Automated Author Profile

FLYNN, KYLE

National Agricultural Library

Current S-Index

4.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

1.1

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

67.3%

Average FAIR Score per dataset

Total Citations

8

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth

Two field research projects focused on cotton were conducted at the El Reno, OK and Temple, TX USDA-ARS research stations. The study at the Southern Plains research station took place in 2019 where cotton cultivars included: FiberMax 1830 GLT, FiberMax 1888 GL, FiberMax 2498 GLT, Phytogen 300 W3FE, Phytogen 350 W3FE, and Phytogen 490 W3FE. The experiment took place on Norge silt loam soil. The experimental design included a randomized complete block design with three replications and four nitrogen treatments: unfertilized, cover crop (Lathyrus sativus) with 0, 30, or 60 kg/ha of inorganic nitrogen. The experiment was planted at a seeding rate of 12 seeds/m on May 28, 2019. The study at the Texas Gulf station incorporated four cultivars: DP 1646 B2XF, DP 2012 B3XF, DP 2239 B3XF, and DP 1646 B2XF. The experiment took place on Houston Black clay soils. The experimental design included 6-row strip plots with 0.76 m row spacings and approximately 00.1 m plant spacing at a seeding rate of 13 seeds per meter. The experiment also included a multi-planting date design that included March 28, April 11, April 22, and May 11.These two stations collected in-situ measurements of height, node count, leaf area index (LAI), canopy cover percentage, and chlorophyll content. LAI data were collected using the LAI-2200C Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA). Canopy cover data were collected using the app “Canopeo” where a ratio of plant to ground pixels were calculated. Chlorophyll content data were collected using Chlorophyll Content Meter-300 (Opti-Sciences, Hudson, NH, USA) where the unit of measure was mg/m2. Directly following these measurements a spectroradiometer (FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA) was utilized to collect hyperspectral data from 350nm to 2500nm. The locations of both the in-situ and hyperspectral data collections were chosen at random throughout the field projects and took place in 2019 (OK) and 2022 (TX) with specific dates of collection included in the database.

Authors

  • FLYNN, KYLE ;
  • Witt, Travis W. ;
  • S. Baath, Gurjinder ;
  • Chinmayi, H.K. ;
  • Smith, Douglas ;
  • Gowda, Prasanna ;
  • Ashworth, Amanda
1 Citation0 Mentions85% FAIR0.8 Dataset Index
10.15482/usda.adc/277654772024

Data from: Hyperspectral reflectance and machine learning for multi-site monitoring of cotton growth

Two field research projects focused on cotton were conducted at the El Reno, OK and Temple, TX USDA-ARS research stations. The study at the Southern Plains research station took place in 2019 where cotton cultivars included: FiberMax 1830 GLT, FiberMax 1888 GL, FiberMax 2498 GLT, Phytogen 300 W3FE, Phytogen 350 W3FE, and Phytogen 490 W3FE. The experiment took place on Norge silt loam soil. The experimental design included a randomized complete block design with three replications and four nitrogen treatments: unfertilized, cover crop (Lathyrus sativus) with 0, 30, or 60 kg/ha of inorganic nitrogen. The experiment was planted at a seeding rate of 12 seeds/m on May 28, 2019. The study at the Texas Gulf station incorporated four cultivars: DP 1646 B2XF, DP 2012 B3XF, DP 2239 B3XF, and DP 1646 B2XF. The experiment took place on Houston Black clay soils. The experimental design included 6-row strip plots with 0.76 m row spacings and approximately 00.1 m plant spacing at a seeding rate of 13 seeds per meter. The experiment also included a multi-planting date design that included March 28, April 11, April 22, and May 11.These two stations collected in-situ measurements of height, node count, leaf area index (LAI), canopy cover percentage, and chlorophyll content. LAI data were collected using the LAI-2200C Plant Canopy Analyzer (LI-COR, Lincoln, NE, USA). Canopy cover data were collected using the app “Canopeo” where a ratio of plant to ground pixels were calculated. Chlorophyll content data were collected using Chlorophyll Content Meter-300 (Opti-Sciences, Hudson, NH, USA) where the unit of measure was mg/m2. Directly following these measurements a spectroradiometer (FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA) was utilized to collect hyperspectral data from 350nm to 2500nm. The locations of both the in-situ and hyperspectral data collections were chosen at random throughout the field projects and took place in 2019 (OK) and 2022 (TX) with specific dates of collection included in the database.

Authors

  • FLYNN, KYLE ;
  • Witt, Travis W. ;
  • S. Baath, Gurjinder ;
  • Chinmayi, H.K. ;
  • Smith, Douglas ;
  • Gowda, Prasanna ;
  • Ashworth, Amanda
1 Citation0 Mentions15% FAIR0.4 Dataset Index
10.15482/usda.adc/27765477.v12024

Legume hyperspectral and <i>in-situ</i> biophysical/biochemical dataset collected in the Southern Plains

A field experiment focused on three legumes (soybeans [Glycine max], mothbeans [Vigna aconitifolia], and tepary bean [Phaseolus acutifolius]) was conducted in El Reno, OK over a two year period (2018, 2019). The split-split plot design for the legumes were subject to various row spacing (38cm and 76cm) and irrigation regimes (irrigated and rainfed). Sampling of the plots took place a total of seven times over the two year period. Each of the samplings included an initial triplicate (averaged) hyperspectral readings using a spectroradiometer (350nm to 2500nm; FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA), in-situ measurements (canopy cover [collected with the “Canopeo” app where a ratio of plant to ground pixels were calculated], chlorophyll content [collected with Chlorophyll Content Meter-300, Opti-Sciences, Hudson, NH, USA]), and biomass clipping for various laboratory analytics (dry weight, nitrogen/carbon content, crude protein, neutral detergent fiber, acid detergent fiber, in vitro true digestibility). Locations for sampling (n=334) within the 4m x 3m plots were chosen at random.

Authors

  • FLYNN, KYLE ;
  • S. Baath, Gurjinder ;
  • Chinmayi, H.K. ;
  • O. Lee, Trey ;
  • Gowda, Prasanna ;
  • Northup, Brian K. ;
  • Ashworth, Amanda
3 Citations0 Mentions85% FAIR1.5 Dataset Index
10.15482/usda.adc/278684252024

Legume hyperspectral and <i>in-situ</i> biophysical/biochemical dataset collected in the Southern Plains

A field experiment focused on three legumes (soybeans [Glycine max], mothbeans [Vigna aconitifolia], and tepary bean [Phaseolus acutifolius]) was conducted in El Reno, OK over a two year period (2018, 2019). The split-split plot design for the legumes were subject to various row spacing (38cm and 76cm) and irrigation regimes (irrigated and rainfed). Sampling of the plots took place a total of seven times over the two year period. Each of the samplings included an initial triplicate (averaged) hyperspectral readings using a spectroradiometer (350nm to 2500nm; FieldSpec Pro FR: Malvern Panalytical, Westborough, MA, USA), in-situ measurements (canopy cover [collected with the “Canopeo” app where a ratio of plant to ground pixels were calculated], chlorophyll content [collected with Chlorophyll Content Meter-300, Opti-Sciences, Hudson, NH, USA]), and biomass clipping for various laboratory analytics (dry weight, nitrogen/carbon content, crude protein, neutral detergent fiber, acid detergent fiber, in vitro true digestibility). Locations for sampling (n=334) within the 4m x 3m plots were chosen at random.

Authors

  • FLYNN, KYLE ;
  • S. Baath, Gurjinder ;
  • Chinmayi, H.K. ;
  • O. Lee, Trey ;
  • Gowda, Prasanna ;
  • Northup, Brian K. ;
  • Ashworth, Amanda
3 Citations0 Mentions85% FAIR1.5 Dataset Index
10.15482/usda.adc/27868425.v12024