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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. \u2018Supercascade Red\u2019, \u2018Wave\u00a9 Purple\u2019, and \u2018Carpet Blue\u2019 Petunias (Petunia \u00d7 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 &lt; 0.01). Plant tissue nitrogen concentration as a function of the applied fertilizer rate showed a significant positive response for all three cultivars (p &lt; 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 &gt; 0.05). Manganese and phosphorus had no significance with chlorophyll fluorescence for \u2018Carpet Blue\u2019 and \u2018Wave\u00a9 Purple\u2019 (p &gt; 0.05), though \u2018Supercascade Red\u2019 was found to have significance (p &lt; 0.01). pH did not affect plant canopy size. Chlorophyll fluorescence pixel intensity against the projected canopy size had no significance except in \u2018Wave\u00a9 Purple\u2019 (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.<\/jats:p>","DOI":"10.3390\/s24175809","type":"journal-article","created":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T11:53:11Z","timestamp":1725623591000},"page":"5809","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Validation of In-House Imaging System via Code Verification on Petunia Images Collected at Increasing Fertilizer Rates and pHs"],"prefix":"10.3390","volume":"24","author":[{"given":"Kahlin","family":"Wacker","sequence":"first","affiliation":[{"name":"Department of Horticulture, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1802-9579","authenticated-orcid":false,"given":"Changhyeon","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Plant Science and Landscape Architecture, University of Connecticut, Storrs, CT 06269, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5491-0622","authenticated-orcid":false,"given":"Marc W.","family":"van Iersel","sequence":"additional","affiliation":[{"name":"Department of Horticulture, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0203-7208","authenticated-orcid":false,"given":"Mark","family":"Haidekker","sequence":"additional","affiliation":[{"name":"College of Engineering, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8023-5269","authenticated-orcid":false,"given":"Lynne","family":"Seymour","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6873-7995","authenticated-orcid":false,"given":"Rhuanito Soranz","family":"Ferrarezi","sequence":"additional","affiliation":[{"name":"Department of Horticulture, University of Georgia, Athens, GA 30602, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,6]]},"reference":[{"key":"ref_1","first-page":"309","article-title":"Monitoring vegetation systems in the great plains with ERTS","volume":"351","author":"Rouse","year":"1974","journal-title":"NASA Spec. 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