Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Spectral Phenotyping of Physiological and Anatomical Leaf Traits Related with Maize Water Status.

Plant physiology - 1 Nov 2020

Cotrozzi Lorenzo, Peron Raquel, Tuinstra Mitchell R, Mickelbart Michael V, Couture John J

Abstract excerpt

Advancements in phenotyping techniques capable of rapidly and nondestructively detecting impacts of drought on crops are necessary to meet the 21st-century challenge of food security. Here, we describe the use of hyperspectral reflectance to predict variation in physiological and anatomical leaf traits related with water status under varying water availability in six maize (Zea mays) hybrids that differ in yield...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Crops, Agricultural
Share to Dehydration
Share to Droughts

Methodology Data sources Editorial policy Privacy Delete account & data About Contact Helena Bioinformatics

Share to Plant Leaves

Share to Spectrum Analysis

Share to Stress, Physiological

Share to Zea mays

Source

Open in PubMed Open full text

Identifiers

PMID: 32907885
DOI: 10.1104/pp.20.00577
PMCID: PMC7608158

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Spectral Phenotyping of Physiological and Anatomical Leaf Traits Related with Maize Water Status.PMID 32907885Read ↗

High-Throughput Phenotyping of Maize Leaf Physiological and Biochemical Traits Using Hyperspectral Reflectance.Semantic proximity Read ↗

Phenotyping for abiotic stress tolerance in maize.Semantic proximity Read ↗

Using high-throughput multiple optical phenotyping to decipher the genetic architecture of maize drought tolerance.Semantic proximity Read ↗

Hyperspectral reflectance-based phenotyping for quantitative genetics in crops: Progress and challenges.Semantic proximity Read ↗

Conventional and hyperspectral time-series imaging of maize lines widely used in field trials.Semantic proximity Read ↗

Near-infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments.Semantic proximity Read ↗

Two decades of harnessing standing genetic variation for physiological traits to improve drought tolerance in maize.Semantic proximity Read ↗

Capturing crop adaptation to abiotic stress using image-based technologies.Semantic proximity Read ↗

Bottlenecks and opportunities in field-based high-throughput phenotyping for heat and drought stress.Semantic proximity Read ↗

Genome-wide association study reveals the genetic architecture of drought tolerance in maize using yield-based resistance indices and transcriptomic evidence.Semantic proximity Read ↗

Back to the future for drought tolerance.Semantic proximity Read ↗

Machine Learning Techniques for Predicting Crop Photosynthetic Capacity from Leaf Reflectance Spectra.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.