Phenotyping cotton leaf chlorophyll via hyperspectral reflectance sensing, spectral vegetation indices, and machine learning.

Cotton ( L.) leaf chlorophyll (Chl) has been targeted as a phenotype for breeding selection to improve cotton tolerance to environmental stress. However, high-throughput phenotyping methods based on hyperspectral reflectance sensing are needed to rapidly screen cultivars for chlorophyll in the field.

Proximal Active Optical Sensing Operational Improvement for Research Using the CropCircle ACS-470, Implications for Measurement of Normalized Difference Vegetation Index (NDVI).

Active radiometric reflectance is useful to determine plant characteristics in field conditions. However, the physics of silicone diode-based sensing are temperature sensitive, where a change in temperature affects photoconductive resistance. High-throughput plant phenotyping (HTPP) is a modern approach using sensors often mounted to proximal based platforms for spatiotemporal measurements of field grown plants.

Assessing Drought and Heat Stress-Induced Changes in the Cotton Leaf Metabolome and Their Relationship With Hyperspectral Reflectance.

The study of phenotypes that reveal mechanisms of adaptation to drought and heat stress is crucial for the development of climate resilient crops in the face of climate uncertainty. The leaf metabolome effectively summarizes stress-driven perturbations of the plant physiological status and represents an intermediate phenotype that bridges the plant genome and phenome. The objective of this study was to analyze the effect of water deficit and heat stress on the leaf metabolome of 22 genetically diverse accessions of upland cotton grown in the Arizona low desert over two consecutive years.

Arthropod Demography, Distribution, and Dispersion in a Novel Trap-Cropped Cotton Agroecosystem.

Vernonia [Vernonia galamensis (Cass.) Less.] (Asterales: Asteraceae) was examined as a potential trap crop for the cotton (Gossypium hirsutum L.

Chlorophyll fluorescence imaging captures photochemical efficiency of grain sorghum () in a field setting.

Background: Photosynthesis is one of the most important biological reactions and forms the basis of crop productivity and yield on which a growing global population relies. However, to develop improved plant cultivars that are capable of increased productivity, methods that can accurately and quickly quantify photosynthetic efficiency in large numbers of genotypes under field conditions are needed. Chlorophyll fluorescence imaging is a rapid, non-destructive measurement that can provide insight into the efficiency of the light-dependent reactions of photosynthesis.

A data workflow to support plant breeding decisions from a terrestrial field-based high-throughput plant phenotyping system.

Field-based high-throughput plant phenotyping (FB-HTPP) has been a primary focus for crop improvement to meet the demands of a growing population in a changing environment. Over the years, breeders, geneticists, physiologists, and agronomists have been able to improve the understanding between complex dynamic traits and plant response to changing environmental conditions using FB-HTPP. However, the volume, velocity, and variety of data captured by FB-HTPP can be problematic, requiring large data stores, databases, and computationally intensive data processing pipelines.

Deploying a Proximal Sensing Cart to Identify Drought-Adaptive Traits in Upland Cotton for High-Throughput Phenotyping.

Field-based high-throughput phenotyping is an emerging approach to quantify difficult, time-sensitive plant traits in relevant growing conditions. Proximal sensing carts represent an alternative platform to more costly high-clearance tractors for phenotyping dynamic traits in the field. A proximal sensing cart and specifically a deployment protocol, were developed to phenotype traits related to drought tolerance in the field.

Use of Body-Mounted Cameras to Enhance Data Collection: An Evaluation of Two Arthropod Sampling Techniques.

A study was conducted that compared the effectiveness of a sweepnet versus a vacuum suction device for collecting arthropods in cotton. The study differs from previous research in that body-mounted action cameras (B-MACs) were used to record the activity of the person conducting the arthropod collections. The videos produced by the B-MACs were then analyzed with behavioral event recording software to quantify various aspects of the sampling process.

Resistance to Multiple Soil-Borne Pathogens of the Pacific Northwest, USA Is Colocated in a Wheat Recombinant Inbred Line Population.

Soil-borne pathogens of the Pacific Northwest decrease yields in both spring and winter wheat. Pathogens of economic importance include , , , and AG8. Few options are available to growers to manage these pathogens and reduce yield loss, therefore the focus for breeding programs is on developing resistant wheat cultivars.

Detection and Discrimination of Pratylenchus neglectus and P. thornei in DNA Extracts from Soil.

A species-specific polymerase chain reaction (PCR) method was developed to detect and identify the root-lesion nematodes Pratylenchus neglectus and P. thornei from soil. A primer set was designed from Pratylenchus 28S rRNA gene sequences of the D3 expansion domain.