Dataset Information

Data on agronomic traits, biochemical composition of lipids, proteins and polysaccharides and rheological measurement in a brown mustard seed collection.

ABSTRACT: The data were collected from a brown mustard seeds collection of 18 accessions during two years and in three distinct sites of production in France. The 18 accessions of mustard seeds were selected to be representative of genetic, agronomical and technological variabilities. All accessions were produced in the "Bourgogne" area. This article describes agronomical data (PMG, yield), genotyping data, global composition of mustard seeds (lipids, proteins and polysaccharides) and fine composition of the previous macronutrients potentially involved in the technological properties (fatty acids, storage proteins and osidic composition of polysaccharides). Additional data regarding the potential rheological property of each accessions were also reported. These data can be reused by food industries, breeders and geneticists in order to understand pedoclimatic effects (year and location) and the relation between mustard seed composition and the end-uses properties (paste mustard quality).

SUBMITTER: Le Gall S

PROVIDER: S-EPMC8487003 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Data on agronomic traits, biochemical composition of lipids, proteins and polysaccharides and rheological measurement in a brown mustard seed collection.

Le Gall Sophie S Sole-Jamault Véronique V Nars-Chasseray Marine M Le Goff Aude A Le Bot Lucie L Guinet Thierry T Renaud Christelle C Gervais Jérôme J Bansard Stéphane S Ohleyer Laure L Jeandroz Sylvain S

Data in brief 20210924

The data were collected from a brown mustard seeds collection of 18 accessions during two years and in three distinct sites of production in France. The 18 accessions of mustard seeds were selected to be representative of genetic, agronomical and technological variabilities. All accessions were produced in the "<i>Bourgogne</i>" area. This article describes agronomical data (PMG, yield), genotyping data, global composition of mustard seeds (lipids, proteins and polysaccharides) and fine composit ...[more]

PMID: 34632015

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Project description:ContextAgronomic data such as applied inputs, management practices, and crop yields are needed for assessing productivity, nutrient balances, resource use efficiency, as well as other aspects of environmental and economic performance of cropping systems. In many instances, however, these data are only available at a coarse level of aggregation or simply do not exist.ObjectivesHere we developed an approach that identifies sites for agronomic data collection for a given crop and country, seeking a balance between minimizing data collection efforts and proper representation of the main crop producing areas.MethodsThe developed approach followed a stratified sampling method based on a spatial framework that delineates major climate zones and crop area distribution maps, which guides selection of sampling areas (SA) until half of the national harvested area is covered. We provided proof of concept about the robustness of the approach using three rich databases including data on fertilizer application rates for maize, wheat, and soybean in Argentina, soybean in the USA, and maize in Kenya, which were collected via local experts (Argentina) and field surveys (USA and Kenya). For validation purposes, fertilizer rates per crop and nutrient derived at (sub-) national level following our approach were compared against those derived using all data collected from the whole country.ResultsApplication of the approach in Argentina, USA, and Kenya resulted in selection of 12, 28, and 10 SAs, respectively. For each SA, three experts or 20 fields were sufficient to give a robust estimate of average fertilizer rates applied by farmers. Average rates at national level derived from our approach compared well with those derived using the whole database ( ± 10 kg N, ± 2 kg P, ± 1 kg S, and ± 5 kg K per ha) requiring less than one third of the observations.ConclusionsThe developed minimum crop data collection approach can fill the agronomic data gaps in a cost-effective way for major crop systems both in large- and small-scale systems.SignificanceThe proposed approach is generic enough to be applied to any crop-country combination to guide collection of key agricultural data at national and subnational levels with modest investment especially for countries that do not currently collect data.

Dataset Information

Data on agronomic traits, biochemical composition of lipids, proteins and polysaccharides and rheological measurement in a brown mustard seed collection.

Publications

Data on agronomic traits, biochemical composition of lipids, proteins and polysaccharides and rheological measurement in a brown mustard seed collection.

Similar Datasets

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