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Beaucouzé, France

Pierre J.,Agrocampus Ouest | Teulat B.,Agrocampus Ouest | Juchaux M.,University of Angers | Mabilleau G.,University of Angers | And 2 more authors.
Plant Science

Hypocotyl growth is a key characteristic for plant emergence, influenced by environmental conditions, particularly temperature, and varying among genotypes. Cellular changes in Medicago truncatula hypocotyl were characterized to study the impact of the environment on heterotrophic growth and analyze differences between genotypes. The number and length of epidermal cells, ploidy levels, and sugar contents were measured in hypocotyls grown in the dark at 20. °C and 10. °C using two genotypes with contrasting maximum hypocotyl length. Hypocotyl elongation in the dark was due to cell elongation and not to an increase in cell number. A marked increase in cell ploidy level was observed just after germination and until mid elongation of the hypocotyl under all treatments. Larger ploidy levels were also observed in the genotype with the shorter hypocotyl and in cold conditions, but they were associated with larger cells. The increase in ploidy level and in cell volume was concomitant with a marked increase in glucose and fructose contents in the hypocotyl. Finally, differences in hypocotyl length were mainly due to different number of epidermal cells in the seed embryo, shown as a key characteristic of genotypic differences, whereas temperature during hypocotyl growth affected cell volume. © 2013 Elsevier Ireland Ltd. Source

Matthews S.,University of Aberdeen | Noli E.,University of Bologna | Demir I.,Ankara University | Khajeh-Hosseini M.,Ferdowsi University of Mashhad | Wagner M.-H.,GEVES
Seed Science Research

Seed quality standards enable seed users to achieve their objectives in the establishment of uniform seedlings to a high and reliable level for a range of agricultural and horticultural crops, growing systems and market outlets. Quality standards of commercial seed lots are determined by their positions on the seed survival curves and the shape of their germination progress curves. Although comparative descriptions of germination curves can be achieved by the calculation of the mean germination time (MGT; delay to radicle emergence), single early counts of radicle emergence provide a convenient means of predicting MGT and differences between seed lots. Evidence is presented for an ageing and metabolic repair hypothesis as the overall physiological basis to explain the principles behind the standard germination and vigour tests (ageing, electrolyte leakage, cold test, germination rate and seedling size). The work of the International Seed Testing Association (ISTA) in developing convenient, inexpensive and internationally repeatable tests is illustrated. © 2012 Cambridge University Press. Source

Matthews S.,University of Aberdeen | Wagner M.-H.,GEVES | Kerr L.,Alexander Harley Seeds Milnathort Ltd. | McLaren G.,SASA | Powell A.A.,University of Aberdeen
Seed Science and Technology

The objective of the work was to develop a routine vigour test indicative of the relative field emergence of commercial seed lots of winter oilseed rape. The potential for a vigour test based on rate of radicle emergence (RE) was examined. The germination progress curves of nine lots (cv. Vision) were determined at 20°C using an automated system which captured RE images every two hours for 72 hours. Each curve was described by its mean germination time (MGT), which is the average lag period (delay) from the start of imbibition to RE. MGT was indicative of 7-day field emergence (R2 = 0.930) and maximum emergence of the lots (R2 = 0.745). The automated single counts suggested that the 24- and 30-hour counts were the appropriate timings for comparisons across three laboratories in standard germination tests in pleated paper at 20°C. The mean counts, particularly those at 30 hours, from the three laboratories predicted MGT (R2 = 0.920), 7-day emergence (R2 = 0.961) and maximum emergence (R2 = 0.713). A similar ranking of the lots in terms of their RE counts was seen at 13°C after 48 hours in rolled towels. The counts were reproducible between laboratories, all R2 between laboratories being greater than 0.930. The time to RE was closely related to total germination after controlled deterioration, which gives a measure of seed age. The possibility that the slow rate of RE in low vigour seed may result from more time being needed for repair of deterioration in aged seeds is discussed. A routine vigour test at 20°C in which RE is counted at 30 hours, possibly in a standard germination test, is suggested. Counts of RE could be done either manually or by an automated system such as the one described. Source

Benoit L.,University of Notre Dame | Belin T.,University of Notre Dame | Durr C.,CNRS Research Institute on Horticulture and Seeds | Chapeau-Blondeau F.,University of Notre Dame | And 3 more authors.
Computers and Electronics in Agriculture

This article proposes a computer-vision based protocol, useful to contribute to high-throughput automated phenotyping of seedlings during elongation, the stage following germination. Radicle and hypocotyl are two essential organs which start to develop at this stage, with the hypocotyl growing towards the soil surface and the radicle exploring deeper layers for nutrient absorption. Early identification and measurement of these two organs are important to the characterization of the plant emergence and to the prognosis of the adult plant. In normal conditions, this growth process of radicle and hypocotyl takes place in the soil, in the dark. Identification and measurement of these two organs are therefore challenging, because they need to be achieved with no light that could alter normal growth conditions. We propose here an original protocol exploiting an inactinic green light, produced by a controlled LED source, coupled to a standard low-cost gray-level camera. On the resulting digital images, we devise a simple criterion based on gravitropism and amenable to direct computer implementation. The automated criterion, through comparison with the performance of human experts, is demonstrated to be efficient for the detection and separation of radicle and hypocotyl, and generic for various species of seedlings. Our protocol especially brings improvement in terms of cost reduction over the current method found in the recent literature which resorts to higher-cost passive thermal imaging to perform the same task in the dark, and that we also consider here for comparison. Our protocol connected to automation of image acquisition, can serve to improve high-throughput phenotyping equipments for analysis of seed quality and genetic variability. © 2014 Elsevier B.V. Source

Durr C.,French National Institute for Agricultural Research | Constantin J.,French National Institute for Agricultural Research | Wagner M.-H.,GEVES | Navier H.,French National Institute for Agricultural Research | And 3 more authors.
European Journal of Agronomy

Breeding oilseed rape for oil and protein contents may have led to differences in seedling emergence in genotypes. New opportunities for deep automated phenotyping of germination and seedling growth are being developed on phenotyping platforms. Our aim was to demonstrate that using these data to parameterize a crop emergence model complements field experiments for the evaluation of differences among genotypes. Five genotypes, chosen in a diverse set of winter oilseed rape for their different germination speeds, were phenotyped for germination at different temperatures and water potentials as well as for radicle and hypocotyl growth. These data were used as parameters to run the SIMPLE crop emergence model over a period of 27 years (1985-2012), at two locations, one in France and one in Germany, and at four sowing dates. Field experiments were performed in 2012, 2013 and 2014, and the emergence of the five genotypes was measured at early and late sowing dates. First, model predictions were compared with observed field emergence in the French sowing trials in 2014. The model proved to be rather good at predicting the emergence of the genotypes. Then, for the simulation study, the model extended the observed differences between locations and sowing dates over a greater number of years. The model also identified the main reasons for non-emerging seedlings and their frequencies in the simulated sowings. Differences between the five genotypes were on average very small, but complex interactions appeared that led to bigger differences under certain sowing conditions. This study demonstrates that combining deep phenotyping with crop models in simulation studies paves the way for more precise and detailed evaluation of genotypes. © 2016 Elsevier B.V.. Source

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