cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.30890804
title: Supplementary Material for: Composite digenic diabetes linked to heterozygous variants of GCK and NEUROD1 - A Case Report

description: Introduction. We wanted to establish the etiologic cause of diabetes in a female subject with mild hyperglycemia since childhood, that suddenly worsened in her late 40s. We retrieved proband's laboratory data from age of 5 years. We assessed type 1 diabetes autoantibodies and performed genetic screening by clinical exome. 
Case presentation. Proband showed stable hyperglycemia not requiring pharmacological therapy for 42 years. Proband's fasting plasma glucose increased from 120-130 mg/dl (6.1-7.2 mmol/L) to 150-159 mg/dl (8.3-8.8 mmol/L) at the age of 47 years. Four type 1 diabetes autoantibodies resulted repeatedly negative. A spontaneous glucokinase pathogenic variant (c.645C&gt;A, p. Tyr215Ter) and a NEUROD1variant (c.616dupC, p.His206ProfsTer38) were identified in the proband. Her mother, who carries the NEUROD1 variant, was diagnosed with diabetes by OGTT (120'= 211 mg/dl) when 77 years old. NEUROD1, a low penetrance maturity onset diabetes of the young (MODY) gene, is known to regulate gene trascription of GCK and SLC2A2, encoding for GLUT2, a functional partner of GCK in glucose sensing of the  cell.
Conclusions. We conclude that the low penetrance NEUROD1 variant is responsible of the peculiar trajectory of fasting glucose in a subject who presented with classical metabolic phenotype associated with glucokinase haploinsufficiency from childhood to adulthood.
DOI: 10.6084/m9.figshare.30890804.v1
title: Supplementary Material for: Composite digenic diabetes linked to heterozygous variants of GCK and NEUROD1 - A Case Report

description: Introduction. We wanted to establish the etiologic cause of diabetes in a female subject with mild hyperglycemia since childhood, that suddenly worsened in her late 40s. We retrieved proband's laboratory data from age of 5 years. We assessed type 1 diabetes autoantibodies and performed genetic screening by clinical exome. 
Case presentation. Proband showed stable hyperglycemia not requiring pharmacological therapy for 42 years. Proband's fasting plasma glucose increased from 120-130 mg/dl (6.1-7.2 mmol/L) to 150-159 mg/dl (8.3-8.8 mmol/L) at the age of 47 years. Four type 1 diabetes autoantibodies resulted repeatedly negative. A spontaneous glucokinase pathogenic variant (c.645C&gt;A, p. Tyr215Ter) and a NEUROD1variant (c.616dupC, p.His206ProfsTer38) were identified in the proband. Her mother, who carries the NEUROD1 variant, was diagnosed with diabetes by OGTT (120'= 211 mg/dl) when 77 years old. NEUROD1, a low penetrance maturity onset diabetes of the young (MODY) gene, is known to regulate gene trascription of GCK and SLC2A2, encoding for GLUT2, a functional partner of GCK in glucose sensing of the  cell.
Conclusions. We conclude that the low penetrance NEUROD1 variant is responsible of the peculiar trajectory of fasting glucose in a subject who presented with classical metabolic phenotype associated with glucokinase haploinsufficiency from childhood to adulthood.
DOI: 10.25909/22875356
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (N June)

description: Images and data from various phenotyping studies (N June) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.25909/22875356.v1
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (N June)

description: Images and data from various phenotyping studies (N June) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.25909/22875359
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (S July)

description: Images and data from various phenotyping studies (S July) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.25909/22875359.v1
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (S July)

description: Images and data from various phenotyping studies (S July) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.25909/22875362
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (S June)

description: Images and data from various phenotyping studies (S June) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.25909/22875362.v1
title: APPF TPA phenotyping dataset: UA TPA (Mischis, Berger) - Various (S June)

description: Images and data from various phenotyping studies (S June) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, Berger) ending 2013-07-01
DOI: 10.6084/m9.figshare.30890807
title: Supplementary Material for: A Novel Missense Mutation in a Compound Heterozygous Patient with Fish-Eye Disease: A Case Report

description: Introduction: Fish-eye disease (FED) is a rare autosomal recessive disorder caused by a partial deficiency of lecithin-cholesterol acyltransferase (LCAT) activity. It is characterized by progressive corneal opacification and dyslipidemia in the absence of systemic manifestations. We describe the clinical presentation, optical coherence tomography (OCT) imaging findings, and Scheimpflug-based corneal densitometry results in a patient with FED carrying both a pathogenic variant and a novel missense variant of the LCAT gene not reported in the current literature.

Case Presentation: We present a rare case of a 25-year-old female with bilateral corneal opacities, reduced plasma high-density lipoprotein cholesterol (&lt; 5 mg/dL), and elevated low-density lipoprotein cholesterol levels (&gt; 133 mg/dL). Visual acuity remained 20/20 in both eyes. Slit-lamp examination revealed diffuse subepithelial and anterior stromal deposits. The central corneal thickness was thinner than normal on Scheimpflug tomography, measuring 419 µm OD and 409 µm OS. OCT findings confirmed stromal thinning (479 µm OD and 470 µm OS), with preserved central epithelial thickness, and demonstrated corneal opacities throughout the cornea. The cholesteryl ester–to–total cholesterol ratio remained within normal range. Genetic analysis identified a previously reported pathogenic variant in exon 4 of LCAT (c.440C&gt;T, p.Thr147Ile) and a novel missense mutation in exon 5 (c.715G&gt;A, p.Gly239Ser), classified as a variant of uncertain significance.

Conclusion: FED is a rare genetic disorder that is associated with corneal clouding and dyslipidemia. Genetic analysis confirmed the diagnosis with a compound heterozygous genotype, while OCT and corneal densitometry were effective modalities for quantifying and characterizing lipid deposits in FED.
DOI: 10.25909/22875368
title: APPF TPA phenotyping dataset: UA TPA (Mischis, KAUST) - Quinoa (pilot)

description: Images and data from quinoa phenotyping studies (pilot) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, KAUST) ending 2016-05-20
DOI: 10.25909/22875368.v1
title: APPF TPA phenotyping dataset: UA TPA (Mischis, KAUST) - Quinoa (pilot)

description: Images and data from quinoa phenotyping studies (pilot) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Mischis, KAUST) ending 2016-05-20
DOI: 10.6084/m9.figshare.30890807.v1
title: Supplementary Material for: A Novel Missense Mutation in a Compound Heterozygous Patient with Fish-Eye Disease: A Case Report

description: Introduction: Fish-eye disease (FED) is a rare autosomal recessive disorder caused by a partial deficiency of lecithin-cholesterol acyltransferase (LCAT) activity. It is characterized by progressive corneal opacification and dyslipidemia in the absence of systemic manifestations. We describe the clinical presentation, optical coherence tomography (OCT) imaging findings, and Scheimpflug-based corneal densitometry results in a patient with FED carrying both a pathogenic variant and a novel missense variant of the LCAT gene not reported in the current literature.

Case Presentation: We present a rare case of a 25-year-old female with bilateral corneal opacities, reduced plasma high-density lipoprotein cholesterol (&lt; 5 mg/dL), and elevated low-density lipoprotein cholesterol levels (&gt; 133 mg/dL). Visual acuity remained 20/20 in both eyes. Slit-lamp examination revealed diffuse subepithelial and anterior stromal deposits. The central corneal thickness was thinner than normal on Scheimpflug tomography, measuring 419 µm OD and 409 µm OS. OCT findings confirmed stromal thinning (479 µm OD and 470 µm OS), with preserved central epithelial thickness, and demonstrated corneal opacities throughout the cornea. The cholesteryl ester–to–total cholesterol ratio remained within normal range. Genetic analysis identified a previously reported pathogenic variant in exon 4 of LCAT (c.440C&gt;T, p.Thr147Ile) and a novel missense mutation in exon 5 (c.715G&gt;A, p.Gly239Ser), classified as a variant of uncertain significance.

Conclusion: FED is a rare genetic disorder that is associated with corneal clouding and dyslipidemia. Genetic analysis confirmed the diagnosis with a compound heterozygous genotype, while OCT and corneal densitometry were effective modalities for quantifying and characterizing lipid deposits in FED.
DOI: 10.25909/22875374
title: APPF TPA phenotyping dataset: UA TPA (Tanner) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tanner)
DOI: 10.25909/22875374.v1
title: APPF TPA phenotyping dataset: UA TPA (Tanner) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tanner)
DOI: 10.25909/22875380
title: APPF TPA phenotyping dataset: UA TPA (Tanner) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tanner)
DOI: 10.25909/22875380.v1
title: APPF TPA phenotyping dataset: UA TPA (Tanner) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tanner)
DOI: 10.25909/22875383
title: APPF TPA phenotyping dataset: UA TPA (Tester, Berger) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tester, Berger) ending 2011-07-27
DOI: 10.25909/22875383.v1
title: APPF TPA phenotyping dataset: UA TPA (Tester, Berger) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA TPA (Tester, Berger) ending 2011-07-27
DOI: 10.6084/m9.figshare.30890810
title: Supplementary Material for: Distinct Mortality Risks in Generalized Pustular Psoriasis and Palmoplantar Pustulosis: A Nationwide, Population-based, Cohort Study

description: Introduction: The differences in all-cause and cause-specific mortality among patients with generalized pustular psoriasis (GPP), palmoplantar pustulosis (PPP), and psoriasis vulgaris (PV) are not well understood. The aim of our study was to compare all-cause and cause-specific mortality in patients with GPP, PPP, and PV.
Methods: We conducted a nationwide, retrospective cohort study using data from the Korean National Health Insurance Service and National Death Registry between 2002 and 2022. Patients with GPP, PPP, and PV aged ≥18 years were identified based on ≥3 visits with principal diagnosis codes. Baseline characteristics, including demographics, general health data, socioeconomic status, and comorbidity profiles, were balanced using inverse probability weighting. Participants were followed-up from the index date until the occurrence of death, emigration, or the end of the observation period to investigate all-cause and cause-specific mortality.
Results: Multivariate regression analysis showed that patients with GPP had significantly higher all-cause mortality than those with PV (adjusted hazard ratio [aHR], 1.23; 95% confidence interval [CI], 1.20–1.25), while patients with PPP had lower all-cause mortality (aHR, 0.89; 95% CI, 0.87–0.91). GPP was associated with higher cause-specific mortality, particularly from hematologic (aHR, 1.76; 95% CI, 1.27–2.44) and respiratory diseases (aHR, 1.37; 95% CI, 1.30–1.46), whereas PPP patients had lower mortality from gastrointestinal (aHR, 0.57; 95% CI, 0.52–0.63) and infectious diseases (aHR, 0.71; 95% CI, 0.63–0.80). Subgroup and sensitivity analyses confirmed these findings.
Conclusions: GPP is associated with higher all-cause and cause-specific mortality than PV, while PPP is linked to lower mortality, indicating potential epidemiological and biological differences among these subtypes.
DOI: 10.6084/m9.figshare.30890810.v1
title: Supplementary Material for: Distinct Mortality Risks in Generalized Pustular Psoriasis and Palmoplantar Pustulosis: A Nationwide, Population-based, Cohort Study

description: Introduction: The differences in all-cause and cause-specific mortality among patients with generalized pustular psoriasis (GPP), palmoplantar pustulosis (PPP), and psoriasis vulgaris (PV) are not well understood. The aim of our study was to compare all-cause and cause-specific mortality in patients with GPP, PPP, and PV.
Methods: We conducted a nationwide, retrospective cohort study using data from the Korean National Health Insurance Service and National Death Registry between 2002 and 2022. Patients with GPP, PPP, and PV aged ≥18 years were identified based on ≥3 visits with principal diagnosis codes. Baseline characteristics, including demographics, general health data, socioeconomic status, and comorbidity profiles, were balanced using inverse probability weighting. Participants were followed-up from the index date until the occurrence of death, emigration, or the end of the observation period to investigate all-cause and cause-specific mortality.
Results: Multivariate regression analysis showed that patients with GPP had significantly higher all-cause mortality than those with PV (adjusted hazard ratio [aHR], 1.23; 95% confidence interval [CI], 1.20–1.25), while patients with PPP had lower all-cause mortality (aHR, 0.89; 95% CI, 0.87–0.91). GPP was associated with higher cause-specific mortality, particularly from hematologic (aHR, 1.76; 95% CI, 1.27–2.44) and respiratory diseases (aHR, 1.37; 95% CI, 1.30–1.46), whereas PPP patients had lower mortality from gastrointestinal (aHR, 0.57; 95% CI, 0.52–0.63) and infectious diseases (aHR, 0.71; 95% CI, 0.63–0.80). Subgroup and sensitivity analyses confirmed these findings.
Conclusions: GPP is associated with higher all-cause and cause-specific mortality than PV, while PPP is linked to lower mortality, indicating potential epidemiological and biological differences among these subtypes.
DOI: 10.25909/22875386
title: APPF TPA phenotyping dataset: UCopenhagen (Jall) - Maize

description: Images and data from maize phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UCopenhagen (Jall) ending 2016-11-28
DOI: 10.25909/22875386.v1
title: APPF TPA phenotyping dataset: UCopenhagen (Jall) - Maize

description: Images and data from maize phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UCopenhagen (Jall) ending 2016-11-28
DOI: 10.25909/22875392
title: APPF TPA phenotyping dataset: Uni Sask (Beattie, Murrell) - Barley

description: Images and data from barley phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of Uni Sask (Beattie, Murrell) ending 2011-12-07
DOI: 10.25909/22875392.v1
title: APPF TPA phenotyping dataset: Uni Sask (Beattie, Murrell) - Barley

description: Images and data from barley phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of Uni Sask (Beattie, Murrell) ending 2011-12-07
DOI: 10.25909/22875395
title: APPF TPA phenotyping dataset: Uni Sask (Taran) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of Uni Sask (Taran) ending 2011-11-24
DOI: 10.25909/22875395.v1
title: APPF TPA phenotyping dataset: Uni Sask (Taran) - Chickpea

description: Images and data from chickpea phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of Uni Sask (Taran) ending 2011-11-24
DOI: 10.25909/22875398
title: APPF TPA phenotyping dataset: UniSA (Seiffert, Berger) - Various

description: Images and data from various phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UniSA (Seiffert, Berger) ending 2013-01-31
DOI: 10.25909/22875398.v1
title: APPF TPA phenotyping dataset: UniSA (Seiffert, Berger) - Various

description: Images and data from various phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UniSA (Seiffert, Berger) ending 2013-01-31
DOI: 10.25909/22875401
title: APPF TPA phenotyping dataset: UniSA (Cai) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UniSA (Cai) ending 2013-10-09
DOI: 10.25909/22875401.v1
title: APPF TPA phenotyping dataset: UniSA (Cai) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UniSA (Cai) ending 2013-10-09
DOI: 10.25909/22875407
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Cousins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Cousins) ending 2017-07-31
DOI: 10.25909/22875407.v1
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Cousins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Cousins) ending 2017-07-31
DOI: 10.25909/22875410
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Hue) - Tomato

description: Images and data from tomato phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Hue)
DOI: 10.25909/22875410.v1
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Hue) - Tomato

description: Images and data from tomato phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Hue)
DOI: 10.25909/22875413
title: APPF TPA phenotyping dataset: UA (Cavagnaro) - Tomato

description: Images and data from tomato phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro) ending 2017-04-20
DOI: 10.25909/22875413.v1
title: APPF TPA phenotyping dataset: UA (Cavagnaro) - Tomato

description: Images and data from tomato phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro) ending 2017-04-20
DOI: 10.25909/22875416
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Watts-Williams) - Medic

description: Images and data from medic phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Watts-Williams) ending 2017-11-28
DOI: 10.25909/22875416.v1
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Watts-Williams) - Medic

description: Images and data from medic phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Watts-Williams) ending 2017-11-28
DOI: 10.25909/22875422
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Watts-Williams) - Medic (calibration)

description: Images and data from medic phenotyping studies (calibration) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Watts-Williams) ending 2017-12-19
DOI: 10.25909/22875422.v1
title: APPF TPA phenotyping dataset: UA (Cavagnaro, Watts-Williams) - Medic (calibration)

description: Images and data from medic phenotyping studies (calibration) performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Cavagnaro, Watts-Williams) ending 2017-12-19
DOI: 10.25909/22875425
title: APPF TPA phenotyping dataset: UA (Solomon) - Maize

description: Images and data from maize phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Solomon)
DOI: 10.25909/22875425.v1
title: APPF TPA phenotyping dataset: UA (Solomon) - Maize

description: Images and data from maize phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA (Solomon)
DOI: 10.25909/22875428
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2012-09-18
DOI: 10.25909/22875428.v1
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2012-09-18
DOI: 10.25909/22875431
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2012-03-27
DOI: 10.25909/22875431.v1
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2012-03-27
DOI: 10.25909/22875437
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2013-03-26
DOI: 10.25909/22875437.v1
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2013-03-26
DOI: 10.25909/22875443
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2013-10-28
DOI: 10.25909/22875443.v1
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2013-10-28
DOI: 10.25909/22875446
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2015-04-01
DOI: 10.25909/22875446.v1
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2015-04-01
DOI: 10.25909/22875449
title: APPF TPA phenotyping dataset: UA ACPFG (Collins) - Wheat

description: Images and data from wheat phenotyping studies performed at the APPF Plant Accelerator (TPA), University of Adelaide, on behalf of UA ACPFG (Collins) ending 2012-09-27