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Rangeland fodder resources used to feed ruminants in the Sahel decline considerably in both quantity and quality from the wet to dry seasons. While it is widely assumed worldwide that this seasonality of fodder supply impacts intake levels and therefore enteric methane (eCH4) emissions, there are very few references based on in vivo measurements of eCH4 in this region. The purpose of this study was to test the assumption that the seasonality of fodder supply impacts intake levels and consequently eCH4 in ruminants. Thus, eCH4 was measured in vivo in Sudanese Fulani zebu cattle during three main seasons of the year (wet season: WS, cold dry season: CDS, and hot dry season: HDS). The experiment was carried out on 10 steers aged 32 months with an average (± SD) initial BW of 138 ± 5.8 kg (i.e. 0.55 Tropical Livestock Unit − TLU) and kept in individual pens. Animals were fed with natural rangeland fodder harvested each season following herders' practices, i.e. green fodder in the WS and dry fodder hay in the CDS and HDS. Different levels of fodder were offered to the animals to reproduce the gradient of fodder availability on rangelands over the year (six trials): 3.3% BW during the CDS; 3.3, 2.3, and 1.4% BW successively during the HDS; and 2.3% in two sequential studies in the WS. Each trial lasted 3 weeks, split into 2 weeks of fodder adaptation and 1 week of data collection. The BW, quantity of voluntary DM intake, digestibility of DM digestibility and of OM digestibility, and eCH4 (GreenFeed® system) were measured for each animal. Fodder composition varied considerably between seasons (P < 0.05). The DM intake (g/kg BW per day) varied from 23.9 in CDS to 15.7 in HDS and 22.3 in WS (P < 0.001). The DM digestibility varied from 0.50 in CDS to 0.46 in HDS and 0.57 in WS. The eCH4 yields (g/kg DM intake per day) varied significantly from 25.2 in the CDS to 31.8 in the HDS and 20.5 in the WS. When extrapolated over a full year and irrespective of season, eCH4 emissions

In Africa, a wide variety of diets (forage + crop co-products or other agricultural by-products) is being used by livestock farmers in different production systems to adapt to climate change. This study aimed to assess the performance of various local feeding strategies on Sudanese Fulani zebu cattle. Two experiments were carried out on 10 steers aged initially 33 months (142 kg body weight – BW). The animals were fed eight different diets at an intake level of 3.2% LW in dry matter (DM), including two control diets of 100% rangeland forage (100% RF) and six experimental diets made up of forage and crop co-products (75:25 DM ratio). In the first experiment, the control diet was made up of rangeland forage (RF) and supplements consisted of four cereal co-products (CC), i.e. maize, sorghum, millet, and rice straws. In the second experiment, the control diet consisted of Panicum maximum (Pmax) hay, and the supplements tested were two legume co-products (LC), i.e. cowpea and peanut haulms. Each experiment lasted 3 weeks, including 2 weeks of adaptation to the diet and 1 week of data collection on individual animals (intake, apparent digestibility, and enteric methane). The NDF content of the diets was different within each experiment (p < 0.05). Among diets containing CC, DM intake [g/kg BW] was significantly higher (+31%; p = 0.025) for the diet containing rice straw than for the other diets, which showed similar levels to the RF diet. Among diets containing LC, intake was significantly higher (p = 0.004) than for the Pmax diet. Intake was higher for the peanut haulm diet than for the cowpea haulm diet. The DM digestibility was similar between the different diets in each experiment. Enteric methane (eCH4) yield [g/kg DMI] from the CC and LC-containing diets were reduced by an average of 23% and 20% compared to the RF and Pmax control diets respectively. Raising awareness among agro-pastoralists about the use of crop co-products offers real prospects for eCH4 emissions

Background: The climate and harvest management practices influence forage production in the Sahel. However, the combined effect of these parameters has not been assessed. Aim: This study aims to measure the joint effect of rainfall and harvesting practices on the quantity and quality of forage. Methods: Aboveground biomass samples were collected during (July and August) and at the end (October) of the 2021 rainy season by full cutting on 68 harvest plots: 20 plots with different water regimes (varying water quantities and duration of inputs), and 48 plots with different quantities of water combined with different cutting heights (0 or 5 cm above ground) and harvest periods (early or late). Results: The aboveground biomass ranged from 2,932.2 ± 1,672.1 to 6,383.6 ± 2,962.6 kg/ha for water regime treatments, and 2,397.7 ± 6,263.4 kg/ha to 15,059.2 ± 9,782.9 kg/ha for cumulated harvest aboveground biomass. The crude fiber rate (as % of dry matter) was between 5.5 ± 0.9% and 6.4 ± 1.2%. Digestible crude protein varied between 21.8 ± 67.96% and 67.2 ± 15.8%. Regardless of the quantity of water received, equivalent quantities and qualities of forage (p > 0.05) were produced by the plots that were not harvested until the end of the season and those harvested at the beginning of the development cycle of the forage species. The amount of aboveground biomass produced was the same, independent of the cutting heights (3,535.8 ± 2,953.5 for 0 cm and 4,503.4 ± 3,068.6 kg/ha for 5 cm). On the other hand, the plots harvested at the fruiting stage of the species produced forage composed of young plants in smaller quantities and of good quality. Conclusions: The quantity and quality of herbaceous forage yield at the end of the rainy season were mainly influenced by the phenological stage. Forage resource management programs should favor cutting times and heights that allow optimal ground coverage to reduce the risk of erosion.

Le renouvellement de nombreuses essences d'intérêts économique et écologique est remis en cause par une hausse généralisée des populations de cervidés et des dégâts qu'ils occasionnent. La simulation d'abroutissement est une méthode expérimentale consistant à combiner la section mécanique de la plante et l'application de salive de cervidés sur la zone sectionnée qui permet de contrôler précisément les épisodes d'abroutissement auxquels sont soumis les plants. Nous illustrons ici, par deux exemples, les possibilités offertes par cette technique pour comprendre les effets des abroutissements de chevreuil sur la croissance et survie des plants de Chêne.

L'élevage de ruminants en Afrique subsaharienne est singulier par les milieux et ressources qu'il exploite et par des systèmes d'élevage aux effectifs parfois élevés mais souvent peu productifs. L'évaluation de son impact environnemental est toutefois complexe car les modèles classiquement utilisés ne sont pas adaptés aux animaux et aux modes d'élevage de cette région. Il est important d'apporter des connaissances objectives sur la production du méthane entérique, principal gaz à effet de serre de ces élevages.

Drought can induce phenotypic plasticity in a range of plant root and shoot traits. These traits have been shown to explain differences in root and shoot litter decomposability between species. However, it is unknown how drought-induced plasticity of root and shoot traits alters their decomposability. To investigate this issue across a range of species, we grew a grass Lolium perenne, a forb Plantago lanceolata and a legume Trifolium repens common to European temperate grasslands and subjected them to a 5-week moderate drought treatment. We compared morphological and chemical root and shoot traits of the droughted plants to well-watered controls. We then conducted a decomposition assay of the senesced root and shoot material over 16 weeks, with mass loss measurements at five timepoints. Drought had significant and sometimes strong effects on morphological and chemical root and shoot traits of all three species, sometimes similar to differences between species and generally in line with a shift to a more resource-conservative strategy. Drought also increased the labile litter fraction in roots of Lolium perenne, which was associated with a substantial increase in non-structural carbohydrates. Drought decreased the labile litter fraction in shoots of Plantago lanceolata, but this could not be explained by the traits we measured. Drought effects on litter decomposability were weaker than on plant traits. Our results suggest that plant trait-mediated effects of drought on litter decomposability can either increase or decrease vegetation feedbacks to climate change. They also show that drought-induced plasticity in root and shoot traits does not automatically translate into equivalent changes in litter decomposability. Read the free Plain Language Summary for this article on the Journal blog.

Partial least square regression (PLSR) is a reference statistical model in chemometrics. In agronomy, it is used to predict components (response variables y) of chemical composition of vegetal materials from spectral near infrared (NIR) data X collected from spectrometers. PLSR reduces the dimension of the spectral data X by defining vectors that are then used as latent variables (LVs) in a multiple linear model. One difficulty is to determine the relevant dimensionality (number of LVs) for the given data. This step can be very time consuming when many datasets have to be processed and/or the datasets are frequently updated. The paper focuses on an alternative, bypassing the determination of the PLSR dimensionality and allowing for automatizing the predictions. The strategy uses ensemble learning methods, such as averaging or stacking the predictions of a set of PLSR models with different dimensionalities. The paper presents various methods of PLSR averaging and stacking and compares their performances to the usual PLSR on six real datasets on different types of forages. The main finding of the study was the overall superiority of the averaging methods compared to the usual PLSR. We therefore believe that such methods can be recommended to analyze NIR data on forages.

Sorghum currently contributes to the species portfolio that is supporting bioenergy production including anaerobic digestion. Although agro-morphological ideotypes maximizing biogas production have been recently proposed, there is a crucial need to refine our understanding of the impacts of the stem composition and structure on this processing trait in order to ensure genetic gains in the mid to long terms. This study aims to assess the potential of Sorghum bicolor ssp bicolor stem genetic diversity to maximize genetic gains for biogas production and define a biogas stem ideotype. In this context, a panel of 57 genotypes, encompassing most of the stem composition variability available in cultivated sorghum, was characterized over five sites. Simultaneous histological and biochemical characterizations were performed. A high broad sense heritability associated with a moderate genetic variability was detected for stem biogas potential ensuring significant genetic gains in the future. In addition, the development of a stem histological phenotyping pipeline made it possible to describe the genetic diversity available for the internode anatomy and the repartition of key cell wall components. Consistently with previous studies, moderate to high heritability was observed for stem biochemical components. Genetic correlation, hierarchical clustering, and multiple stepwise regression analyses identified soluble sugar content as the first main driver of biogas potential genetic variability. Nevertheless, breeding programs should anticipate that biogas yield improvement will also rely on the monitoring of the cell wall components and their distribution in the stem jointly with the soluble sugar content. According to the assets of sorghum in terms of adaptation to environmental stresses and the present results regarding the identification of stem ideotypes suitable for different value chains, this species will surely play a key role to optimize the economic and environmental sust

In the dataset presented in this article, sixty sugarcane samples were analyzed by eight visible / near infrared spectrometers including seven micro-spectrometers. There is one file per spectrometer with sample name, wavelength, absorbance data [calculated as log10 (1/Reflectance)], and another file for reference data, in order to assess the potential of the micro-spectrometers to predict chemical properties of sugarcane samples and to compare their performance with a LabSpec spectrometer. The Partial Least Square Regression (PLS-R) algorithm was used to build calibration models. This open access dataset could also be used to test new chemometric methods, for training, etc.

This dataset presents 127 raw near infrared spectra of different organic samples acquired on three different spectrometers in three different labs. An example of data processing is shown to create six spectra transfer models between the three spectrometers (two by two). In order to build and validate these transfer models, the dataset was split into two sets of spectra: a first set was used to compute six spectra transfer models thanks to the Piecewise Direct standardisation function (PDS). A second set of spectra, independent of the first one was used to validate transfer models. Spectrum treatments and models were created on ChemFlow (https://vm-chemflow-francegrille.eu/), a free online chemometric software that includes all the necessary functions.

The Andropogonae tribe hosts some of the most efficient plant biomass accumulators on earth (sugarcane, switchgrass, miscanthus...). Among these, sorghum is a relevant candidate to support biomass value chain development for energy, biomaterials and innovative biorefinery approaches. Sorghum exhibits a large genetic variability for biomass composition providing the opportunities to support the development of different value chains. However, the access to fine-tuned varieties fitting the expectations of the various end-products is currently hampered by a limited understanding of the genetic architecture of the biomass and cell wall quality related traits. To tackle these limitations, an atlas of genomic regions that control the composition and properties of the vegetative biomass is under development. To fulfil this objective, we are integrating the results from i) GWAS analyses from three complementary broad based panels (i.e. worldwide collection (400 accessions), photoperiod sensitive (220) and photoperiod-insensitive (175) panels), ii) two Backcross Nested Association Mapping population (the first corresponding to 29 donor and 2 recurrent parents for a total of 1300 BC1F4 progenies and the second corresponding to 10 donors and 2 recurrent parents for a total of 2000 BC1F5) and iii) several connected biparental populations. All these populations were characterized either for their whole aboveground biomass composition or specifically for their stem composition using Van Soest methods. In addition, in vitro organic matter digestibility and cell wall digestibility were obtained using the Aufrere methods. Projection of the genomic regions identified on the different populations on the sorghum reference genome allowed to restrict the set of candidate genes. Meanwhile, dynamics of gene expression and biomass components accumulation patterns were analyzed on three contrasting genotypes to refine this list in combination with a comparative genomic approach taking advanta

Faecal near infrared spectroscopy (FNIRS) can be a good technique to predict functional properties like intake or in vivo digestibility of forages by small ruminants. Data were collected from 108 different digestibility indoor and outdoor trials in Senegal and France carried out from 1993 to 2013 on sheep fed with a large variety of forage species. Faecal samples were scanned by a Foss NIRSystem 5000 monochromator. Calibrations were established on indoor trials samples and performed using the modified partial least square (mPLS) procedure to estimate dry or organic matter (DMI, OMI, g/kg metabolic weight, BW0.75) intake, in vivo dry and organic matter (DMD, OMD,%) digestibility. The derived standard errors of calibration (SEC) and coefficients of determination (R2cal) were 6.52 g/kg BW0.75 and 0.81 for DMI, 5.17 g/kg BW0.75 and 0.86 for OMI, 1.50% and 0.93 for DMD and 1.95% and 0.88 for OMD, respectively. These values confirm the interest of the use of FNIRS as a tool to manage small ruminants. The results obtained show a good accuracy with values similar to other published results for intake and digestibility. Validation on outdoor trials samples show the difficulty to extrapolate the prediction of intake with limited samples number and only one pasture quality.

Les instituts de recherche en productions animales des pays du Sud disposent parfois de laboratoires d'analyse. Cependant ces laboratoires rencontrent souvent des difficultés de fonctionnement soit techniques (défaut d'approvisionnement en eau ou électricité) soit humaines (difficultés à avoir et/ou conserver des agents formés). De plus, les centres de recherche disposent parfois de capacités d'investissement en équipements scientifiques assez bonnes (projets, coopération, dons) mais ne disposent pas des ressources financières pour les maintenir et les faire fonctionner correctement. La production de données de référence fiables est donc généralement très difficile et aléatoire. Dans ce contexte où il est également de plus en plus difficile de faire voyager des échantillons pour des raisons sanitaires ou réglementaires, l'utilisation de la SPIR est une solution efficace pour permettre la production de données expérimentales à grande échelle. L'UMR Selmet travaille à la mise en place d'un réseau SPIR en Afrique et Océan Indien. Cette stratégie vise à appuyer nos partenaires d'une part à s'équiper en SPIR pour leur permettre d'acquérir une capacité de caractérisation de leurs ressources alimentaires et d'autre part à les accompagner dans le développement de cette technique. Pour l'UMR Selmet l'accompagnement des partenaires passe par la formation et par le développement et le déploiement d'outil d'aide à la prédiction (plateforme de prédiction en ligne " NIRSPred "). Il est cependant essentiel d'associer les partenaires à la production de données de référence et d'éviter de les rendre totalement dépendants de bases centralisées. L'aide au suivi de la qualité des spectromètres (création automatisée de carte de contrôle " ASDMonitor ") est également un élément important de l'appui au développement du réseau.

Certains échantillons de végétaux conservés dans des collections (échantillothèques, herbiers, carpothèques, …) ont une valeur scientifique ou patrimoniale importante, et la mesure de leurs caractéristiques biochimiques par SPIR serait intéressante. Une limite à cette utilisation peut être l'état de conservation des échantillons et ses conséquences sur leur composition chimique. Dans le cadre de la valorisation d'importantes collections d'aliments pour animaux (plus de 60 000 échantillons stockés depuis les années 1960), nous avons étudié l'évolution des spectres et des prédictions de composition chimique avec la durée de stockage d'échantillons de fourrages. 120 échantillons appartenant à 4 catégories de végétaux ont été sélectionnés. Les spectres des échantillons présentés en poudre ont été collectés sur un spectromètre FOSS (NIRSYSTEM 5000 et 6500, 1100-2500nm) en 2002 puis à nouveau en 2017. Deux types de comparaisons ont été réalisées, l'étude de l'évolution du spectre et l'étude de l'évolution des prédictions de trois paramètres clé : protéines (MAT), fibres totales (NDF) et digestibilité in vitro (DMO). La distance entre les spectres initiaux et les spectres obtenus après 15 ans est supérieure à celle observée entre deux répétitions réalisées à la même date. Une partie des différences est logiquement située dans les bandes de l'eau mais certaines se situent dans d'autres régions spectrales. Les valeurs de prédictions montrent (i) que les résultats sont comparables pour les paramètres MAT et DMO, (ii) qu'il y a une diminution de la teneur en NDF pour toutes les catégories d'échantillons, (iii) que les écarts-types sont identiques pour un même paramètre. Les régressions linéaires entre les prédictions basées sur les anciens et les nouveaux spectres donnent des R² autour de 0,96. Malgré le biais qu'il peut y avoir, les valeurs restent fortement corrélées. Il est donc nécessaire de prendre des précautions dans l'interprétation des données de prédictions sur des é

Dans le cadre du projet Biomass For the Futur (BFF), des échanges inter-laboratoires d'échantillons de miscanthus, sorgho et maïs sont effectués afin de mesurer et de prédire des paramètres biochimiques. Chaque laboratoire possède ses propres méthodes de mesures expérimentales et ses modèles de calibration proche infrarouge. A ce jour, les prédictions issues des modèles de calibration nécessitent l'acquisition de spectres au laboratoire. L'objectif du travail mené ici est de pouvoir s'affranchir de cette étape d'acquisition en créant des modèles de transfert entre deux spectromètres. En effet, les appareils des laboratoires partenaires sont de marques différentes, et n'ont pas les mêmes modalités d'acquisition (unités, résolution…). Il est donc nécessaire de créer des modèles permettant de transférer un spectre d'un appareil vers un autre afin de l'utiliser pour la prédiction de paramètres biochimiques. La présentation repose ici sur les modèles de transfert entre l'UMR SELMET pour leur spectromètre FOSS NIRSystem5000, et le LBE pour le spectromètre BUCHI N-500. Les modèles de transfert sont réalisés sur ChemFlow, logiciel de chimiométrie gratuit en ligne, permettant le stockage et le partage de données entre utilisateurs. Deux types d'échantillons ont été échangés entre ces deux laboratoires pour la création des modèles : 40 échantillons de référence, représentatifs des activités de chaque laboratoire, ainsi que 31 échantillons spécifiques du projet BFF (maïs, miscanthus et sorgho). Ces deux jeux de données ont dans un premier temps été pris séparément pour créer deux modèles : le modèle labo40 (global) et le modèle BFF31 (local). Puis dans un second temps, les 71 échantillons sont rassemblés pour créer le modèle globalBFF71. Ces trois modèles sont construits avec l'outil de transfert PDS (Piecewise Direct Standardization) et diffèrent seulement par leur jeu de construction. Enfin, un modèle témoin est testé, le modèle 0, créé sans outil de transfert, simplement av

Contexte et objectifs: en Tunisie, la majorité des parcours sont situés dans les zones semi-arides et arides. Ils couvrent une superficie de 5,5 millions d'hectares. Ces parcours jouent un rôle vital quant à leur apport extrêmement considérable au niveau du bilan fourrager de l'élevage extensif. Soumis à un système d'exploitation pastoral intensif, ces parcours ont atteint un stade de dégradation très avancé. Les espèces pastorales comestibles, variant selon l'espèce animale exploitant le parcours, constituent la ration de base du dromadaire conduit en extensif. Il est donc indispensable d'étudier la composition chimique de ces espèces. L'objectif de cette étude est la mise en place d'une méthodologie basée sur la spectroscopie proche infrarouge spir pour la caractérisation de quelques espèces pastorales dans le sud tunisien (retama reatam, haloxylon shmittianum, suaeda mollis, salsola tetrandra, zygophyllum album, ariplex halimus, halocnemum strobilaceum, limoniastrum guyonianum, anabasis articulata et frankinia thymofolia) palatable par le dromadaire, permettant de déduire la bonne complémentation pendant les années sèches. Matériel et méthodes: les échantillons ont été collectés de deux parcours du sud tunisien (El bhaier et El fjé) et analysés pour déterminer leur teneurs en matières minérales (MM), matière organique(MO), en matières azotées totales (MAT), ensuite les teneurs en fibres (NDF, ADF et ADL) et la digestibilité in vitro. Ils sont été passé par la SPIR (TANGO-BRUKER) en utilisant des longueurs d'ondes variant entre 800 et 2500 nm, et à l'aide d'un logiciel appelé opus pour créer une méthode de prédiction. Résultats et discussion: les critères retenus pour évaluer la qualité des modèles établis sont: le coefficient de détermination (r²), l'erreur standard de validation croisée (RMSECV ou RMSEP), l'erreur standard d'estimation (RMSEE), et le RPD représentant le rapport entre l'écart-type de la population et variant entre 1,4 et 3. Ce paramètre permet la

Sweet and biomass sorghum are expected to contribute increasingly to bioenergy production. Better understanding the impacts of the genotypic and environmental variabilities on biomass component traits and their properties is essential to optimize energy yields. This study aimed to evaluate whether traits contributing to stem biomass growth and biochemical composition at different biological scales (co)vary with the genotype and the water status in sorghum. Height genotypes were studied over two years in field conditions in southern France under two water treatments (well watered vs. 25 days' dry down during stem elongation). Main stem internode number, size, (non)structural carbohydrate, and lignin contents were measured at the end of the stress period and/or at final harvest, together with biochemical and histological analyses of the youngest expanded internode. The tallest genotypes showed the highest stem dry weights and lignin contents. Stem (structural) biomass density was positively correlated with lignin content, particularly in internode parenchyma. Stem soluble sugar and lignin contents were inversely proportional across genotypes and water conditions. Genotypes contrasted for drought sensitivity and recovery capacity of stem growth and biochemical composition. The length and cell wall deposition of internodes expanding under water deficit were reduced and did not recover, these responses being weakly correlated. Genotypic variability was pointed out in the growth recovery of internodes expanding under re‐watered conditions. According to the observed genotypic variability and the absence of antagonistic correlations between the responses of the different traits to water availability, it is suggested that biomass sorghum varieties optimizing their responses to water availability in terms of growth and cell wall deposition can be developed for different bioenergy targets.