Applying Dickson Quality Index, Chlorophyll Fluorescence, and Leaf Area Index for Assessing Plant Quality of Pentas lanceolata

Authors

  • Kuan-Hung LIN 1) Ton Duc Thang University, Faculty of Applied Sciences, Ho Chi Minh City 700000, Vietnam 2) Chinese Culture University, Department of Horticulture and Biotechnology, Taipei 114, Taiwan
  • Chun-Wei WU Kang Ning University, Center for General Education, Taipei 114, Taiwan
  • Yu-Sen CHANG National Taiwan University, Department of Horticulture and Landscape Architecture, Taipei 106, Taiwan

DOI:

https://doi.org/10.15835/nbha47111312

Keywords:

nondestructive, photosynthesis, reflectance spectroscopy, root growth potential, seedling vigor

Abstract

Plant quality greatly relates to the seedling vigor (SV), survival and growth of plants after transplantation. The objective of this study was to use the nondestructive measurements of chlorophyll fluorescence (ChlF) and leaf area index (LAI) as SV indices for star cluster (Pentas lanceolata). Plants were grown in potting soil under nature sunlight for 90 d. A total of 13 morphological and physiological parameters were selected for measurements. Among them, root growth potential (RGP) was the best predictor for SV in all tested plants. Plants were separated into 5 RGP groups based on the number of new roots, and remaining parameters were also separated into those same levels. The trends and rates of increase from levels 1 to 5 in Dickson quality index (DQI), LAI, total dry mass, and ChlF were all similar to the RGP index. Although RGP and DQI are frequently used as indices for SV, these measurements are time-consuming and require sample destruction. Consistent and strongly high correlations were observed among DQI, LAI, and ChlF, demonstrating the applicability of these indices for measuring SV in star cluster. The measurements of LAI and ChlF were predicted using multiple variables from validation datasets, and showed novel and useful parameters for examining the SV of star cluster.

References

Carter GA (1998). Reflectance wavebands and indices for remote estimation of photosynthesis and stomatal conductance in pine canopies. Remote Sensing of Environment 63:61-72.

Chiu YC, Hsu WC, Chang YC (2015). Detecting cabbage seedling diseases by using chlorophyll fluorescence. Engineering in Agriculture, Environment and Food Food 8:95-100.

Currey CJ, Hutchinson VA, Lopez RG (2012). Growth, morphology, and quality of rooted cuttings of several herbaceous annual bedding plants are influenced by photosynthetic daily light integral during root development. HortScience 47:25-30.

Davis AS, Jacobs DF (2005). Quantifying root system quality of nursery seedlings and relationship to outplanting performance. New Forests 30:295-311.

Demmig-Adams B, Adams WW, Barker DH, Logan BA, Bowlong DR, Verhoeven AS (1996). Using chlorophyll fluorescence to assess the fraction of absorbed light allocated to thermal dissipation of excess excitation. Physiologia Plantarum 98:253-264.

Devitt DA, Morris RL, Fenstermaker LK (2005). Foliar damage, spectral reflectance, and tissue ion concentrations of trees sprinkle irrigated with waters of similar salinity but different chemical composition. HortScience 40:819-826.

Dickson A, Leaf AL, Hosner JF (1960). Quality appraisal of white spruce and white pine seedling stock in nurseries. The Forestry Chronicle 36:10-13.

Dillen SY, Beeck MO, Hufkens K (2012). Seasonal patterns of foliar reflectance in relation to photosynthetic capacity and color index in two co-occurring tree species, Quercus rubra and Betula papyrifera. Agricultural and Forest Meteorology 160:60-68.

Ellison DS, Schutzki R, Pascal N, Cregg B (2016). Root growth potential, water relations and carbohydrate status of ash alternative species following pre-plant storage. Urban Forestry & Urban Greening 18:59-64.

Facchi A, Baroni G, Boschetti M, Gandolfi C (2010). Comparing optical and direct methods for leaf area index determination in a maize crop. Journal of Agricultural Engineering 41:33-40.

Fracheboud Y, Leipner J (2003). The application of chlorophyll fluorescence to study light, temperature, and drought stress. In: DeEll JR, Toivonen PM (Eds). Practical Applications of Chlorophyll Fluorescence in Plant Biology, Kluwer, Dordrecht pp 125-150.

Huang C, Zhao S, Wang L, Anjum S, Chen M, Zou C (2013). Alteration in chlorophyll fluorescence, lipid peroxidation and antioxidant enzymes activities in hybrid ramie (Boehmeria nivea L.) under drought stress. Australian Journal of Crop Science 7:594-599.

Jacobs DF, Salifu KF, Seifert JR (2005). Relative contribution of initial root and shoot morphology in predicting field performance of hardwood seedlings. New Forests 30:235-251.

Kitao M, Lei TT, Koike T, Tobita H, Maruyama Y (2006). Tradeoff between shade adaptation and mitigation of photoinhibition in leaves of Quercus mongolica and Acer mono acclimated to deep shade. Tree Physiology 26:441-448.

Kowalczyk K, Sieczko L, Goltsev V, Kalaji HM, Gajc-Wolska J, Gajewski M, … Cetner MD (2018). Relationship between chlorophyll fluorescence parameters and quality of the fresh and stored lettuce (Lactuca sativa L.). Scientia Horticulturae 235:70-77.

Laing W, Greer D, Sun O, Beets P, Lowe A, Payn T (2000). Physiological impacts of magnesium (Mg) deficiency in Pinus radiata: Growth and photosynthesis. The New Phytologist 146:47-57.

Levizou E, Drilias P, Psaras GK, Maneta Y (2005). Nondestructive assessment of leaf chemistry and physiology through spectral reflectance measurements may be misleading when changes in trichome density co-occur. New Phytologist 165:463-472.

Liu L, Yang X, Zhou H, Liu S, Zhou L, Li X, Yang J, Wu J (2018). Relationship of root zone soil moisture with solar-induced chlorophyll fluorescence and vegetation indices in winter wheat: A comparative study based on continuous ground-measurements. Ecological Indicators 90: 9-17.

Manas P, Castro E, Heras J (2009). Quality of maritime pine (Pinus pinaster Ait.) seedlings using waste materials as nursery growing media. New Forests 37:295-311.

Mattsson A (1997). Predicting field performance using seedling quality assessment. New Forests 13:227-252.

Maxwell K, Johnson GN (2000). Chlorophyll fluorescence-a practical guide. Journal of Experimental Botany 51:659-668.

Molina BR, Arellano C, Sosinski BR, Fernandez GE (2011). A protocol to assess heat tolerance in a segregating population of raspberry using chlorophyll fluorescence. Scientia Horticulturae 130:524-530.

Pollastrini M, Nogales A, Benavides R, Bonal D, Finer L, Radoglou K, Bussotti F (2017). Tree diversity affects chlorophyll a fluorescence and other leaf traits of tree species in a boreal forest. Tree Physiology 37:199-208.

Porcar CA, Pfündel E, Korhonen JF, Juurola E (2008). A new monitoring PAM fluorometer (MONI-PAM) to study the short- and long-term acclimation of photosystem II in field conditions. Photosynthesis Research 96:173-179.

Radoglou K, Raftoyannis Y (2002). The impact of storage, desiccation and planting date on seedling quality and survival of woody plant species. Forestry 75:179-190.

Raymond FK, Roger NC (1999). Spectroscopic determination of leaf biochemistry using band depth analysis of absorption features and stepwise multiple linear regression. Remote Sensing of Environment 67:267-287.

Ritchie GA, Landis TD, Dumroese RK, Haase DL (2010). Assessing plant quality. In: Landis TD, Dumroese RK, Haase DL (Eds). The container tree nursery manual. United States Department of Agriculture, Washington DC pp 17-82.

Roller KJ (1976). Field performance of container-grown Norway and black spruce seedlings. Canadian Forestry Service Department of the Environment. Information Report M-X-64. 17 p.

Scalon SP, Jeromini TS, Mussury RM, Dresch DM (2014). Photosynthetic metabolism and quality of Eugenia pyriformis Cambess. seedlings on substrate function and water levels. Anais da Academia Brasileira de Ciências 324:103-113.

Song C (2012). Optical remote sensing of forest leaf area index and biomass. Progress in Physical Geography 37:98-113.

Stone EC (1955). Poor survival and the physiological condition of planting stock. Forest Science 1:90-94.

Strachan IB, Pattey E, Boisvert JB (2002). Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance. Remote Sensing of Environment 80:213-224.

Tanaka Y, Brotherton P, Hostetter S, Chapman D, Dyce S, Belanger J, Johnson B, Duke S (1997). The operational planting stock quality testing program at Weyerhaeuser. New Forests 13:423-437.

Thompson BE (1985). Seedling morphological evaluation: what you can tell by looking. In: Duryea ML (Ed). Evaluating seedling quality: principles, procedures, and predictive abilities of major tests. Proceedings of the workshop of Forest Research Laboratory of the Oregon State University, Oregon pp 59-71.

Tsakaldimi M, Tsitsoni T, Ganatsas G, Zagas T (2009). A comparison of root architecture and shoot morphology between natural regenerated and container seedlings of Quercus ilex L. Plant and Soil 324:103-113.

Turner DP, Cohen WB, Kennedy RE (1999). Relationships between leaf area index and Landsat TM spectral vegetation indices across three temperate zone sites. Remote Sensing of Environment 70:52-68.

Vidaver WE, Lister GR, Brooke RC, Binder WD (1991). A manual for the use of variable chlorophyll fluorescence in the assessment of the ecophysiology of conifer seedlings. In FRDA forest resource development report 163, British Columbia, Canada.

Wightman KE (1999). Good tree nursery practices: practical guidelines for community nurseries. International Centre for Research in Agroforestry, Nairobi, Kenya.

Wilson BC, Jacobs DF (2006). Quality assessment of temperate and deciduous hardwood seedlings. New Forests 31:417-433.

Wilson B, Jacobs DF (2012). Chlorophyll fluorescence of stem cambial tissue reflects dormancy development in Juglans nigra seedlings. New Forests 43:771-778.

Wu CW, Lin KH, Lee MC, Peng YL, Chou TY, Chang YS (2015). Using chlorophyll fluorescence and vegetation indices to predict the timing of nitrogen demand in Pentas lanceolata. Korean Journal of Horticultural Science and Technology 33:845-853.

Yang H, Yang X, Zhang, Heskel M, Sun S, Tang J (2017). Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest. Global Change Biology 23:2874-2886.

Yamane Y, Kashino Y, Koike H, Satoh K (1997). Increases in the fluorescence F0 level and reversible inhibition of Photosystem II reaction center by high-temperature treatments in higher plants. Photosynthesis Research 52:57-64.

Zou X, Shi J, Hao L, Zhao J (2011). In vivo noninvasive detection of chlorophyll distribution in cucumber (Cucumis sativus) leaves by indices based on hyperspectral imaging. Analytica Chimica Acta 706:105-112.

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Published

2018-10-20

How to Cite

LIN, K.-H., WU, C.-W., & CHANG, Y.-S. (2018). Applying Dickson Quality Index, Chlorophyll Fluorescence, and Leaf Area Index for Assessing Plant Quality of Pentas lanceolata. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 47(1), 169–176. https://doi.org/10.15835/nbha47111312

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Section

Research Articles
CITATION
DOI: 10.15835/nbha47111312

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