Fabrice Davrieux

Quantitative trait loci for grain quality, productivity, morphological and agronomical traits in sorghum (#Sorghum bicolor# L. Moench)

Abstract Quantitative trait loci (QTLs) for grain quality, yield components and other traits were investigated in two Sorghum caudatum×guinea recombinant inbred line (RIL) populations. A total of 16 traits were evaluated (plant height, panicle length, panicle compactness, number of kernels/panicle, thousand-kernel weight, kernel weight/panicle, threshing percentage, dehulling yield, kernel flouriness, kernel friability, kernel hardness, amylose content, protein content, lipid content, germination rate and molds during germination and after harvest) and related to two 113- and 100-point base genetic maps using simple (SIM) and composite (CIM) interval mapping. The number, effects and relative position of QTLs detected in both populations were generally in agreement with the distributions, heritabilities and correlations among traits. Several chromosomal segments markedly affected multiple traits and were suspected of harbouring major genes. The positions of these QTLs are discussed in relation to previously reported studies on sorghum and other grasses. Many QTLs, depending on their relative effects and position, could be used as targets for marker-assisted selection and provide an opportunity for accelerating breeding programmes.

Effects of shade on the development and sugar metabolism of coffee (Coffea arabica L.) fruits.

Coffee fruits grown in shade are characterized by larger bean size than those grown under full-sun conditions. The present study assessed the effects of shade on bean characteristics and sugar metabolism by analyzing tissue development, sugar contents, activities of sucrose metabolizing enzymes and expression of sucrose synthase-encoding genes in fruits of coffee (Coffea arabica L.) plants submitted to full-sun (FS) and shade (SH) conditions. Evolution of tissue fresh weights measured in fruits collected regularly from flowering to maturation indicated that this increase is due to greater development of the perisperm tissue in the shade. The effects of light regime on sucrose and reducing sugar (glucose and fructose) contents were studied in fresh and dry coffee beans. Shade led to a significant reduction in sucrose content and to an increase in reducing sugars. In pericarp and perisperm tissues, higher activities of sucrose synthase (EC 2.4.1.13) and sucrose-phosphate synthase (SPS: EC 2.4.1.14) were detected at maturation in the shade compared with full sun. These two enzymes also had higher peaks of activities in developing endosperm under shade than in full sun. It was also noted that shade modified the expression of SUS-encoding genes in coffee beans; CaSUS2 gene transcripts levels were higher in SH than in FS. As no sucrose increase accompanied these changes, this suggests that sucrose metabolism was redirected to other metabolic pathways that need to be identified.

Near Infrared Spectroscopy for High-Throughput Characterization of Shea Tree (Vitellaria paradoxa) Nut Fat Profiles

The Shea tree (Vitellaria paradoxa) is a major tree species in African agroforestry systems. Butter extracted from its nuts offers an opportunity for sustainable development in Sudanian countries and an attractive potential for the food and cosmetics industries. The purpose of this study was to develop near-infrared spectroscopy (NIRS) calibrations to characterize Shea nut fat profiles. Powders prepared from nuts collected from 624 trees in five African countries (Senegal, Mali, Burkina Faso, Ghana and Uganda) were analyzed for moisture content, fat content using solvent extraction, and fatty acid profiles using gas chromatography. Results confirmed the differences between East and West African Shea nut fat composition: eastern nuts had significantly higher fat and oleic acid contents. Near infrared reflectance spectra were recorded for each sample. Ten percent of the samples were randomly selected for validation and the remaining samples used for calibration. For each constituent, calibration equations were developed using modified partial least squares (MPLS) regression. The equation performances were evaluated using the ratio performance to deviation (RPD(p)) and R(p)(2) parameters, obtained by comparison of the validation set NIR predictions and corresponding laboratory values. Moisture (RPD(p) = 4.45; R(p)(2) = 0.95) and fat (RPD(p) = 5.6; R(p)(2) = 0.97) calibrations enabled accurate determination of these traits. NIR models for stearic (RPD(p) = 6.26; R(p)(2) = 0.98) and oleic (RPD(p) = 7.91; R(p)(2) = 0.99) acids were highly efficient and enabled sharp characterization of these two major Shea butter fatty acids. This study demonstrated the ability of near-infrared spectroscopy for high-throughput phenotyping of Shea nuts.

Prediction of carotenoids, cyanide and dry matter contents in fresh cassava root using NIRS and Hunter color techniques

Efforts are currently underway to improve carotenoids content in cassava roots through conventional breeding as a strategy to reduce vitamin A deficiency. However, only few samples can be quantified each day for total carotenoids (TCC) and β-carotene (TBC) contents, limiting the gains from breeding. A database with >3000 samples was used to evaluate the potential of NIRS and chromameter devices to predict root quality traits. Maximum TTC and TBC were up to 25.5 and 16.6 μg/g (fresh weight basis), respectively. NIRS predictions were highly satisfactory for dry matter content (DMC, R(2): 0.96), TCC (R(2): 0.92) and TBC (R(2): 0.93). NIRS could also distinguish roots with high or low cyanogenic potential (R(2): 0.86). Hunter color parameters could also be used for predictions, but with lower accuracy than NIRS. NIRS or chromameter improve selection protocols, allowing faster gains from breeding. Results also demonstrate that TBC and DMC can be improved simultaneously (required for the adoption of biofortified cassava).

Quantification of Kavalactones and Determination of Kava (Piper methysticum) Chemotypes Using Near-Infrared Reflectance Spectroscopy for Quality Control in Vanuatu

Kava ( Piper methysticum Forst f., Piperaceae) has anxiolytic properties and the ability to promote a state of relaxation without the loss of mental alertness. The rapid growth of the nutraceutical market between 1998 and 2000 has been stopped by a ban in Europe and Australia because of some suspicion of liver toxicity. It is now important to develop a fast, cheap, and reliable quality test to control kava exports. The aim of this study is to develop a calibration of the near-infrared reflectance spectroscopy (NIRS) using partial least-squares (PLS) regression. Two hundred thirty-six samples of kava roots, stumps, and basal stems were collected from the Vanuatu Agricultural Research and Technical Centre germplasm collection and from four villages. These samples, representing 45 different varieties, were analyzed using NIRS to record their absorption spectra between 400 and 2500 nm. A set of 101 selected samples was analyzed for their kavalactone content using HPLC. The results were used for PLS calibration of the NIRS. The NIRS prediction of the kavalactone content and the dry matter were in agreement with the HPLC results. There were good correlations between these two series of results, and coefficients ( R (2)) were all close to 1. The measurements were reproducible and had repeatability on par with the HPLC method. The NIRS system has been calibrated for the six major kavalactone content measurements, and it is suggested that this method could be used for quality control in Vanuatu.

Prediction by near infrared spectroscopy of the composition of plant raw materials from the organic fertiliser industry and of crop residues from tropical agrosystems

The dynamics of carbon (C) and nitrogen (N) of plant residues and organic fertilisers are of great interest for agricultural and global warming studies. The proportion of the fractions obtained from biochemical analyses (fibres by sequential Van Soest analysis) can be used for predicting both C and N transformation of organic materials in soils. Considering the expensive and time-consuming Van Soest method, the principal aim of this study was to elaborate near infrared (NIR) calibrations for fibres, in order to use them for consecutive studies (for example, our works on transformation of added organics or TAO model). A wide set of organic fertilisers and their raw materials was sampled, including plant materials originating from temperate (especially Mediterranean) and tropical regions. The particular objective of this work was to build NIR calibrations for fibre fractions, along with C and N content, in plant materials used in the organic fertiliser industry and green house gases mitigating strategies. The second particular objective was to test for two levels of validation of the equations previously elaborated: (1) validation with a set of randomly chosen samples that was not considered during the calibration step, (2) extrapolation of the predictive capacity of the equations when applying them to outliers that were previously discarded. The fibres were the best predicted parameters, as R² = 0.95, 0.91, 0.97, 0.97 for neutral detergent soluble, hemicelluloses, cellulose and lignin, respectively, whereas the characteristics of total organic matter had R² varying from 0.87 (N Kjeldahl) to 0.94 (C Dumas). The accuracy of the calibrations developed for fibres was confirmed by the first level of validation, since the standard errors of prediction were close to the corresponding standard errors of cross-validation and the standard errors of calibration. Nevertheless, the calibrations developed for ash and C Dumas were not so good. Surprisingly, at the second level of validation, some outliers were not so badly predicted. This can illustrate the robustness of the calibrations for cellulose, lignin and, to a lesser extent, N Dumas which are key parameters for our modelling works on C and N transformation of added organics in soils.

The use of near infrared spectroscopy to determine the fat, caffeine, theobromine and (-)-epicatechin contents in unfermented and sun-dried beans of Criollo cocoa

Cocoa is an important raw material in international trade, for which the highest quality is demanded. Venezuelan Criollo cocoa beans from the south of Lake Maracaibo or Chuao are of very high quality and are considered to be Venezuelas finest beans. It is therefore important to characterise and define that quality, or its precursors, in the different primary cocoa processing stages. Given the large number of samples to be analysed, new analytical techniques providing fast and reliable quality data are essential. Near infrared (NIR) spectroscopy utilises wavelengths from 780–2500 nm to measure the absorbance by a sample, compute organic functional groups and quantitatively predict a particular factor. It has been extensively used to analyse food quality and to determine the main alkaloids of coffee. Fat, caffeine, theobromine and (−)-epicatechin contents are related to cocoa bean “flavour” quality. These parameters are usually determined using conventional methods, which are time consuming, destructive and expensive. The goals of this study were to use NIR spectroscopy to develop a fast and non-destructive tool to determine compounds in unfermented and sun-dried cocoa beans of high quality. Calibration coefficients of determination (R2) and standard errors of cross-validation were 0.94 and 0.89%, 0.94 and 0.05%, 0.88 and 0.08% and 0.96 and 0.18% for fat, caffeine, theobromine and (−)-epicatechin contents (% dry matter), respectively. The results confirmed the good predictability of the models and showed that NIR spectroscopy can be used as a rapid method for determining these compounds in cocoa beans.

Prediction of the chemical composition of poultry excreta by near infrared spectroscopy.

The potential of near infrared (NIR) spectroscopy for the determination of the chemical composition of poultry excreta was investigated, within the framework of studies on heritability of digestive efficiency in broilers. Samples in the calibration and validation databases (DB1 and DB2) corresponded to animals fed with a similar wheat-based diet. A second validation study was performed on excreta samples from animals fed more variable diets, including peas and maize (DB3). Excreta samples were freeze-dried and ground. Near infrared reflectance spectra were taken on a monochromator spectrometer between 400nm and 2500nm. Samples were analysed for mineral matter (MM), gross energy (GE), starch, crude fat (CFAT), total nitrogen (NTOT), uric acid nitrogen (NUA) and protein nitrogen estimated directly (PNTERP) or by difference between NTOT and NUA (PNUA). Depending on the parameters studied, 250 to 700 samples were analysed by reference methods. The standard error of cross-validation (SECV) and R2 of calibrations were: 0.60% and 0.96 for MM, 166 kJ kg−1 and 0.99 for GE, 0.59% and 1.00 for starch, 0.44% and 0.99 for CFAT, 0.25% and 0.89 for NTOT and 0.22% and 0.97 for NUA, respectively. Calibration for PNTERP (SECV=0.07%; R2=0.98) was much more precise than PNUA (SECV=0.21%, R2=0.85). Validation carried out on databases DB2 and DB3 resulted in standard errors of prediction (on DB2) and extrapolation (on DB3) generally higher than SECV, while remaining relatively precise with prediction r2 values from 0.83 to 0.99 and extrapolation r2 from 0.86 to 0.98, with the exception of PNUA for which r2 was 0.22 and 0.64, respectively. For some parameters, the lower validation performance was due to biases, particularly in the case CFAT and NUA for prediction and MM, GE and NUA for extrapolation. Global calibrations made with DB1+DB2+DB3 were more precise (GE, NTOT) or equally precise (all other parameters) than with DB1 alone. These results confirmed the potential precision of calibrations for the major organic compounds in poultry excreta and suggested that their use could be extended to excreta issued from a wider range of diets without losing precision.

Near infrared spectroscopy as a new tool to determine cocoa fermentation levels through ammonia nitrogen quantification

Fermentation is a key step in obtaining fine cocoa through the formation of potent aroma precursors. The fermentation level of cocoa beans is traditionally assessed by measuring the amount of ammonia nitrogen (NH₃) using the time-consuming Conway technique. Near infrared spectroscopy (NIRS), a rapid and efficient tool, was used to analyze NH₃ levels in several hundred cocoa samples at different fermentation levels from six geographical origins. Fermentation levels were expressed as the number of fermentation days and sum of temperatures. The correlation between Conway results and NIRS spectra enabled the development of a reliable and accurate NIRS calibration to determine NH₃ content. We confirm that NH₃ is produced during fermentation and its amount depends on the fermentation time, sum of temperatures and geographical origin. NIRS could be used by chocolate manufacturers as a routine method to sort cocoa samples according to their level of fermentation.

Diversity of Cacao Trees in Waslala, Nicaragua: Associations between Genotype Spectra, Product Quality and Yield Potential

The sensory quality and the contents of quality-determining chemical compounds in unfermented and fermented cocoa from 100 cacao trees (individual genotypes) representing groups of nine genotype spectra (GG), grown at smallholder plantings in the municipality of Waslala, Nicaragua, were evaluated for two successive harvest periods. Cocoa samples were fermented using a technique mimicking recommended on-farm practices. The sensory cocoa quality was assessed by experienced tasters, and seven major chemical taste compounds were quantified by near infrared spectrometry (NIRS). The association of the nine, partially admixed, genotype spectra with the analytical and sensory quality parameters was tested. The individual parameters were analyzed as a function of the factors GG and harvest (including the date of fermentation), individual trees within a single GG were used as replications. In fermented cocoa, significant GG-specific differences were observed for methylxanthines, theobromine-to-caffeine (T/C) ratio, total fat, procyanidin B5 and epicatechin, as well as the sensory attributes global score, astringency, and dry fruit aroma, but differences related to harvest were also apparent. The potential cocoa yield was also highly determined by the individual GG, although there was significant tree-to-tree variation within every single GG. Non-fermented samples showed large harvest-to-harvest variation of their chemical composition, while differences between GG were insignificant. These results suggest that selection by the genetic background, represented here by groups of partially admixed genotype spectra, would be a useful strategy toward enhancing quality and yield of cocoa in Nicaragua. Selection by the GG within the local, genetically segregating populations of seed-propagated cacao, followed by clonal propagation of best-performing individuals of the selected GG could be a viable alternative to traditional propagation of cacao by seed from open pollination. Fast and gentle air-drying of the fermented beans and their permanent dry storage were an efficient and comparatively easy precondition for high cocoa quality.