Early-Stage Detection of Biotic and Abiotic Stress on Plants by Chlorophyll Fluorescence Imaging Analysis

Biosensors, Год журнала: 2023, Номер 13(8), С. 796 - 796

Опубликована: Авг. 8, 2023

Most agricultural land, as a result of climate change, experiences severe stress that significantly reduces yields. Crop sensing by imaging techniques allows early-stage detection biotic or abiotic to avoid damage and significant yield losses. Among the top certified for plant is chlorophyll fluorescence imaging, which can evaluate spatiotemporal leaf changes, permitting pre-symptomatic monitoring physiological status long before any visible symptoms develop, allowing high-throughput assessment. Here, we review different examples how analysis be used stress. Chlorophyll able detect early 15 min after Spodoptera exigua feeding, 30 Botrytis cinerea application on tomato plants, onset water-deficit stress, thus has potential detection. (ChlF) rapid, non-invasive, easy perform, low-cost, highly sensitive method estimate photosynthetic performance influence diverse stresses plants. In terms ChlF parameters, fraction open photosystem II (PSII) reaction centers (qp) detection, since it been found in many recent studies most accurate appropriate indicator ChlF-based screening impact environmental

Язык: Английский

Evaluation of Low-Cost Multi-Spectral Sensors for Measuring Chlorophyll Levels Across Diverse Leaf Types

Sensors, Год журнала: 2025, Номер 25(7), С. 2198 - 2198

Опубликована: Март 31, 2025

Chlorophyll levels are a key indicator of plant nitrogen status, which plays critical role in optimizing agricultural yields. This study evaluated the performance three low-cost multi-spectral sensors, AS7262, AS7263, and AS7265x, for non-destructive chlorophyll measurement. Measurements were taken from diverse set five leaf types, including smooth, uniform leaves (banana mango), textured (jasmine sugarcane), narrow (rice). Partial least squares regression models used to fit sensor spectra levels, using nested cross-validation ensure robust model evaluation. Sensor was assessed R2 mean absolute error (MAE) scores. The AS7265x demonstrated best on with validation scores 0.96-0.95. Its decreased other leaves, 0.75-0.85. AS7262 AS7263 while slightly less accurate, achieved reasonable ranging 0.93 0.86 smooth 0.85 0.73 leaves. All particularly show potential measurement applications. Their low cost accuracy make them suitable applications such as monitoring levels.

Язык: Английский

Improving Functioning of Soil–Plant Systems Using the Application of Sustainable and Intelligent Methods

Agronomy, Год журнала: 2023, Номер 13(11), С. 2715 - 2715

Опубликована: Окт. 28, 2023

We are privileged to serve as Guest Editors for this Special Issue (SI), “Improving Functioning of Soil–Plant Systems Using the Application Sustainable and Intelligent Methods”, in international journal Agronomy [...]

Язык: Английский