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THE QUALITY INDEX - A NEW TOOL FOR INTEGRATING QUANTITATIVE MEASUREMENTS TO ASSESS QUALITY OF YOUNG FLORICULTURE PLANTS

2013· article· en· W2591182099 on OpenAlex

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aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
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Bibliographic record

VenueActa Horticulturae · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFlowering Plant Growth and Cultivation
Canadian institutionsnot available
FundersNational Institute of Food and AgricultureFred C. Gloeckner FoundationPurdue University
KeywordsFloricultureIndex (typography)Quality (philosophy)Computer scienceBiologyHorticultureWorld Wide Web

Abstract

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Floriculture crops are an important sector of ornamental horticulture, with an estimated wholesale value in the United States (U.S.) of US$ 4.13 billion in 2010. Furthermore, the value of propagative materials for these crops is US$ 376 million. The majority of floriculture crop producers utilize young plants including seedlings (plugs) or rooted stem-tip cuttings (liners) produced by propagation specialists and shipped to producers for finishing. Research has focused on improving the efficiency and quality of young plants production, since the advent of the “plug revolution” and increasing popularity of annuals produced from stem-tip cuttings has provided many challenges and opportunities in young plant production. Numerous quantitative measurements of seedlings and rooted cuttings are taken to measure the effects of environmental and/or cultural treatments during propagation. However, of greater importance to young plant producers is the cumulative effect of quantitative parameters on young plant quality. To resolve this, a subjective rating based on perceived visual quality is sometimes used. Here we present the Quality Index (QI), a tool integrating several quantitative measurements and indices to provide an objective assessment of young plant quality. For example, we found that when the daily light integral is increased during propagation of seeds and cuttings of new and current floriculture crops, the QI of young plants increased by up to 858%. We will introduce this concept and discuss the applications, opportunities, and limitations of using the QI for assessing the effects of environmental and/or cultural conditions during propagation of young plant quality in floriculture production. INTRODUCTION Rooted cuttings (liners) and seedlings (plugs) comprise a valuable sector of the global floriculture market. The use of young plants (plugs and liners) allows growers the ability to increase the consistency of their crop and minimize post-transplant finishing time. An increase in the popularity and use of young plants in the past few decades has resulted in more research regarding the effects of environmental conditions and cultural practices on the growth, development, and performance of plugs and liners. For example, research on cutting propagation of herbaceous annual bedding plants has focused on the effects of temperature and duration during shipping on cuttings (Lopez and Runkle, 2008) and environmental and cultural conditions during propagation, including substrate composition (Giselrod, 1983), misting (Graves and Zhang, 1996; Wilkerson et al., 2005a), substrate temperature (Wilkerson et al., 2005b), and mineral nutrition (Santos et al., 2008, 2009). In these studies morphological data were collected and, while the quality of rooted cuttings was not measured, many of the data reported reflect the quality of young plants. For example, important characteristics of seedlings and rooted cuttings include overall growth or biomass accumulation during propagation, the relative amount of root and shoot biomass (R:S ratio), and thickness of stems for easier handling and transplanting (Lopez and Runkle, 2008; Pramuk and Runkle, 2005). These types of data influence the quality and performance of young plants. Proc. VIIth IS on New Floricultural Crops Eds.: G. Facciuto and M.I. Sanchez Acta Hort. 1000, ISHS 2013 386 We may look to the reforestation and afforestation literature from greenhouse and nursery production of tree seedlings for a more comprehensive and integrated morphological assessment of young plant quality (Ritchie, 1984, 2010; Mattsson, 1996; Thompson, 1985). Forest nursery scientists have developed quantitative indices that integrate morphological traits correlated to outplanting success, including the “Dickson Quality Index” (Dickson et al., 1960). The quality index (QI) was originally designed for assessing the quality of Picea abies (L.) H. Karst. and Pinus strobus L. seedlings (Dickson et al., 1960), and is a product of the total dry mass (TDM) divided by the sum of the shoot: root dry mass ratio (S:R) and ratio of stem caliper to stem length (sturdiness quotient; SQ), or QI = TDM/(S:R + SQ). Because these data are frequently collected in young floriculture crop research, an integrated index such as QI provides a tool to easily and objectively measure young plant quality. We have found no reports using any indices such as the QI to assess the quality of young herbaceous floriculture propagules. Therefore, our objective with this research was to evaluate the potential of the QI as an integrated, quantitative measurement of seedling and rooted cutting quality. MATERIALS AND METHODS Experiment 1 Seeds of Tecoma stans (L.) Juss. ex Kunth ‘Mayan Gold’ (Pan American Seed, West Chicago, IL, USA) were sown on 13 Feb. 2009, 23 June 2009, and 15 Jan. 2010 in 72-cell plug trays (44-mL individual cell volume; Dillen Products, Middlefield, OH, USA) filled with a commercial soilless medium composed of (v/v) 70% Canadian sphagnum peat moss and 30% perlite (Super Fine Germinating Mix; Conrad Fafard, Anderson, SC, USA). Seeds were covered with a thin layer of vermiculite (Sunshine; SunGro Horticulture, Bellevue, WA, USA) to maintain moisture and were irrigated as necessary with acidified water supplemented with water-soluble fertilizer (Peters Excel© Cal-Mag© 15N–2.2P–12.5K; Scotts Co., Marysville, OH, USA) to provide 100 mg·L-1 N with every watering beginning at sowing. The greenhouse air temperature set point was a constant 23°C. A 16-h photoperiod (5 am to 9 pm) was maintained with natural day lengths and day-extension lighting provided from high-pressure sodium (HPS) lamps (e-system HID; PARsource, Petaluma, CA, USA). An automatic woven shade curtain was retracted when the outdoor light intensity reached 1000 μmol·m-2·s-1 (OLS 50; Ludvig Svensson Inc., Charlotte, NC, USA) throughout the study to prevent leaf scorch. Immediately after sowing, seeds were placed under daily light integral (DLI) treatments created in the propagation environment with the combination of supplemental light provided by HPS lamps and fixed woven shade cloths placed above individual propagation compartments that reduced light by 30, 50, or 70% (DeWitt Company, Sikeston, MO, USA) or no shade. Five weeks after sowing, fifteen seedlings per DLI treatment were randomly harvested for data collection. Stem caliper above the lowest leaf and stem length from the surface of the substrate to the stem tip were measured with a digital caliper (digiMax; Wiha, Schonach, Germany). Roots were excised and roots and shoots were dried separately in an oven at 70°C for 3 d then weighed. Total dry mass (TDM; shoot dry mass + root dry mass), root: shoot dry mass ratio (R:S; root dry mass/stem dry mass), a modified version of the sturdiness quotient (SQ; shoot length/stem caliper) (Thompson, 1985), and a modified version of the Quality Index [QI = TDM × (R:S + SQ)] (Dickson, 1960) were calculated. Data were analyzed using regression analysis (SPSS 17.0; SPSS, Inc., Chicago, IL, USA) with DLI as the independent variable. Experiment 2 Cuttings of Angelonia angustifolia Benth. ‘AngelMist White Cloud’, Argyranthemum frutescens (L.) Sch. Bip. ‘Madeira Cherry Red’, Diascia barberae Hook. f.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.938
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.142
GPT teacher head0.333
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it