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Stacy A. Adams, Ellen T. Paparozzi, and W.W. Stroup

`Dark Red Annette Hegg' poinsettias (Euphorbia pulcherrima Willd. ex Klotzsch) were grown in a 1 peat : 1 perlite : 1 vermiculite medium using a pinched production schedule with varying N and S fertilizer application rates. Fifty-six treatments consisting of eight N levels (100 to 275 mg·L−1 in 25-mg·L−1 increments) and seven S levels (0 to 75 mg·L−1 in 12.5-mg·L−1 increments) were supplied. Other required nutrients were supplied at commercial recommendations for all treatments. Foliage of each plant was evaluated quantitatively by chromometer readings every 3 weeks. Marketability was determined by sensory evaluations from commercial producers, retailers, and consumers. Results indicated distinct color differences (hue, chroma, value) between S levels of 0 and 12.5 mg·L−1 and a slight difference between S at 12.5 and 25 mg·L−1. The foliage of plants receiving 0 S was lighter, more vivid, and more yellow-green in color. As N levels increased, there was a linear response; foliage became more green, darker, and more dull. Commerical and consumer evaluators rated plants that received S at 0 or 12.5 mg·L−1 at all N levels and plants receiving N at 100 mg L−1 as unmarketable. This research indicates that `Annette Hegg' poinsettia requires S at a minimum of 25 mg·L−1 and N at a minimum of 125 mg·L−1 for commercial acceptance, and commercial N application rates may be greatly reduced when adequate S is supplied.

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Melinda McVey McCluskey, Ellen T. Paparozzi, and Susan L. Cuppett

Previous research on leaf lettuce has shown that altering the N:S ratio has an effect on plant color and N and S content. It appears that nitrogen rates can be decreased if known rates of sulfur are applied. The next step was to determine what effect altering the N:S ratio in lettuce had on consumer acceptance of the product.

`Grand Rapids' lettuce was grown hydroponically at six rates of S (0, 7.5, 15, 30, 60, 120 ppm) and four rates of N (30, 60, 120, 240 ppm). Sensory evaluation was performed on 20 of 24 treatments. The sensory panel was composed of 12 panelists who used the nonstructured hedonic scale to evaluate each lettuce treatment on appearance, color, texture, flavor, bitter flavor, and overall acceptability.

Results from the sensory evaluation indicate that differences in color, appearance, and bitter flavor were detected between treatments by the panel. Lettuce plants that received higher amounts of N in relation to S were considered less bitter in flavor and, over all, more acceptable than plants which received higher amounts of S in relation to N. These results indicate that altering the N:S ratio will affect consumer acceptance of leaf lettuce.

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Ellen T. Paparozzi, M. Elizabeth Conley, and Walter W. Stroup

Three cultivars of poinsettia, Freedom Red, Lilo and Red Sails, were grown in a peat:perlite:vermiculite mix according to a commercial production schedule. Twelve selected nitrogen–sulfur fertilizer combinations were applied (125, 150, 175 ppm N with either 12.5, 25, or 37.5 ppm S, 225 and 275 ppm N with either 37.5 or 75 ppm S). The experimental design was a split plot with cultivars as the whole plot and fertilizer levels as the split-plot factor. Mix samples were taken initially, at production week 7 and at the end of the experiment. Nitrate-nitrogen, sulfate-sulfur and total nitrogen were determined. Data were analyzed using SAS PROC MIXED. Visually all cultivars responded similarly to all treatments and were salable. Thus, levels of N as low as 125 or 150 with 12.5 ppm S produced quality plants. Sulfate-S tended to accumulate in the mix while nitrate-N and total N did not. Both nitrate-N and sulfate-S concentrations were affected by an interaction between the cultivar and the amount of S applied with `Freedom' better able to utilize available sulfur. `Lilo' removed more nitrate-N and total N from the mix than `Freedom' which removed more than `Red Sails', but only at specific levels of sulfur. There was no cultivar by nitrogen interaction for any variable measured.

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Matthew H. Kramer, Ellen T. Paparozzi, and Walter W. Stroup

We examined all articles in volume 139 and the first issue of volume 140 of the Journal of the American Society for Horticultural Science (JASHS) for statistical problems. Slightly fewer than half appeared to have problems. This is consistent with what has been found for other biological journals. Problems ranged from inappropriate analyses and statistical procedures to insufficient (or complete lack of) information on how the analyses were performed. A common problem arose from taking many measurements from the same plant, which leads to correlated test results, ignored when declaring significance at P = 0.05 for each test. In this case, experiment-wise error control is lacking. We believe that many of these problems could and should have been caught in the writing or review process; i.e., identifying them did not require an extensive statistics background. This suggests that authors and reviewers have not absorbed nor kept current with many of the statistical basics needed for understanding their own data, for conducting proper statistical analyses, and for communicating their results. For a variety of reasons, graduate training in statistics for horticulture majors appears inadequate; we suggest that researchers in this field actively seek out opportunities to improve and update their statistical knowledge throughout their careers and engage a statistician as a collaborator early when unfamiliar methods are needed to design or analyze a research study. In addition, the ASHS, which publishes three journals, should assist authors, reviewers, and editors by recognizing and supporting the need for continuing education in quantitative literacy.

Open access

Matthew H. Kramer, Ellen T. Paparozzi, and Walter W. Stroup

We examined all articles in volume 139 and the first issue of volume 140 of the Journal of the American Society for Horticultural Science (JASHS) for statistical problems. Slightly fewer than half appeared to have problems. This is consistent with what has been found for other biological journals. Problems ranged from inappropriate analyses and statistical procedures to insufficient (or complete lack of) information on how the analyses were performed. A common problem arose from taking many measurements from the same plant, which leads to correlated test results, ignored when declaring significance at P = 0.05 for each test. In this case, experiment-wise error control is lacking. We believe that many of these problems could and should have been caught in the writing or review process; i.e., identifying them did not require an extensive statistics background. This suggests that authors and reviewers have not absorbed nor kept current with many of the statistical basics needed for understanding their own data, for conducting proper statistical analyses, and for communicating their results. For a variety of reasons, graduate training in statistics for horticulture majors appears inadequate; we suggest that researchers in this field actively seek out opportunities to improve and update their statistical knowledge throughout their careers and engage a statistician as a collaborator early when unfamiliar methods are needed to design or analyze a research study. In addition, the ASHS, which publishes three journals, should assist authors, reviewers, and editors by recognizing and supporting the need for continuing education in quantitative literacy.

Open access

Matthew H. Kramer, Ellen T. Paparozzi, and Walter W. Stroup

We examined all articles in volume 139 and the first issue of volume 140 of the Journal of the American Society for Horticultural Science (JASHS) for statistical problems. Slightly fewer than half appeared to have problems. This is consistent with what has been found for other biological journals. Problems ranged from inappropriate analyses and statistical procedures to insufficient (or complete lack of) information on how the analyses were performed. A common problem arose from taking many measurements from the same plant, which leads to correlated test results, ignored when declaring significance at P = 0.05 for each test. In this case, experiment-wise error control is lacking. We believe that many of these problems could and should have been caught in the writing or review process; i.e., identifying them did not require an extensive statistics background. This suggests that authors and reviewers have not absorbed nor kept current with many of the statistical basics needed for understanding their own data, for conducting proper statistical analyses, and for communicating their results. For a variety of reasons, graduate training in statistics for horticulture majors appears inadequate; we suggest that researchers in this field actively seek out opportunities to improve and update their statistical knowledge throughout their careers and engage a statistician as a collaborator early when unfamiliar methods are needed to design or analyze a research study. In addition, the ASHS, which publishes three journals, should assist authors, reviewers, and editors by recognizing and supporting the need for continuing education in quantitative literacy.

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Matthew H. Kramer, Ellen T. Paparozzi, and Walter W. Stroup

A key characteristic of scientific research is that the entire experiment (or series of experiments), including the data analyses, is reproducible. This aspect of science is increasingly emphasized. The Materials and Methods section of a scientific paper typically contains the necessary information for the research to be replicated and expanded on by other scientists. Important components are descriptions of the study design, data collection, and statistical analysis of those data, including the software used. In the Results section, statistical analyses are presented; these are usually best absorbed from figures. Model parameter estimates (including variances) and effect sizes should also be included in this section, not just results of significance tests, because they are needed for subsequent power and meta-analyses. In this article, we give key components to include in the descriptions of study design and analysis, and discuss data interpretation and presentation with examples from the horticultural sciences.

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Marci Spaw, Kimberly A. Williams*, Ingrid L. Mallberg, Laurie Hodges, and Ellen T. Paparozzi

Case studies promote the development of problem-solving skills, but few have been created for horticulture and related curricula. This web-based decision case presents the challenge of determining the cause of symptoms of foliar chlorosis in a crop of cut Dicentra spectabilis while forcing it for Valentine's Day sales. It provides a tool to promote the development of diagnostic skills for production dilemmas, including nutritional disorders, disease and insect problems, and evaluation of the appropriateness of cultural practices. Cut Dicentra is a minor crop and standard production practices are not well established. Therefore, solving this case requires that students research production protocol as well as nutritional and pest problems to develop a solution. In this case study, which is supported by an image-rich web-based version at www.hightunnels.org/cutflowercasestudy.htm, a grower at Flint's Flower Farm must determine the cause of foliar chlorosis that is slowly appearing on about half of the plants of her cut Dicentra crop. The condition could be related to a number of possible problems including a nutritional disorder, insect attack, disease infection, or production practices. Some resources are provided to aid students in gathering background information. Data accumulated by the grower is presented to allow students to logically eliminate unlikely solutions and predict (a) probable cause(s). The solution, which is rather unique to this crop, is provided. This case study is intended for use in upper-level undergraduate courses of floriculture production, nutrient management, plant pathology, and entomology.

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Sabrina J. Ruis, Humberto Blanco-Canqui, Ellen T. Paparozzi, and Russ Zeeck

Processed corn (Zea mays L.) stover (PCS), defined as finely ground stover with or without additions, could be a potential alternative to peat in greenhouse mixes. However, this option has not yet been examined. We performed two split-plot experiments (1 and 2) with tomatoes (Solanum lycopersicum L.) and marigolds (Tagetes patula L.) as main plots. Expt. 1 involved five stover rates (0%, 25%, 50%, 75%, and 100% by volume) mixed with peat as subplots. Expt. 2 involved 0% stover mixed with peat, 25% distillers grain, and 50% quick compost (mechanically processed to accelerate compost process) stover with and without CaO, and 75% quick compost stover without CaO, as subplots. We measured growth parameters (height, dry weight, and flower number) and properties of the mixes. During Expt. 1, across both species, the addition of stover at rates >50% reduced relative greenness by 40%, vegetative biomass yield by 74%, and reproductive biomass yield by 73% compared to mixes with 0% and 25% stover. As the stover rate increased, available water content in the mixes decreased (r = −0.34; P < 0.001). Mixes with 0% and 25% stover had 34% more available water than mixes with 100% stover, which probably reduced plant growth in the 100% stover treatment. As the stover rate increased, plant tissue N and P concentrations decreased. Mixes with 0% stover generally had greater N and P concentrations than mixes with stover. During Expt. 2, for marigolds, the addition of 50% quick compost stover+CaO and 75% quick compost stover-CaO reduced relative greenness by 19% and vegetative biomass by 66% compared to mixes with 25% distillers grain or 0% stover. For tomatoes, the addition of 50% quick compost stover+CaO and 75% quick compost stover-CaO reduced biomass yield by 64%, which may be due to the higher pH and electrical conductivity (EC) of both treatments. Plant tissue N and P concentrations were greater in the mix with 25% distillers grain compared to most treatments, but N and P concentrations in the other mixes varied. Overall, the 25% distillers grain (3 peat: 1 distiller grain: 4 perlite) and 25% stover (3 peat: 1 stover: 4 perlite) treatments showed the most promise as additives in a peat-based mix.

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Ellen T. Paparozzi, Neil Mattson, Mara Grossman, Stephanie Burnett, and Roberto Lopez