Pentas: A data-driven approach for generating leaf tissue nutrient interpretation ranges

Authors: VEAZIE, PATRICK - North Carolina State University; CHEN, HSUAN - North Carolina State University; HICKS, KRISTIN - North Carolina Department Of Agriculture & Consumer Services; Boldt, Jennifer; WHIPKER, BRIAN - North Carolina State University

Submitted to: Journal of Plant Nutrition
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/29/2024
Publication Date: 10/1/2024
Citation: Veazie, P., Chen, H., Hicks, K., Boldt, J.K., Whipker, B. 2024. Pentas: A data-driven approach for generating leaf tissue nutrient interpretation ranges. Journal of Plant Nutrition. https://doi.org/10.1080/01904167.2024.2405637.
DOI: https://doi.org/10.1080/01904167.2024.2405637

Interpretive Summary: The greenhouse floriculture industry relies on collecting and analyzing leaf samples to diagnose nutrient disorders. The diversity of flowering plants grown makes it challenging to develop comprehensive, crop-specific leaf tissue nutrient standards for all crops. Basic tissue nutrient values exist for pentas, a popular warm-season plant, but the values are based on a small data set. This research used a larger set of leaf samples to develop nutrient distribution curves for eleven essential elements. Refined values were defined for deficient, low, sufficient, high, and excessive nutrient values. This additional precision will help growers better identify when pentas plants are deficient or excessive in a particular element and guide which corrective actions to take. Improved leaf nutrient ranges will improve crop growth and reduce overuse of fertilizers.

Technical Abstract: Foliar tissue sampling has been used in the greenhouse industry to diagnose nutrient disorders for many crops. Leaf tissue nutrient standards for pentas (Pentas lanceolata Forssk.) were non-existent before a recent rate study was published. This study expands prior work and presents a novel method to create data-driven nutrient interpretation ranges by fitting models based on the Sufficiency Range Approach (SRA) to provide more refined ranges of deficient, low, sufficient, high, and excessive values for 11 essential elements based on n=407 data points. Data distributions were analyzed by fitting Normal, Gamma, and Weibull distributions. This study establishes the use of SRA for the creation of refined interpretation ranges for pentas foliar nutrient analysis results with a higher degree of precision than what is currently available to the greenhouse industry for diagnosing fertility status.