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However, biophysical and ecophysiological constraints during vegetative growth are also at play and can strongly impact crop phenotypes. It has been argued that a broadened examination of crop phenotypes through a functional trait-based lens should improve our understanding of the domestication syndrome.2. We used a collection of 39 genotypes representative of key steps during tetraploid wheat domestication and grew them in a common garden experiment. We quantified the vegetative phenotype of each genotype through the measurements of 13 functional traits related to root, leaf and whole-plant dimensions.3. In modern cultivars, compared to ancestral forms, leaf longevity was shorter, while net photosynthetic rate, leaf production rate and nitrogen content were higher.Modern cultivars had a shallower root system and exhibited a larger proportion of fine roots, preferring to invest biomass above-rather than below-ground. We found ancestral forms to be integrated phenotypes characterized by coordination between above-and below-ground functioning. Conversely, in modern forms, human selection appeared to have broken this coordination and to have generated a new type of network of trait covariations.

The normalized difference vegetation index (NDVI) continues to provide easy and fast methodologies to characterize wheat genetic resources in response to abiotic stresses. This study identifies ways to maximize green leaf area duration during grain filling and develops NDVI models to predict physiological maturity and different stay-green parameters to increase grain yield of rainfed winter wheat under terminal drought. Three wheat populations were evaluated: one containing 240 landraces from Afghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall conditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one year in the same location). The onset of senescence, maximum "greenness", rate of senescence and residual "greenness" at physiological maturity were estimated using sequential measurements of NDVI and have shown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs were identified among the different stay-green attributes, e.g. delayed onset of senescence and high maximum "greenness" resulted in accelerated rates of senescence and highest yields and were most evident in the landrace populations. It is concluded, that the use of rate of senescence to select for staygreen must be coupled with other stay-green components, e.g. onset of senescence or maximum "greenness" to avoid the effects of the trade-offs on final grain yield. The NDVI decay curves (using the last three NDVI measurements up to maturity) were used to estimate days to maturity using the NDVI decay during the senescence period and days to heading. A training and testing set (20 and 80% of each population, respectively) were used for calibrations allowing for correlations between predicted and observed maturity of up to r=+0.85 (P<0.0001). This procedure will facilitate large-scale wheat phenotyping in the future.

Tomato (Solanum lycopersicum) quality traits such as juice soluble solid content (Brix), juice pH, color parameters (Hue and Chroma), firmness and water content, are critical factors for fruit quality assessment. The need for screening very large numbers of fruit has led to the development of a high-throughput method using visible-near infrared (VIS-NIR) spectrometry. We are reporting here a set of results obtained with a portable spectrometer using the 350-2500 nm range, showing good prediction of the quality traits cited above, over a wide range of developmental stages from immature green to ripe tomato fruit, cv. Micro-Tom. This is a rather good set of quality traits compared to previous publications predicting tomato quality with VIS-NIR spectrometry, and the prediction is robust, as it was obtained by grouping sets of different operators. This would be a useful tool to phenotype hundreds of Micro-Tom per day, making it possible to follow the dynamics of the described parameters on growing fruits. Thus the method can be used to study the biochemistry and physiology of fruit development in planta.

1. Ecological theories suggest that higher plant genetic diversity can increase productivity in natural ecosystems. So far, varietal mixtures, that is, the cultivation of different genotypes within a field, have shown contrasting results, notably for grain yield where both positive and negative mixing effects have been reported.

In wheat (Triticum spp.), the N content of leaves during the grain filling period (GFP) plays a key role in maintaining photosynthetic activity and determining the amount of N available for grain protein content (GPC). We documented flag N leaf resorption in durum wheat (Triticum turgidum L.) plants under a nonlimiting level of N in 2010 and under two different levels of N fertilization in 2011. During the GFP, we monitored changes in flag leaf N content by a nondestructive method based on near‐infrared spectroscopy. The datasets were modeled for each plant; parameters were extracted and analyzed to determine which source of variation (genotype and/or N availability) predominated. Different genotypic profiles were highlighted opposing Ixos versus Primadur when comparing two different levels of N availability, with Ixos flag leaves being the most affected by a low level of N preanthesis. High postanthesis N availability delayed the beginning of N resorption (t0) and there was a strong negative correlation between t0 and the resorption duration. Delayed N resorption was associated with better grain yield components. A high proportion of the variation of grain yield per spike and GPC was explained by multiple linear regressions combining the width of the flag leaf and N dynamic parameters under the nonlimiting N availability. The negative correlation between yield and GPC may result from the initiation of N resorption during grain filling, potentially increasing yield if delayed or increasing GPC if occurring early.

AGAP : équipe GE2pop (Génomique évolutive et gestion des populations)Light propagation modeling in 3-dimensional virtual scenes has been successfully applied to many fields, including plant canopies. However, its application to detailed analyses on how multiple scattering affects spectral-based biochemistry assessments has never been proposed. In this article, a wheat canopy model has been built using simulation models included in the open source software platform Open-Alea. Adel-Wheat, a 3D dynamic model of the aerial growth of winter wheat, has been associated with spectra collected on wheat leaves with an ASD spectrometer, and then used as input of the Caribu light propagation model. Caribu calculates the proportion of direct and scattered light for all polygons of the 3D scene. Principal component analysis was first applied to analyze the distribution of resulting spectra in the spectral feature space. Then the influence of canopy structure on quantitative regression models has been considered. For this purpose, a typical agronomical problem, i.e. nitrogen content retrieval, was addressed, using a Partial Least Square regression model. This study exhibits some important results concerning the distribution of collected spectra in the spectral feature space due to multiple scattering, and underlines the physical interpretation of these results. In the short term, it shows that satisfactory nitrogen content prediction (error about 0.5% of dry matter) can be obtained at the plant level, when considering only the plant top leaves. Moreover, its paves the way for future researches to develop spectral analysis tools able to overcome such multiple scattering phenomena