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Article

Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs

by
Kahlin Wacker
1,†,
Changhyeon Kim
2,†,
Marc W. van Iersel
1,
Mark Haidekker
3,
Lynne Seymour
4 and
Rhuanito Soranz Ferrarezi
1,*
1
Department of Horticulture, University of Georgia, Athens, GA 30602, USA
2
Department of Plant Science and Landscape Architecture, University of Connecticut, Storrs, CT 06269, USA
3
College of Engineering, University of Georgia, Athens, GA 30602, USA
4
Department of Statistics, University of Georgia, Athens, GA 30602, USA
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2024, 24(17), 5809; https://doi.org/10.3390/s24175809
Submission received: 23 July 2024 / Revised: 25 August 2024 / Accepted: 30 August 2024 / Published: 6 September 2024
(This article belongs to the Section Smart Agriculture)

Abstract

In a production environment, delayed stress recognition can impact yield. Imaging can rapidly and effectively quantify stress symptoms using indexes such as normalized difference vegetation index (NDVI). Commercial systems are effective but cannot be easily customized for specific applications, particularly post-processing. We developed a low-cost customizable imaging system and validated the code to analyze images. Our objective was to verify the image analysis code and custom system could successfully quantify the changes in plant canopy reflectance. ‘Supercascade Red’, ‘Wave© Purple’, and ‘Carpet Blue’ Petunias (Petunia × hybridia) were transplanted individually and subjected to increasing fertilizer treatments and increasing substrate pH in a greenhouse. Treatments for the first trial were the addition of a controlled release fertilizer at six different rates (0, 0.5, 1, 2, 4, and 8 g/pot), and for the second trial, fertilizer solution with four pHs (4, 5.5, 7, and 8.5), with eight replications with one plant each. Plants were imaged twice a week using a commercial imaging system for fertilizer and thrice a week with the custom system for pH. The collected images were analyzed using an in-house program that calculated the indices for each pixel of the plant area. All cultivars showed a significant effect of fertilizer on the projected canopy size and dry weight of the above-substrate biomass and the fertilizer rate treatments (p < 0.01). Plant tissue nitrogen concentration as a function of the applied fertilizer rate showed a significant positive response for all three cultivars (p < 0.001). We verified that the image analysis code successfully quantified the changes in plant canopy reflectance as induced by increasing fertilizer application rate. There was no relationship between the pH and NDVI values for the cultivars tested (p > 0.05). Manganese and phosphorus had no significance with chlorophyll fluorescence for ‘Carpet Blue’ and ‘Wave© Purple’ (p > 0.05), though ‘Supercascade Red’ was found to have significance (p < 0.01). pH did not affect plant canopy size. Chlorophyll fluorescence pixel intensity against the projected canopy size had no significance except in ‘Wave© Purple’ (p = 0.005). NDVI as a function of the projected canopy size had no statistical significance. We verified the ability of the imaging system with integrated analysis to quantify nutrient deficiency-induced variability in plant canopies by increasing pH levels.
Keywords: plant image segmentation; chlorophyll fluorescence; normalized difference vegetation index plant image segmentation; chlorophyll fluorescence; normalized difference vegetation index

Share and Cite

MDPI and ACS Style

Wacker, K.; Kim, C.; Iersel, M.W.v.; Haidekker, M.; Seymour, L.; Ferrarezi, R.S. Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs. Sensors 2024, 24, 5809. https://doi.org/10.3390/s24175809

AMA Style

Wacker K, Kim C, Iersel MWv, Haidekker M, Seymour L, Ferrarezi RS. Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs. Sensors. 2024; 24(17):5809. https://doi.org/10.3390/s24175809

Chicago/Turabian Style

Wacker, Kahlin, Changhyeon Kim, Marc W. van Iersel, Mark Haidekker, Lynne Seymour, and Rhuanito Soranz Ferrarezi. 2024. "Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs" Sensors 24, no. 17: 5809. https://doi.org/10.3390/s24175809

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