Details
Originalsprache | Englisch |
---|---|
Aufsatznummer | 64 |
Seiten (von - bis) | 64 |
Seitenumfang | 13 |
Fachzeitschrift | Scientific data |
Jahrgang | 12 |
Ausgabenummer | 1 |
Publikationsstatus | Veröffentlicht - 14 Jan. 2025 |
Abstract
Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015-2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits. Beside grain yield, ten agronomic traits, four baking quality traits, plant height, heading date, maturity date and six fungal disease infection indices are included. Additionally, we provide management records, including fertilizer use, plant protection measures, irrigation, and weather data. We demonstrate how this dataset can address four agronomic questions related to GxExM interactions. Further potential applications of the dataset include empirical analyses, genomic and enviromic analyses for breeding targets, or development of decision-supporting models for agricultural management and policy decisions.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Statistik und Wahrscheinlichkeit
- Informatik (insg.)
- Information systems
- Sozialwissenschaften (insg.)
- Ausbildung bzw. Denomination
- Informatik (insg.)
- Angewandte Informatik
- Entscheidungswissenschaften (insg.)
- Statistik, Wahrscheinlichkeit und Ungewissheit
- Sozialwissenschaften (insg.)
- Bibliotheks- und Informationswissenschaften
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in: Scientific data, Jahrgang 12, Nr. 1, 64, 14.01.2025, S. 64.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Multi-environment field trials for wheat yield, stability and breeding progress in Germany
AU - Wang, Tien Cheng
AU - Rose, Till
AU - Zetzsche, Holger
AU - Ballvora, Agim
AU - Friedt, Wolfgang
AU - Kage, Henning
AU - Léon, Jens
AU - Lichthardt, Carolin
AU - Ordon, Frank
AU - Snowdon, Rod J.
AU - Stahl, Andreas
AU - Stützel, Hartmut
AU - Wittkop, Benjamin
AU - Chen, Tsu Wei
N1 - Publisher Copyright: © 2025. The Author(s).
PY - 2025/1/14
Y1 - 2025/1/14
N2 - Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015-2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits. Beside grain yield, ten agronomic traits, four baking quality traits, plant height, heading date, maturity date and six fungal disease infection indices are included. Additionally, we provide management records, including fertilizer use, plant protection measures, irrigation, and weather data. We demonstrate how this dataset can address four agronomic questions related to GxExM interactions. Further potential applications of the dataset include empirical analyses, genomic and enviromic analyses for breeding targets, or development of decision-supporting models for agricultural management and policy decisions.
AB - Multi-environmental trials (MET) with temporal and spatial variance are crucial for understanding genotype-environment-management (GxExM) interactions in crops. Here, we present a MET dataset for winter wheat in Germany. The dataset encompasses MET spanning six years (2015-2020), six locations and nine crop management scenarios (consisting of combinations for three treatments, unbalanced in each location and year) comparing 228 cultivars released between 1963 and 2016, amounting to a total of 526,751 data points covering 24 traits. Beside grain yield, ten agronomic traits, four baking quality traits, plant height, heading date, maturity date and six fungal disease infection indices are included. Additionally, we provide management records, including fertilizer use, plant protection measures, irrigation, and weather data. We demonstrate how this dataset can address four agronomic questions related to GxExM interactions. Further potential applications of the dataset include empirical analyses, genomic and enviromic analyses for breeding targets, or development of decision-supporting models for agricultural management and policy decisions.
UR - http://www.scopus.com/inward/record.url?scp=85215758787&partnerID=8YFLogxK
U2 - 10.1038/s41597-024-04332-7
DO - 10.1038/s41597-024-04332-7
M3 - Article
C2 - 39809815
AN - SCOPUS:85215758787
VL - 12
SP - 64
JO - Scientific data
JF - Scientific data
SN - 2052-4463
IS - 1
M1 - 64
ER -