R. dumalis EC025995 ICAR-IARI, New Delhi 10 R. multiflora EC032219 ICAR-IARI, New Delhi 11 R. glutinosa EC 025999 ICAR-IARI, New Delhi 12 R. damascena EC025987 ICAR-IARI, New Delhi 13 R. bourboniana IC010649 ICAR-IARI, New Delhi 14 R. chinensis viridiflora FLS-IARI/P10/B15-1 ICAR-IARI, New Delhi 15 R. indica var. odorata FLS-IARI/MB10-A ICAR-IARI, New Delhi 16 R. banksiae IW004421 ICAR-IARI, R.S, Katrain 17 R. rubiginosa EC026371 ICAR-NBPGR, R.S, Shimla 18 Rosa sps. FLS-P8/B19-2 ICAR-NBPGR, R.S, Shimla 19 R. inodora EC025783 ICAR-NBPGR, R.S, Shimla 20 R. spinossisima EC032847 ICAR-NBPGR, R.S, Shimla 21 R. rubrifolia EC032417 ICAR-NBPGR, R.S, Shimla 22 Jwala FLS-P10/B19-1 ICAR-IARI, New Delhi 23 Himroz FLS-P9/B19-1 ICAR-IARI, New Delhi 24 Rani Sahiba FLS-P8/B19-1 ICAR-IARI, New Delhi 25 Rose Sherbat FLS-IARI/1B/R3-C4 ICAR-IARI, New Delhi 26 Dr Huey FLS-P11/B19-3 ICAR-IARI, New Delhi 27 Wild Species 1 FLS/2016/RW1 ICAR-IARI, R.S, Katrain 28 Wild Species 2 FLS/2016/RW2 ICAR-IARI, R.S, Katrain 29 Wild Species 3 FLS/2016/RW3 ICAR-IARI, R.S, Katrain 30 Wild Species 4 FLS/2016/RW4 ICAR-IARI, R.S, Katrain 31 Wild Species 5 FLS/2016/RW5 ICAR-IARI, R.S, Katrain

Results and Discussion five variable had loading value of ≥0.5. They are- young Based on morphological traits, it was inferred that high shoot: anthocyanin colouration, young shoot: hue of variation is available in genus Rosa. Variations were noticed anthocyanin colouration, prickles on stem: present/absent, for almost all important vegetative characters. The prickles: predominant colour and leaflet serration of margin. morphological traits which differentiate species and cultivars After observing these characters, we named this component 1 into distinct groups are plant growth habit, the shape of as Water use efficiency (WUE). In the second component, prickles, leaflet shape and size, leaf serration and shape of three variable had loading value of ≥0.5; plant growth habit, stipules. Principal component analysis (PCA) was used to shape of the lower side of prickle and type of stipule. We identify multidimensional relationships among various traits named this second component as growth dimension after for grouping species. It extracts all important variables in the observing these 3 characters. The third component was named form of different components from a large set of variables photosynthetic assimilation as the variable (traits) having available in a dataset and presents them in more interpretable loading value of ≥0.5 were related to leaf (Length and breadth form. Principle components altogether explained 100% of the of the terminal leaflet and its shape of base). In fourth accumulated variables (Yoshioka, 2004) [15]. PCA was carried principal component, only two variable had loading value of out on 14 traits of all the species, the first five principal ≥0.5, prickles colour and leaf glossiness of upper side. Based components captured 70% of the variability. In component 1, on both traits, this component was named as heat tolerance.

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The fifth component was named as radiation use efficiency (Radiation use efficiency) (Fig. 3 & 4). These three after analyzing as two variables namely shape of blade and tip components were interrelated hence, in the PCA biplot, all of terminal leaflet had loading value of ≥0.5 (Table 3). PCA species got clustered into one group only (Positive X and Y biplot was constructed using loading value of each axis). It has been hypothesized that leaves having serrated component. Each species is represented as a point in margins are more active than entire leaves in terms of the biplot. All species were grouped in four clusters in biplot. photosynthesis and transpiration besides having a higher One cluster will depict species having positive values on both surface area resulting in higher accumulation of photosynthate axes (+X and +Y), another two will depict species having with better radiation use efficiency (Royer and Wilf, 2006; positive value for one component and one negative Semchenko and Zobel, 2007) [9, 10]. Hence, species R. component or vice-versa (+X & -Y or, -X & +Y), while the tomentosa, R. glutinosa, R. multiflora and Rose Sherbat can fourth cluster will depict species having negative values for be used for breeding cultivars for an area having higher light both axes (-X and -Y). intensity. We also plotted PCA between component 1 (Water The first biplot was constructed between component 1 (Water use efficiency) and component 5 (Radiation use efficiency) in use efficiency) and component 2 (Growth dimension) (Fig. 1). order to select species and cultivars having higher water and As mentioned earlier species were grouped into four clusters. radiation use efficiency (Fig. 5). Any species having this two When we need to select any species or breed cultivars having quality will be of paramount importance due to declining quality like higher water use efficiency with better growth, we water resources and increasing incoming solar radiations. Dr can use species from the cluster showing positive value for Huey, Rosa glutinosa, wild species 1, wild species 2, Rose both components (X-axis and Y-axis). Following species are Sherbat, and R. spinossisima are some of the species and most suitable for this purpose: R. nitida X R. rugosa, R. cultivars which can be used for breeding new cultivars with banksiae, R. macrophylla, R. odorata, R. indica major, R. water and radiation use efficiency. Most of the wild species wichuriana, R. multiflora, R. tomentosa, R. chinensis grown for their ornamental purposes only in certain places, ‘Viridiflora’, R. spinossisima, Dr. Huey, wild species 2, wild but Tejaswini, and Prakash, 2005 [13] reported that R. species 3 and wild species 5. Species having higher positive multiflora, R. odorata and R. bourboniana, are more widely values (such as R. banksiae, R. nitida × R. rugosa, R. distributed in India as they are used as rootstocks. macrophylla, and R. odorata) on both axes can be used donor parent for these two traits. As anthocyanin pigments are water Conclusion soluble and act as an antioxidant thereby protecting plants In India, there is no dearth of wild rose germplasm, a large no from various abiotic stresses and delaying leaf senescence of species are growing in wild. Many of these wild species ((Landi et al., 2015) [5]. The second biplot was constructed have been evolved to survive severe droughts, extreme heat between component 2 (Growth dimension) and component 3 and cold and other biotic stresses. This germplasm have been (Photosynthetic assimilation) (Fig. 2). Species having better evaluated for various morphological traits and multivariate growth dimension with higher photosynthetic assimilation as analysis was done. Few species such as R. banksiae, R. nitida depicted by higher values both X and Y axis is R. slancensis, × R. rugosa, R. macrophylla, R. odorata, R. tomentosa, R. R. nitida × R. rugosa, R. macrophylla, R. banksiae and R. glutinosa, R. multiflora, Rose Sherbat and Dr Huey were odorata and hence can be used donor parent for these two found to be suitable for breeding cultivars with good water traits. The third biplot was constructed between component 3 use efficiency, radiation use efficiency with better growth (Photosynthetic assimilation) and component 4 (Heat dimension. These wild roses can be used in various breeding tolerance). Similarly, fourth biplot was also constructed programmes owing to the great level of diversity for between component 4 (Heat tolerance) and component 5 morphological characters.

Table 3: Loading value of five components of Principal component analysis using morphological traits and named assigned to a particular group as per the variables observed in each component

Growth Photosynthetic Heat Radiation use Traits Water-Use Efficiency dimension assimilation Tolerance efficiency Plant growth habit -0.138 0.729 0.03 -0.319 0.115 Young shoot: Anthocyanin colouration 0.793 -0.040 0.112 0.010 0.070 Young shoot: Hue of anthocyanin colouration 0.793 -0.205 -0.178 0.050 -0.106 Prickles on stem: Present/Absent -0.584 -0.469 0.184 -0.030 -0.421 Prickles: Predominant colour 0.56 0.050 0.080 0.514 0.040 Prickles: Shape of lower side 0.010 0.502 -0.070 0.325 0.221 Leaf glossiness of upper side -0.070 -0.13 0.010 0.783 0.090 Leaflet serration of margin -0.696 -0.184 0.080 0.302 0.314 Terminal leaflet: length (cm) 0.090 0.468 0.708 0.385 -0.204 Terminal leaflet: breadth (cm) -0.070 -0.070 0.919 0.00 0.117 Terminal leaflet: Shape of blade 0.115 -0.378 0.306 -0.474 0.564 Terminal leaflet: shape of the tip 0.118 -0.199 -0.07 -0.153 -0.808 Terminal leaflet: shape of base -0.100 -0.361 0.612 -0.394 0.184 Type of stipule 0.05 0.804 -0.03 -0.01 -0.06

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Fig 1: PCA biplot constructed between component 1 (Water use efficiency) and component 2 (Growth dimension)

Fig 2: PCA biplot constructed between component 2 (Growth dimension) and component 3 (Photosynthetic assimilation)

Fig 3: PCA biplot constructed between component 3 (Photosynthetic assimilation) and component 4 (Heat tolerance) ~ 3280 ~ International Journal of Chemical Studies

Fig 4: PCA biplot constructed between component 4 (Heat tolerance) and component 5 (Radiation use efficiency)

Fig 5: PCA biplot constructed between component 1 (Water use efficiency) and component 5 (Radiation use efficiency)

Table 2: DUS Scores of 31 rose species as per PPV &FRA guidelines. Details are given below

Characters 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Species Rosa nitida × R rugusa 7 9 5 3 3 3 3 5 4.1 2.2 3 2 2 3 R. slancensis 5 1 1 5 4 3 5 5 6.6 3.1 1 2 2 3 R. indica major 7 9 3 5 4 3 3 5 6 2.7 5 1 2 1 R. macrophylla 5 9 5 5 4 3 3 3 5.9 2.8 1 2 2 3 R. brunonii 3 9 7 5 4 1 1 3 4.2 3.1 7 4 3 1 R. wichuraina 7 9 5 5 2 1 1 5 4.1 2.7 5 2 2 3 R. moschata 3 9 7 5 4 1 3 3 4 2.2 3 1 3 1 R. tomentosa 3 9 5 5 4 3 5 5 6.5 2.9 5 2 2 3 R. dumalis 3 9 7 5 4 1 3 3 4.3 2.7 9 4 3 1 R. multiflora 5 9 5 3 4 1 5 5 4.9 2.9 5 2 2 3 R. glutinosa 1 9 7 5 4 3 5 7 3.7 2.6 7 1 3 1 R. chinensis viridiflora 3 9 3 5 4 3 3 5 5 2.6 1 2 2 1 R. bourboniana 3 1 1 5 4 3 3 7 4.1 3.2 7 1 2 1 R. damascena 3 9 1 7 2 1 3 5 6.5 4.4 5 1 3 1 R. odorata 5 9 3 5 5 3 5 5 5.6 2.6 1 2 2 3 R. banksiae 7 9 7 1 4 3 3 3 5.1 1.45 1 2 1 5 ~ 3281 ~ International Journal of Chemical Studies

R. rubignosa 3 1 5 7 2 1 5 7 4 2.6 3 3 2 1 Rosa sp. 7 9 3 5 2 3 5 5 4.6 2.5 7 1 3 3 R. inodora 3 1 1 7 2 1 3 5 2.3 1.2 3 2 2 1 R. spinossisima 3 9 5 3 4 1 3 3 3.1 1.6 5 1 2 3 R. rubrifolia 5 9 5 7 4 1 7 7 3.2 1.6 3 2 2 1 Jwala 3 9 5 5 3 3 3 3 5.1 2.5 5 2 2 1 Himroz 5 9 3 7 4 1 3 5 4.5 3 3 4 3 1 Rani Sahiba 5 9 3 5 3 1 3 5 4.2 2.9 7 1 3 1 Rose Sherbat 1 9 5 3 4 1 5 7 5.4 3.6 5 1 3 1 Dr. Huey 7 9 3 3 4 3 3 5 3.8 3.4 7 1 2 1 Wild Species 1 3 9 5 3 4 1 5 3 4.8 2.8 7 1 2 1 Wild Species 2 7 9 5 5 4 3 3 5 4.4 3 7 1 3 1 Wild Species 3 5 9 7 5 4 1 5 3 5.6 3.2 5 1 3 3 Wild Species 4 9 1 1 5 3 1 3 7 5.5 3.2 7 1 4 5 Wild Species 5 5 9 7 5 4 1 7 5 6.1 2.7 3 2 2 3

Note: Morphological traits and their score. 7. Rathore DS, Umesh C. Rosa species (A bulletin). 1. Plant growth habit: (Upright-1, Semi-upright-3, National Bureau of Plant Genetic Resources; New Delhi, Intermediate-5, Moderately spreading-7, Strongly 1992. Spreading-9) 8. Revelle W. Psych: Procedures for Personality and 2. Young shoot: Anthocyanin colouration (Absent-1, Psychological Research, Northwestern University, Present-9) Evanston, Illinois, USA, 2017; Version = 1.7.8. 3. Young shoot: Hue of anthocyanin colouration (Very 9. Royer DL, Wilf P. Why do toothed leaves correlate with weak-1, Weak-3, Medium-, Strong-7, Very strong-9) cold climates? Gas exchange at leaf margins provides 4. Prickles on stem: (Absent-1, Few-3, Medium-5, Many-7) new insights into a classic paleotemperature proxy. 5. Prickles: Predominant colour (Greenish-1, Yellowish-2, International Journal of Plant Sciences. 2006; 167:11-8. Reddish-3, Brown-4, Purplish-5) 10. Semchenko M, Zobel K. The role of leaf lobation in 6. Prickles: Shape of lower side (Deep concave-1, Concave- elongation responses to shade in the rosette-forming forb 3, Flat-5, Convex-7, High convex-9) Serratula tinctoria (Asteraceae). Annals of botany. 2007; 7. Leaf glossiness of upper side (Absent-1, Weak-3, 100:83-90. Medium-, Strong-7) 11. Sharma S. (Ed.). Governometrics and technological 8. Leaflet serration of margin (Absent-1, Fine-3, Medium-5, innovation for public policy design and precision. IGI Dense-7) Global, 2014. 9. Terminal leaflet: length (cm) 12. Singh S, Dhyani D, Nag A, Sharma RK. Morphological 10. Terminal leaflet: breadth (cm) and molecular characterization revealed high species- 11. Terminal leaflet: Shape of blade (Lanceolate-1, Elliptic- level diversity among cultivated, introduced and wild 3, Ovate-5, Broadly ovate-7) roses (Rosa sp.) of western Himalayan region. Genetic 12. Terminal leaflet: shape of the tip (Acuminate-1, Acute-2, Resources and Crop Evolution. 2017; 64(3):515-530. Obtuse-3, Rounded-4) 13. Tejaswini, Prakash MS. Utilization of wild rose species 13. Terminal leaflet: shape of base (Acute-1, Obtuse-2, in India. Acta Hortic. 2005; 690:91-96. Rounded-3, Cordate-4) 14. Wissemann V. Conventional taxonomy of wild roses. In: 14. Type of stipule (Clasped-1, Winged-3, Rudimentary-5, Encyclopedia of rose science (Roberts A, Debener T, and Fish tail-7) Gudin S, eds). London: Academic Press. 2003; 111-117. 15. Yoshioka Y, Iwata H, Ohsawa R, Ninomiya S. Acknowledgement Quantitative evaluation of flower colour pattern by image The first author is thankful to UGC for the fellowship analysis and principal component analysis of Primula provided during the tenure of study. sieboldii E. Morren. Euphytica. 2004; 139(3):179-186.

References 1. Authority PPVFR. Protection of Plant Varieties & Farmers, Rights Authority. 2013. Plant Variety Journal of India. 2012; 7(8):34-49. 2. Bamber CJ. Plants of the Punjab, North West Frontier, Province and Kashmir, Bishen Singh, Dehradun, India, 1976. 3. Coolen H. The meaning of dwelling features. Conceptual and methodological issues. 2008; 164. 4. Duthie JF. Flora of the Upper Gangetic Plain and of the Adjacent Siwalik and sub-Himalayan Tracts. International Book Distributors, 1971; 1:327-328. 5. Landi M, Tattini M, Kevin S Gould. Multiple functional roles of anthocyanins in plant-environment interactions. Environmental and Experimental Botany. 2015; 119:4- 17. 6. Pal BP. The Rose in India. The Rose in India, 1966.

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