Image-based leaf SPAD value and chlorophyll measurement using a mobile phone: enabling accessible and sustainable crop management
| dc.contributor.author | Anderson J. | |
| dc.contributor.author | Boonyaves K. | |
| dc.contributor.author | Okamoto H. | |
| dc.contributor.author | Karaket N. | |
| dc.contributor.author | Chuekong W. | |
| dc.contributor.author | Garvie M. | |
| dc.contributor.author | Chabang N. | |
| dc.contributor.author | Osorio D. | |
| dc.contributor.author | Supaibulwatana K. | |
| dc.contributor.correspondence | Anderson J. | |
| dc.contributor.other | Mahidol University | |
| dc.date.accessioned | 2026-06-02T18:18:51Z | |
| dc.date.available | 2026-06-02T18:18:51Z | |
| dc.date.issued | 2026-06-01 | |
| dc.description.abstract | Purpose: Leaf chlorophyll content is a critical indicator of plant health. On-farm monitoring is limited by the high cost and accessibility of specialised meters and laboratory assays. This study evaluates a smartphone-based imaging method (PhotoFolia) as a practical, low-cost alternative for accurately estimating leaf SPAD (Soil and Plant Analysis Development) values and chlorophyll content. Methods: Image-based estimates from the PhotoFolia mobile application were validated against standard laboratory assays and SPAD-502+ meter readings. The validation was conducted across four commercial rice varieties cultivated in Thailand. Results: The smartphone imaging method predicted SPAD values with a mean absolute error (MAE) of 1.2 units and chlorophyll concentrations with a mean absolute percentage error (MAPE) of 7.2% relative to laboratory benchmarks. Conclusion: With SPAD error approaching the industry ±1 unit standard and chlorophyll estimation remaining below a 10% relative error threshold, this approach demonstrates that ordinary mobile phones can serve as highly accessible, cost-effective tools for routine on-farm crop monitoring, eliminating the need for dedicated hardware. Highlights: Novel low-cost approach for chlorophyll assay and SPAD-value measurement using standard mobile phone. Achieves accuracy comparable to commercial tools. Eliminates need for specialised sensors or laboratory equipment. Impact: This study demonstrates that mobile phone-based image analysis can accurately estimate leaf SPAD and chlorophyll levels in rice under ambient lighting conditions, offering a low-cost, accessible tool for monitoring plant health. | |
| dc.identifier.citation | Precision Agriculture Vol.27 No.3 (2026) | |
| dc.identifier.doi | 10.1007/s11119-026-10386-x | |
| dc.identifier.eissn | 15731618 | |
| dc.identifier.issn | 13852256 | |
| dc.identifier.scopus | 2-s2.0-105039878089 | |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/123456789/117063 | |
| dc.rights.holder | SCOPUS | |
| dc.subject | Agricultural and Biological Sciences | |
| dc.title | Image-based leaf SPAD value and chlorophyll measurement using a mobile phone: enabling accessible and sustainable crop management | |
| dc.type | Article | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105039878089&origin=inward | |
| oaire.citation.issue | 3 | |
| oaire.citation.title | Precision Agriculture | |
| oaire.citation.volume | 27 | |
| oairecerif.author.affiliation | Mahidol University | |
| oairecerif.author.affiliation | University of Sussex | |
| oairecerif.author.affiliation | Faculty of Science, Mahidol University |
