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1. Is low-input management system a good selection environment to screen winter wheat genotypes adapted to organic farming?

Author

Stephane Gilles, Olivier Gardet, Jean-Yves Morlais, Francois-Xavier Oury, Paul Bataillon, Patrice Walczak, Bernard Rolland, Alexandre Pichard, Antonin-Pierre Le Campion, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Fourrages Environnement Ruminants Lusignan (FERLUS), Institut National de la Recherche Agronomique (INRA), Domaine expérimental d'Auzeville (UE AUZEVILLE), Agri Obtentions (AO), Guyancourt, French Technical Institute for Organic farming (ITAB, network coordinated by Laurence Fontaine) , InterBio Bretagne as part of the State-Region (Brittany), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de la Recherche Agronomique (INRA), UE 1373 Fourrages Environnement Ruminants Lusignan, Institut National de la Recherche Agronomique (INRA)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Environnement et Agronomie (E.A.)-Biologie et Amélioration des Plantes (BAP)-Fourrages Environnement Ruminants Lusignan (FERLUS), Agri-Obtentions, and Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST

Subjects
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 2. Zero hunger, Genetic diversity, Organic farming, business.industry, Breeding strategy, Plant Science, 15. Life on land, Horticulture, Biology, Weed control, Efficiency, Agronomy, Agriculture, Genotype, Genetics, Indirect selection, Relative selection efficiency, Plant breeding, Low-input management systems, business, Agronomy and Crop Science, Cropping
Abstract

International audience; The move toward resilient and productive agriculture requires, among other innovations, the design of new sustainable farming systems in which the variety plays a main role. Plant breeding strategies adapted to organic farming conditions have to deal with limiting factors. Whereas in north-west France, it is known that trials carried out under high-input management do not give a good prediction of genotype performance in organic conditions, less is known about the relative stability of wheat genotypes between low-input (LI) and organic cropping systems. A retrospective analysis of 34 winter wheat trials conducted from 2004 to 2011 was performed to determine whether data obtained on genotypes grown under LI conditions can be used to predict genotype performance in organic (ORG) target conditions. Every year, ORG and LI (no fungicide or growth regulators, N balance sheet-60 kgN/ha, weed control with herbicides) trials including 25-30 genotypes describing a large range of genetic diversity were sown in three different agro-climatic regions across north-west France. Genotype performance in ORG management system was reduced from 25 to 40 % for yield and from 10 to 22 % for grain protein content. Estimates of genotypic values appeared to be more precise under LI than ORG conditions. Because of high genetic correlations between LI and ORG conditions, the relative efficiency of indirect selection from LI to ORG conditions was approximately 1. Spearman's rank correlations were high (Rs = 0.54-0.92) and genotype rank inversions generally had a minor extent. However, in 2005 and 2010, almost 50 % of the lines had to be retained in LI to keep 80 % of the top 20 % of genotypes in organic conditions. Compared with previous results from high-input conditions, LI management provided a better prediction of genotype performance under ORG conditions but crossover genotype x management interactions could be observed between both systems. Overall, combining information provided from both LI and ORG crop management systems appears to be a good process for building efficient and adapted breeding schemes for ORG farming conditions.

Published
2014
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2. From selection to cultivation with the support of all stakeholders: the first registration in France of two winter bread wheat varieties after value for cultivation and use evaluation in organic farming systems

Author

Patrice Walczak, A. Le Campion, Olivier Gardet, L. Fontaine, Francois-Xavier Oury, Emmanuel Heumez, A. Mailliard, Bernard Rolland, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Institut Technique de l'Agriculture Biologique (ITAB), SEV, Groupe d'Etudes et de Contrôle des Variétés et des Semences (GEVES), Agri Obtentions (AO), Domaine expérimental de Brunehaut (LILL MONS UE), Institut National de la Recherche Agronomique (INRA), Fourrages Environnement Ruminants Lusignan (FERLUS), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), AGROCAMPUS OUEST-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA), Agri-Obtentions, UE 1373 Fourrages Environnement Ruminants Lusignan, Institut National de la Recherche Agronomique (INRA)-Physiologie Animale et Systèmes d'Elevage (PHASE), Institut National de la Recherche Agronomique (INRA)-Environnement et Agronomie (E.A.)-Biologie et Amélioration des Plantes (BAP)-Fourrages Environnement Ruminants Lusignan (FERLUS), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Cash crop, 01 natural sciences, Agricultural science, winter bread wheat, organic farming, plant breeding, Production (economics), Plant breeding, Cultivar, 2. Zero hunger, Sustainable development, business.industry, value for cultivation and use (VCU), 04 agricultural and veterinary sciences, 15. Life on land, variety, Agronomy, Intensive crop farming, Agriculture, 040103 agronomy & agriculture, Organic farming, 0401 agriculture, forestry, and fisheries, General Agricultural and Biological Sciences, business, 010606 plant biology & botany
Abstract

International audience; Winter bread wheat is the most important cash crop for French organic farmers. The choice of its varieties farmers cultivate is therefore very important. Most of the available varieties were initially bred for intensive “conventional” farming systems (with high inputs of mineral fertilizers and pesticides). Thus, screening current and novel varieties for organic conditions is necessary to identify varieties suitable for organic farming conditions in a short-term experiment. After 18 years of breeding and screening in a combination of both low input and organic crop management systems, the two pure lines Hendrix and Skerzzo were registered in the official French catalogue with the special mention “organic farming.” The acreages of commercial seed production to be sold to organic farmers continuously increased from 120, 139 to 160 ha in 2013, 2014, and 2015, respectively. This successful process was made possible due to the support of the whole agricultural organic economic sector associated with the initiative.

Published
2017
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3. Bread wheat milling behavior: effects of genetic and environmental factors, and modeling using grain mechanical resistance traits

Author

Joel Abecassis, Emmanuel Heumez, Valerie Lullien-Pellerin, Bernard Rolland, Arnaud Dubat, C. Bar L’Helgouac’h, Francois-Xavier Oury, C. Michelet, Olivier Gardet, M. Rousset, Privat Lasme, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Ingénierie des Agro-polymères et Technologies Émergentes (UMR IATE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université Montpellier 2 - Sciences et Techniques (UM2)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université de Montpellier (UM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Union Française des Semenciers (UFS), Chopin Technologies, Agri-Obtentions, Domaine expérimental de Brunehaut (LILL MONS UE), Institut National de la Recherche Agronomique (INRA), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), AGROCAMPUS OUEST-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA), Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), ARVALIS - Institut du végétal [Paris], FSOV (Fonds de Soutien a l'Obtention Vegetale) 2007-2010, research consortium 'Valeur Meuniere II', Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Agri Obtentions (AO), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), a CIFRE PhD grant, and Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Université Montpellier 2 - Sciences et Techniques (UM2)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)

Subjects
0106 biological sciences, Yield (engineering), ble tendre, Flour, Biology, Environment, Genes, Plant, 01 natural sciences, Endosperm, wheat flour, Protein content, Grain weight, 0404 agricultural biotechnology, Hardness, [SDV.IDA]Life Sciences [q-bio]/Food engineering, Genetics, strength of materials, Food science, grain de blé, Alleles, Triticum, 2. Zero hunger, Models, Genetic, digestive, oral, and skin physiology, technology, industry, and agriculture, food and beverages, 04 agricultural and veterinary sciences, General Medicine, Mechanical resistance, 040401 food science, farine de blé, résistance mécanique, Test weight, Nitrogen fertilizer, Agronomy, soft wheat, mouture, Seeds, milling, Edible Grain, Agronomy and Crop Science, 010606 plant biology & botany, Biotechnology
Abstract

International audience; Genetic (Pinb-D1 alleles) and environment (through vitreousness) have important effects on bread wheat milling behavior. SKCS optimal values corresponding to soft vitreous or hard mealy grains were defined to obtain the highest total flour yield.Near-isogenic lines of bread wheat that differ in hardness, due to distinct puroindoline-b alleles (the wild type, Pinb-D1a, or the mutated forms, Pinb-D1b or Pinb-D1d), were grown in different environments and under two nitrogen fertilization levels, to study genetic and environmental effects on milling behavior. Milling tests used a prototype mill, equipped with two break steps, one sizing step, and two reduction steps, and this enabled 21 individual or aggregated milling fractions to be collected. Four current grain characters, thousand grain weight, test weight, grain diameter, and protein content, were measured, and three characters known to influence grain mechanical resistance, NIRS hardness, SKCS hardness index, and grain vitreousness (a character affecting the grain mechanical behavior but generally not studied). As expected, the wild type or mutated forms of Pinb-D1 alleles led to contrasted milling behavior: soft genotypes produced high quantities of break flour and low quantities of reduction flour, whereas reverse quantities were observed for hard genotypes. This different milling behavior had only a moderate influence on total flour production. NIRS hardness and vitreousness were, respectively, the most important and the second most important grain characters to explain milling behavior. However, contrary to NIRS hardness, vitreousness was only involved in endosperm reduction and not in the separation between the starchy endosperm and the outer layers. The highest flour yields were obtained for SKCS values comprised between 30 and 50, which corresponded either to soft vitreous or hard mealy grains. Prediction equations were defined and showed a good accuracy estimating break and reduction flours portions, but should be used more cautiously for total flour.

Published
2017
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4. Estimation of genetic parameters of a DH wheat population grown at different N stress levels characterized by probe genotypes

Author

Olivier Gardet, Maryse Brancourt-Hulmel, Jacques Le Gouis, Anne Laperche, Emmanuel Heumez, Stress Abiotiques et Différenciation des Végétaux Cultivés (SADV), Institut National de la Recherche Agronomique (INRA)-Université de Lille, Sciences et Technologies, Transfrontalière BioEcoAgro - UMR 1158 (BioEcoAgro), Université d'Artois (UA)-Université de Liège-Université de Picardie Jules Verne (UPJV)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-JUNIA (JUNIA), Université catholique de Lille (UCL)-Université catholique de Lille (UCL), Unité Expérimentale Grandes Cultures Innovation Environnement - Picardie (GCIE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), unité experimentale Le Moulon, and Université de Lille, Sciences et Technologies-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
Yield (engineering), Genotype, Nitrogen, [SDV]Life Sciences [q-bio], Population, chemistry.chemical_element, Breeding, Environment, Biology, Animal science, Genetic variation, Botany, Genetics, Poaceae, education, Triticum, education.field_of_study, General Medicine, Straw, Heritability, Breed, chemistry, Regression Analysis, Agronomy and Crop Science, Biotechnology
Abstract

International audience; Low market prices and environmental concerns in Europe favor lower input wheat production systems. To efficiently breed for new varieties adapted to low input management while maintaining high yield levels, our objective was to characterize the heritability and its components for yield and nitrogen traits under different nitrogen levels. Two hundred and twenty-two doubled-haploid (DH) lines from the cross between Arche (tolerant) and Recital (sensitive) were tested in France at four locations in 2000, and three in 2001, under high (N+) and low (N-) nitrogen supplies. The response of yield to the environment of four probe genotypes, the parents and two controls, were tested and used as descriptors of these environments. Grain yield (GY), its components, and grain and straw nitrogen, called nitrogen traits, were studied. A factorial regression was performed to assess the sensitivity (slope) of the DH lines to nitrogen stress and their performance to low nitrogen supply. An index based on the nitrogen nutrition index at flowering of the probe genotype Recital was the best descriptor of the environment stress. Heritabilities of yield and nitrogen traits for both nitrogen supplies were always above 0.6. When nitrogen stress increased, heritabilities decreased and genotype x nitrogen interaction variances increased. The decrease in heritability was mainly explained by a decrease in genetic variance. Genetic variation for sensitivity to nitrogen stress and performance under low nitrogen supply were shown in the population. GY decreased from 278 to 760 g/m(2) per unit of nitrogen stress index increase and GY under moderate nitrogen stress varied from 340 to 613 g/m(2). Those contrasted reactions revealed specific lines to include in breeding programs for improving GY under low nitrogen supply.

Published
2006
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5. A study of genetic progress due to selection reveals a negative effect of climate change on bread wheat yield in France

Author

Aurélie Mailliard, Gilles Charmet, Jean-Yves Morlais, Francois-Xavier Oury, Maxime Trottet, M. Rousset, Alain Chassin, Bernard Rolland, Olivier Gardet, Emmanuel Heumez, Christelle Godin, Alex Giraud, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Génétique et Amélioration des Plantes, Institut National de la Recherche Agronomique (INRA), Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, UMR INRA / Univ. Bordeaux 1 / Univ. Bordeaux 2 : Physiologie et Biotechnologie Végétales, Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), AGROCAMPUS OUEST-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA)

Subjects
0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, Breeding program, Yield (finance), Soil Science, Climate change, Plant Science, Biology, 01 natural sciences, Bread wheat yield, Genetic progress, SPRING WHEAT, TRITICUM-AESTIVUM L, AGRONOMIC TRAITS, RICE, Productivity, TEMPERATURE, Selection (genetic algorithm), 2. Zero hunger, Resistance (ecology), LAND-USE, PRODUCTIVITY, 04 agricultural and veterinary sciences, Limiting, WINTER-WHEAT, TRENDS, MODERN CULTIVARS, Agronomy, 13. Climate action, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Agronomy and Crop Science, 010606 plant biology & botany, Linear trend
Abstract

International audience; In France, a stagnation of bread wheat yield has been observed since the middle of the 1990s, and the possibility of a decline in breeding progress has been questionned. To investigate this hypothesis, we have considered 2 independent long time series of yield data: one corresponding to the registration trials conducted in France from 1976 to 2010, and the other corresponding to trials from the INRA bread wheat breeding program along the 1970-2010 period. These raw data related to potential bread wheat yield in France, exhibited the same trend to stagnation as observed on national yield in the farms. However, after correction of the "year" effects, the corrected yields appeared to have increased regularly from the 1970s up to now, with quite a high rate in intensive conditions (from 0.065 t ha(-1) yr(-1) to 0.137 t ha(-1) yr(-1)). This linear trend for genetic progress was even higher without fungicide (from 0.097 t ha(-1) yr(-1) to 0.158 t ha(-1) yr(-1)), which could indicate that breeding efforts for productivity and for resistance to diseases tended to have additive results. The corrected yields also enabled us to point out a marked degradation of the agro-climatic potential of the different years. As our registration and breeding trials were as free as possible from agronomic limiting factors, it appeared that climatic factors constituted the main explanation to this degradation. Thus, our study demonstrated that since the end of the 1980s, genetic progress has been partly or totally counterbalanced by the adverse effects of climate change. (C) 2012 Elsevier B.V. All rights reserved.

Published
2012
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6. The prediction of bread wheat quality: joint use of the phenotypic information brought by technological tests and the genetic information brought by HMW and LMW glutenin subunits

Author

Annie Faye, Emmanuel Heumez, Alex Giraud, Francois-Xavier Oury, Gérard Branlard, Bernard Rolland, Hubert Chiron, Olivier Gardet, Maxime Trottet, M. Rousset, Gilles Charmet, Génétique Diversité et Ecophysiologie des Céréales (GDEC), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Institut National de la Recherche Agronomique (INRA), Unité de recherche sur les Biopolymères, Interactions Assemblages (BIA), Institut National de la Recherche Agronomique (INRA), Expérimentation et finition des variétés (VERS GRI UE EXP FINITION VARIE), Génétique et Ecophysiologie des Légumineuses à Graines (UMRLEG) (UMR 102), Etablissement National d'Enseignement Supérieur Agronomique de Dijon (ENESAD)-Institut National de la Recherche Agronomique (INRA)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Domaine expérimental de Brunehaut (LILL MONS UE), Amélioration des Plantes et Biotechnologies Végétales (APBV), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), FSOV (``Fonds de Soutien a l'Obtention Vegetale'), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Institut National de la Recherche Agronomique (INRA)-Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Etablissement National d'Enseignement Supérieur Agronomique de Dijon (ENESAD)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, AGROCAMPUS OUEST-Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Recherche Agronomique (INRA)

Subjects
0106 biological sciences, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, PREDICTION, Locus (genetics), Plant Science, END-USE QUALITY, Horticulture, 01 natural sciences, BREADMAKING, FLOUR QUALITY, 0404 agricultural biotechnology, Glutenin, PROTEIN-COMPOSITIION, RECOMBINANT, INBRED LINES, DEVELOPING GRAINS, Genetics, MAKING QUALITY, QUALITY, Plant breeding, Allele, 2. Zero hunger, GLUTENIN SUBUNITS, MOLECULAR-WEIGHT SUBUNITS, biology, BREAD WHEAT, 04 agricultural and veterinary sciences, 040401 food science, PHYSICAL DOUGH PROPERTIES, biology.protein, ALLELIC VARIATION, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

Attempts have been made to predict Chopin alveograph or French bread-making tests, using tree-based models and PLS regressions. Data came from three sets of trials, involving 130, 214 and 103 different genotypes, which were described for HMW-GS, LMW-GS and small-scale tests currently used in breeding programs. Segmentation trees and PLS regressions indicated that HMW-GS and LMW-GS were not sufficient to explain alone the variability of bread wheat quality. This could be partly due to “allele × environment” and “locus × locus” interactions. For HMW-GS, Glu-B1 was the predominant locus for alveograph and French bread-baking, and some differences in the alleles hierarchy were demonstrated according to the end-use parameter considered. For LMW-GS, Glu-B3 seemed to be preponderant, with alleles b′, c and g being favourable and allele c′ unfavourable. Joint use of the information brought by glutenin subunits and technological tests did not enable to predict satisfactorily, neither the different parameters of French bread-baking, nor the extensibility L of alveograph. Only the prediction of the strength W proved reliable, and robust PLS equations were proposed for this alveograph parameter. These prediction equations could be of interest to select for high values of W in the mid generations of breeding.

Published
2010
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7. Using genotype x nitrogen interaction variables to evaluate the QTL involved in wheat tolerance to nitrogen constraints

Author

Emmanuel Heumez, Eric Hanocq, F. Devienne-Barret, Maryse Brancourt-Hulmel, Jacques Le Gouis, Olivier Gardet, Anne Laperche, Stress Abiotiques et Différenciation des Végétaux Cultivés (SADV), Université de Lille, Sciences et Technologies-Institut National de la Recherche Agronomique (INRA), Environnement et Grandes Cultures (EGC), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Expérimentation et finition des variétés (VERS GRI UE EXP FINITION VARIE), Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-Université de Lille, Sciences et Technologies, and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
0106 biological sciences, Crops, Agricultural, Genotype, Nitrogen, Population, Quantitative Trait Loci, Quantitative trait locus, Biology, Interaction, 01 natural sciences, Chromosomes, Plant, 03 medical and health sciences, Animal science, Quantitative Trait, Heritable, Genetics, Poaceae, education, Crosses, Genetic, Triticum, 030304 developmental biology, 2. Zero hunger, Linkage (software), 0303 health sciences, education.field_of_study, [SDV.GEN]Life Sciences [q-bio]/Genetics, food and beverages, Chromosome Mapping, Genetic Variation, General Medicine, Dwarfing, Phenotype, Doubled haploidy, Agronomy and Crop Science, 010606 plant biology & botany, Biotechnology
Abstract

Lower market prices and environmental concerns now orientate wheat (Triticum aestivum L.) breeding programs towards low input agricultural practices, and more particularly low nitrogen (N) input management. Such programs require knowledge of the genetic determination of plant reaction to N deficiency. Our aim was to characterize the genetic basis of N use efficiency and genotype x N interactions. The detection of QTL for grain yield, grain protein yield and their components was performed on a mapping population of 222 doubled haploid lines (DH), obtained from the cross between an N stress tolerant variety and an N stress sensitive variety. Experiments on the population were carried out in seven different environments, and in each case under high (N(+)) and low (N(-)) N supplies. In total, 233 QTL were detected for traits measured in each combination of environment and N supply, for "global" interaction variables (N(+)-N(-) and N(-)/N(+)), for sensitivity to N stress and for performance under N-limited conditions which were assessed using factorial regression parameters. The 233 QTL were detected on the whole genome and clustered into 82 genome regions. The dwarfing gene (Rht-B1), the photoperiod sensitivity gene (Ppd-D1) and the awns inhibitor gene (B1) coincided with regions that contained the highest numbers of QTL. Non-interactive QTL were detected on linkage groups 3D, 4B, 5A1 and 7B2. Interactive QTL were revealed by interaction or factorial regression variables (2D2, 3D, 5A1, 5D, 6A, 6B, 7B2) or by both variables (1B, 2A1, 2A2, 2D1, 4B, 5A2, 5B). The usefulness of QTL meta-analysis and factorial regression to study QTL x N interactions and the impact of Rht-B1, Ppd-D1 and B1, are discussed.

Published
2006
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