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Multisite Yield Gap Analysis of Miscanthus × giganteus Using the STICS Model
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Development and use of models to predict and study the production and the environmental impacts of bio-mass cropping systems are of great interest for their sustainable development. Improvements were made to the research version of the STICS crop–soil model in order to simulate biomass production and environmental impacts of Miscanthus×giganteus cropping systems in the long term. This research version was then validated on a large database and in various pedoclimatic environments in France and UK. The model accurately simulated biomass production and nitrogen (N) content in aboveground biomass, from planting until 4 to 20 years of cultivation. The model efficiency (EF) was 0.80 and 0.64 for biomass and N content, respectively, and the values of relative RMSE were 23 and 31 %. Soil water and mineral N contents were also satisfactorily predicted (EF=0.96 and 0.42; relative RMSE=10 and 72 %). The model accurately reproduced the effect of management practices on the harvested biomass and N export. Yield gap analysis using simulations with and without active stresses revealed that Miscanthus×giganteus biomass production was limited by both water and N availability during the establishment phase but mainly limited by water availability during the post-establishment phase. The STICS crop–soil model can accurately predict Miscanthus×giganteus biomass production and environmental impacts such as water drainage and nitrate leaching and compare strategies with varying N fertilization, irrigation and harvest date.
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... Cette méthode de calibration est très sommaire comparée à la palette de méthodes que la littérature rapporte pour les modèles biophysiques(Makowski et al., 2006), qui inclut notamment des méthodes globales comme la calibration Bayésienne ou le recuitsimulé. L'inconvénient d'une approche locale par tâtonnement (trial-and-error) comme celle mise en oeuvre dans le chapitre 1 est que si les paramètres sont fortement corrélés entre eux leurs valeurs optimales sont inter-dépendantes et il est impossible de trouver le réel optimum global.Néanmoins ce type de méthode a été utilisée précédemment pour la calibration du modèle STICS pour différentes cultures dont le miscanthus et la canne-à-sucre(Coucheney et al., 2015;Strullu et al., 2015;Valade et al., 2014). Cette approche reste en effet efficace car le fait de disposer de plusieurs variables de calage intervenant dans différents processus écophysiologiques (l'indice foliaire pour la croissance des feuilles, la teneur en azote des organes pour l'absorption des nutriments, la croissance en biomasse pour la photosynthèse nette) permet de séparer les paramètres à calibrer et de mieux interpréter la simulation des processus en jeu. ...
... Une comparaison des résultats de simulations avec les observations a permis de valider le modèle, et des tests statistiques ont montré que les valeurs des paramètres ajustés fournissaient des prédictions acceptablesmalgré des écarts importants sur certains traitements du site de calibration. Le modèle STICS miscanthus a été calibré en utilisant la même approche et un réseau de données d'observation proche de celui utilisé dans le cadre de cette thèse(Strullu et al., 2015), avec des résultats proches : CERES-EGC présente une RMSE de 4,7 t MS ha -1 légèrement plus élevée que celle calculée lors de la calibration de STICS (avec une RMSE de 3,4 t MS ha -1 )(Strullu et al., 2015). Tout comme les résultats du modèle CERES-EGC, le modèle STICS a tendance à surestimer le calcul de la biomasse aérienne. ...
... Une comparaison des résultats de simulations avec les observations a permis de valider le modèle, et des tests statistiques ont montré que les valeurs des paramètres ajustés fournissaient des prédictions acceptablesmalgré des écarts importants sur certains traitements du site de calibration. Le modèle STICS miscanthus a été calibré en utilisant la même approche et un réseau de données d'observation proche de celui utilisé dans le cadre de cette thèse(Strullu et al., 2015), avec des résultats proches : CERES-EGC présente une RMSE de 4,7 t MS ha -1 légèrement plus élevée que celle calculée lors de la calibration de STICS (avec une RMSE de 3,4 t MS ha -1 )(Strullu et al., 2015). Tout comme les résultats du modèle CERES-EGC, le modèle STICS a tendance à surestimer le calcul de la biomasse aérienne. ...
Dans le contexte de réduction des émissions de GES du secteur des transports en France, ce travail de thèse se focalise sur les bilans environnementaux de biocarburants produits à partir de cultures lignocellulosiques. Deux espèces pérennes ont été étudiées : le miscanthus et le switchgrass. Nous avons testé et validé un modèle biophysique, CERES-EGC, pour ces deux cultures. Les simulations ont été spatialisées à l’échelle de la France avec différents niveaux de fertilisations azotées et deux horizons climatiques. Une dimension économique a été introduite en faisant le couplage des sorties du modèle CERES-EGC avec le modèle économique AROPAj. Ce couplage bio-économique a été essentiel pour le calcul des changements d’affectation des sols (CAS) directs liés au développement des cultures lignocellulosiques. Ceux-ci ont été combinés avec les sorties CERES-EGC pour construire une ACV spatialisées prenant en compte les conditions pédoclimatiques des différentes régions de France. Cette évaluation environnementale montre que la substitution d’essence fossile par le bioéthanol permet de réduire les émissions de GES de 76 à 96%, en prenant en compte les CAS. Le rendement et les émissions des cultures dépendent de la dose de fertilisation azotée appliquée. Le miscanthus est plus compétitif et moins impactant que le switchgrass dans les conditions pédoclimatiques françaises. sur le long terme les deux cultures sont encore plus compétitives à l’échelle de la France.
... The delayed harvest also significantly reduced the amount of ash and also reduced biomass by leaving it in the field [27,51,52]. For example, between autumn and winter harvests in the third year of cultivation, the ash content averaged from 3.9% to 2.5% of dry matter. ...
... Clifton-Brown et al. [52] studied the productivity of 15 cultures of miscanthus belonging to M. × giganteus at 5 sites in Europe one year and three years after planting. There was a high and significant correlation of 0.81 between the third-and second-year yields, with this correlation being 0.56 between third and first year yields. ...
The lignocellulosic perennial crop miscanthus, especially Miscanthus × giganteus, is particularly interesting for bioenergy production as it combines high biomass production with low environmental impact. However, there are several varieties that pose a hazard due to susceptibility to disease. This review contains links showing genotype and ecological variability of important characteristics related to yield and biomass composition of miscanthus that may be useful in plant breeding programs to increase bioenergy production. Some clones of Miscanthus × giganteus and Miscanthus sinensis are particularly interesting due to their high biomass production per hectare. Although the compositional requirements for industrial biomass have not been fully defined for the various bioenergy conversion processes, the lignin-rich species Miscanthus × giganteus and Miscanthus sacchariflorus seem to be more suitable for thermochemical conversion processes. At the same time, the species Miscanthus sinensis and some clones of Miscanthus × giganteus with low lignin content are of interest for the biochemical transformation process. The species Miscanthus sacchariflorus is suitable for various bioenergy conversion processes due to its low ash content, so this species is also interesting as a pioneer in breeding programs. Mature miscanthus crops harvested in winter are favored by industrial enterprises to improve efficiency and reduce processing costs. This study can be attributed to other monocotyledonous plants and perennial crops that can be used as feedstock for biofuels.
... Il permet de tester différents scénarios pour l'optimisation de pratiques agricoles (Constantin et al. 2015, Plaza-Bonilla et al. 2015. Cette dernière qualité s'est concrétisée par la création d'une version de recherche prenant explicitement en compte au pas de temps journalier la remobilisation des réserves d'azote souterraines, la création de biomasse racinaire et la rhizodéposition d'azote et de carbone (Strullu et al. 2015). Par ses propriétés, cette version peut mieux simuler la croissance des cultures à bas intrants et le stockage à long terme d'azote et de carbone, en comparaison avec la version standard. ...
... Pour les besoins de ce projet, la version de STICS utilisée est une version de recherche, qui aboutira à la version 8.5 du modèle, dans laquelle l'azote peut être est simulé de façon dynamique, non pas uniquement dans les parties aériennes, mais également dans les parties racinaires (Strullu et al. 2015), conduisant à une répartition de l'azote dans la totalité de la plante. Cela a ainsi permis de rendre compte d'une compétition à l'azote entre racines et biomasses aériennes. ...
Dans le contexte actuel de changements globaux, faire face au défi multiple et interconnecté de la sécurité alimentaire et des impacts environnementaux s’avère fondamental pour la durabilité des systèmes agricoles. La thèse s’attache ainsi à évaluer les performances agronomiques et environnementales des systèmes en AB, en couplant un suivi expérimental réalisé sur un réseau de 35 parcelles agricoles dans la région Hauts-de-France, avec la modélisation du continuum sol-plante-atmosphère afin de mieux comprendre les processus expliquant les dynamiques de l’eau et de l’azote dans ces systèmes, en vue de promouvoir des pratiques de gestion durables.Dans un premier temps, le drainage d’eau et la lixiviation d’azote ont été quantifiés en couplant les données sol-culture-climat et le modèle LIXIM. L’analyse de la lixiviation des parcelles agricoles a permis de déterminer que les facteurs qui expliquent la variabilité. Outre le fort effet sol et l’importance des conditions climatiques sur le drainage, ils sont principalement liés à la combinaison de précédent cultural et de gestion de la couverture du sol en automne. Ces deux derniers jouent en effet sur la quantité d’azote minéral présent avant la période de drainage et expliquent la position du nitrate dans le profil de sol. Nos résultats ont montré le rôle dichotomique des légumineuses dans les systèmes de grandes cultures en AB, et la faible performance des cultures intermédiaires car semées tardivement en automne dans ce contexte.Dans un second temps, le diagnostic des déterminants de l’écart au rendement des cultures ou yield gap a été réalisé via une approche par modélisation déterministe. Le modèle sol-culture STICS a servi à estimer les différents niveaux de rendement potentiel et décomposer le yield gap, en s’appuyant sur le cas du blé tendre et du triticale. Les résultats montrent que le stress en azote permet d’expliquer la majeure partie du yield gap survenant en AB, et dans une moindre mesure les facteurs liés à la pression biotique, pour des systèmes recourant à peu ou pas d’apport azoté exogène.Finalement, le défi de la fourniture en azote dans les systèmes de grandes cultures en AB a été abordé afin de contribuer à une meilleure efficience d’utilisation de l’azote et une amélioration de la productivité des parcelles. Le modèle STICS a permis de simuler l’impact de pratiques de gestion alternatives de l’azote, par expérimentation numérique menée dans le cadre d’une approche participative, mobilisant les agriculteurs, les conseillers techniques et les chercheurs. Les résultats indiquent l’importance de la succession et des pratiques culturales, en particulier la mise en place de cultures intermédiaires et la gestion du retournement des luzernières. L’optimisation des pratiques des agriculteurs restent ainsi possible, en réduisant les émissions potentielles d’azote par lixiviation ou par pertes gazeuses, sans léser la fourniture en N pour les cultures.Dans les contextes pédo-technico-climatiques étudiés, les systèmes de grandes cultures en AB peuvent ainsi combiner performance agronomique et faibles impacts environnementaux, lorsque la gestion de l’azote est bien maîtrisée.
... STICS can simulate varied agricultural management practices related to organic matter inputs, cover crops Constantin et al., 2012) and intercrops (Corre-Hellou et al., 2009). A recent improvement of the model allows simulating perennial crops, including their root turnover, using a ''perennial" research version which has been evaluated for Miscanthus (Strullu et al., 2015) and alfalfa (Strullu et al., 2019). This research version has the potential to simulate long-term CAN dynamics in organic cropping systems. ...
... A research version of STICS (v1610) was used in this study to widen the range of possibilities offered by the currently available standard version (v8.4). We improved the version evaluated by Strullu et al. (2015) in order to i) run successive simulations including intercrops; ii) run simulations of grass-clover over successive years; iii) simulate a cover crop undersown in an already established crop and simulate its subsequent growth after harvest of the main crop; iv) account for partial return to soil of grassland cuttings, and v) simulate the enhanced CAN mineralization rates during the year following grassland destruction. The latter process was mimicked by an artificial input of organic matter, from 2.5 to 5.0 t DM ha À1 yr À1 according to the grassland age, with a low C/N ratio (12). ...
Although organic cropping systems are promoted for their environmental benefits, little is known about their long-term impact on nitrogen (N) fate in the soil-plant-atmosphere system. In this paper, we analyze two long-term experiments: DOK in Switzerland (39-yr) and Foulum organic in Denmark (19-yr). Four treatments were considered in each experiment: two conventional treatments with (CONFYM) or without manure (CONMIN), organic with manure (BIOORG) and unfertilized treatment (NOFERT) at DOK; conventional (CGL-CC+IF) and three organic treatments, one with cover crops only (OGL+CC-M) and two including cover crops and grass-clover with (OGC+CC+M) or without manure (OGC+CC-M), at Foulum. STICS model was used to simulate crop production, N surplus, nitrate leaching, gaseous N losses and changes in soil organic N. It was calibrated in the conventional treatments and tested in organic systems. The crop production, N surplus and soil organic N stocks were satisfactorily predicted. The mean N surplus greatly differed between treatments at DOK, from -58 (NOFERT) to +21 kg N ha-1 yr-1 (CONFYM), but only from -9 (OGL+CC-M) to +21 kg N ha-1 yr-1 (OGC+CC+M) in Foulum. Soil N pools declined continuously in both sites and treatments at a rate varying from -18 to -78 kg N ha-1 yr-1, depending on fertilization and crop rotation. The decline was consistent with the observed N surpluses. Although not all simulations could be tested against field observations and despite of prediction uncertainties, simulations confirm the hypothesis that environmental performances resulting from C and N cycles depend more on specificities of individual than nominal treatments. Significant correlations appeared between long-term N surplus and soil N storage and between total N fertilization and total N gaseous losses. Results showed in both experiments that arable organic systems do not systematically have lower N surplus and N losses than conventional ones, providing opportunity for increasing N use efficiency of these systems.
... Indeed, the N remobilisation from perennial organs during regrowth and the presence of a developed root system after cutting enable the plants to partly or totally avoid N stress, leading to more rapid growth and development of the crop. The STICS model has recently been updated for the simulation of perennial crops and now enables the simulation of biomass production and N accumulation as well as their partitioning between perennial, non-perennial organs and roots (Strullu et al., 2014(Strullu et al., , 2015. Therefore, using these new equations initially developed and evaluated for Miscanthus × giganteus should allow us to capture the growth of seedling and regrowing alfalfa crops using a unique set of parameter values. ...
... A branch of version v9 of the model ('perenne_1680') was created and tested to improve simulations of perennial plants (Strullu et al., 2014(Strullu et al., , 2015. A distinction is made between the biomass and N content of non-perennial organs (organs with a lifetime shorter than one year: leaves and stems), perennial organs (organs with a lifetime longer than one year and used as storage organs by the plant: rhizomes or taproot) and roots (with two kinds diameter influencing their lifetime) ( Fig. 1a and b). ...
We adapted the STICS agro-environmental model to simulate the effects of cultivation practices on the biomass production and nitrogen accumulation of perennial crops undergoing regular defoliation, using alfalfa as an example. A unique set of parameters was used to simulate both establishment and regrowth phases over several years, with the assumption that crop growth is driven by interaction between crop development stage and abiotic stresses. The model accurately simulated the total biomass (stems + leaves + crown + taproot + roots) and aboveground biomass of the crop, with model efficiencies of 0.75 and 0.70, respectively, and relative root mean squared errors (rRMSE) of 42% and 36%, respectively. The evaluation results were also satisfactory with respect to total nitrogen content and the aboveground biomass nitrogen content, with model efficiencies of 0.90 and 0.60, respectively, and rRMSE values of 29% and 31%, respectively. The model thus enabled simulations of both the establishment and regrowth of alfalfa and accurately reproduced its seasonal patterns of growth, even though it tended to underestimate spring biomass production. It also produced accurate simulations of the water and nitrate contents of the soil during cropping and after crop destruction. It could therefore be a useful tool regarding the multi-criteria assessment of cropping systems based on alfalfa with respect to their sustainability.
... It only takes into account a quantity of recycled root considered to be released at a single date corresponding either to crop death or crop destruction. A new research version has recently been developed to simulate perennial crops that includes their regular root turnover (Strullu et al., 2014(Strullu et al., , 2015(Strullu et al., , 2019. It can now simulate root biomass accumulation and root decay on a daily basis for perennial and annual crops, and it symmetrically associates C and N fluxes between plants and soil. ...
... The research version enables the simulation of both annual and perennial crops. It was first developed and evaluated by Strullu et al. (2014Strullu et al. ( , 2015 in order to simulate perennial crops such as miscanthus and recently parameterized for alfalfa (Strullu et al., 2019). It therefore makes it possible to simulate crop rotations including alfalfa (lysimeters L3 and L5). ...
... Area cultivated with Miscanthus relies on M. × giganteus and has thus been used since 1983 [6]. It was rapidly identified as providing promising lignocellulosic biomass due to its high biomass yield per area [3], low nitrogen needs [7], and capability to recycle its nitrogen [8]. However, M. × giganteus is sterile and presents genetic uniformity. ...
The cultivation of Miscanthus has attracted growing interest despite its yield instability. Therefore, understanding what causes such instability is of primary interest for breeding. Our objectives were to estimate the genetic parameters—genetic variance and genetic heritability—and genetic correlations for flowering time-related traits in a biparental Miscanthus sinensis diploid population, and divide the year effect into age and growing season effects using a staggered-start design. The population was established with single plants organized with this design and consisted of two genotype groups established twice in a same field, in 2014 and 2015, with a total of 159 genotypes and 82 common genotypes between the groups. Soil conditions being identical between both stands, the growing season conditions corresponded to climatic conditions. All plants were extensively phenotyped for different panicle and anther emergence traits in 2018 and 2019. All traits were delayed by 3 weeks in 2019 compared to 2018, which was explained by climatic conditions that occurred before the floral transition, mainly a 3 °C decrease in temperatures. When dividing the year effect, the genotype × growing season interaction was much higher than the genotype × age interaction. This increased the genotype × growing season interaction variance compared to the genotype × age interaction variance: the growing season effect decreased the genetic parameters for all flowering time-related traits, up to 20% for broad-sense heritability. Interestingly, most traits responded similarly to this effect. Therefore, M. sinensis breeding for flowering time must be conducted under contrasted climatic conditions to select more stable genotypes.
... We are not aware of previous work aiming at comparing the performance of crops to observations, and therefore we may only compare the prediction error of CERES-EGC to studies focusing on single crops. The RMSE obtained here for miscanthus yields (4.7 t DM ha −1 ) is comparable to that calculated for the same crop with the STICS model, which achieved a RMSE of 3.4 t DM ha −1 [36].For the switchgrass, the RMSE calculated here is 4 t DM ha −1 , which corresponds to what is found on average in the literature, where the values of RMSE vary from 2.7 t DM ha −1 [37] to 6.54 t DM ha −1 . Overall, the relative RMSE values (ranging from 31% to 33%) are of the higher end of the results from the simulation of annual arable crops with the STICS model [26]. ...
Crop yields are important items in the economic performance and the environmental impacts of second-generation biofuels. Since they strongly depend on crop management and pedoclimatic conditions, it is important to compare candidate feedstocks to select the most appropriate crops in a given context. Agro-ecosystem models offer a prime route to benchmark crops, but have been little tested from this perspective thus far. Here, we tested whether an agro-ecosystem model (CERES-EGC) was specific enough to capture the differences between miscanthus and switchgrass in northern Europe. The model was compared to field observations obtained in seven long-term trials in France and the UK, involving different fertilizer input rates and harvesting dates. At the calibration site (Estrées-Mons), the mean deviations between simulated and observed crop biomass yields for miscanthus varied between −0.3 t DM ha−1 and 4.2 t DM ha−1. For switchgrass, simulated yields were within 1.0 t DM ha−1 of the experimental data. Observed miscanthus yields were higher than switchgrass yields in most sites and for all treatments, with one exception. Overall, the model captured the differences between both crops adequately, with a mean deviation of 0.46 t DM ha−1, and could be used to guide feedstock selections over larger biomass supply areas.
... Miscanthus was also under the scope of study in terms of supply-chain strategic planning considering the production operations [13]. A simulation model called Simulateur mulTIdiscplinaire pour les Cultures Standard (STICS) was presented (as an improvement of an existing one) for the accurate prediction of the produced biomass in the long-term (up to 20 years from planting time) in various case studies. ...
Various sources of biomass contribute significantly in energy production globally given a series of constraints in its primary production. Green biomass sources (such as perennial grasses), yellow biomass sources (such as crop residues), and woody biomass sources (such as willow) represent the three pillars in biomass production by crops. In this paper, we conducted a comprehensive review on research studies targeted to advancements at biomass supply-chain management in connection to these three types of biomass sources. A framework that classifies the works in problem-based and methodology-based approaches was followed. Results show the use of modern technological means and tools in current management-related problems. From the review, it is evident that the presented up-to-date trends on biomass supply-chain management and the potential for future advanced approach applications play a crucial role on business and sustainability efficiency of biomass supply chain.
There is a growing interest in the cultivation of miscanthus on marginal land, but biomass yields are much lower there than on good farming land. Therefore, understanding what causes such instability is of primary interest for breeding later-flowering but stable miscanthus genotypes. Our objectives were to estimate the genetic parameters -genetic variance and genetic heritability- and genetic correlations for flowering-time-related traits in a biparental Miscanthus sinensis diploid population, and to divide the year effect into both age and climate effects using a staggered-start design. The population was established with single plants organized in a staggered-start design and consisted of two genotype groups established twice, in 2014 and 2015, with a total of 159 genotypes and 82 common genotypes between the two groups. All plants were extensively phenotyped for different panicle and anther emergence traits in 2018 and 2019. All traits were delayed by about 20 days in 2019 compared to 2018, which was explained by climatic conditions that occurred before the floral transition, mainly by a 3°C decrease in maximal and minimal temperatures. When dividing the year interaction effect, the genotype × climate interaction was much higher than the genotype × age interaction. The climate effect not only caused a delay in the flowering time but also involved differential genotype behavior through climate × genotype interactions, which increased the corresponding genotype × climate interaction variance compared to the genotype × age interaction variance: the climate effect decreased the genetic parameters for all flowering-time related traits, up to 20 % for broad-sense heritability. Interestingly, all traits responded similarly to the climate effect, excepting the interval between the start of panicle emergence and that of anther appearance, for which the correlation coefficients were lower due to significant climate interactions, compared to genotype × age interactions. Therefore, M. sinensis breeding for flowering-time related traits must be conducted under contrasted climates in order to select more stable genotypes.
Bioenergy crops are expected to provide biomass as a replacement for fossil resources, but their impact on the water cycle is still under question. This study aimed at both quantifying the ability of bioenergy crops to use soil water and analysing the relationship between their root systems and soil water uptake.
Water content was monitored continuously for 7 years (2007 – 2013) under perennial (Miscanthus × giganteus and Panicum virgatum), semi-perennial (Festuca arundinacea and Medicago sativa) and annual (Sorghum bicolor and × Triticosecale) bioenergy crops. Root distribution was characterized in 2010 down to 3 m depth. Soil water deficit (SWD) was calculated as the difference between field capacity and actual water content.
Maximal SWD (0 – 210 cm) during the growing season was higher for semi-perennials, despite a lower biomass production than perennials. Water capture in deep soil layers was greater under perennials and semi-perennials than under annual crops. A curvilinear asymptotic relationship was found between water capture and root density and described by a model the parameters of which varied between crops, indicating a variable soil water capture for a given root density.
This study provides quantitative information required to simulate the impact of bioenergy crops on drainage and aquifer loading.
Biomass crops mitigate carbon emissions by both fossil fuel substitution and sequestration of carbon in the soil. We grew Miscanthus x giganteus for 16 years at a site in southern Ireland to (i) compare methods of propagation, (ii) compare response to fertilizer application and quantify nutrient offtakes, (iii) measure long-term annual biomass yields, (iv) estimate carbon sequestration to the soil and (v) quantify the carbon mitigation by the crop. There was no significant difference in the yield between plants established from rhizome cuttings or by micro-propagation. Annual off-takes of N and P were easily met by soil reserves, but soil K reserves were low in unfertilized plots. Potassium deficiency was associated with lower harvestable yield. Yields increased for 5 years following establishment but after 10 years showed some decline which could not be accounted for by the climate driven growth model MISCANMOD. Measured yields were normalized to estimate both autumn (at first frost) and spring harvests (15 March of the subsequent year). Average autumn and spring yields over the 15 harvest years were 13.4?1.1 and 9.0?0.7 t DW ha?1 yr?1 respectively. Below ground biomass in February 2002 was 20.6?4.6 t DW ha?1. Miscanthus derived soil organic carbon sequestration detected by a change in 13C signal was 8.9?2.4 t C ha?1 over 15 years. We estimate total carbon mitigation by this crop over 15 years ranged from 5.2 to 7.2 t C ha?1 yr?1 depending on the harvest time.
Miscanthus has been rated as one of the most promising bioenergy crops due to its potential for biomass production. The sustainable production of Miscanthus for bioenergy feedstock partly depends on the varieties that are efficient in terms of nutrient use for the production of biomass. In this study, 23 Miscanthus accessions, collected from wide range of geographic regions, were established early in March 2010 in Wuhan, China. The feedstock was sampled for nutrient concentration determination late in November 2010 and 2011 (at physiological maturity), and harvested early in February 2011 and 2012 (after a killing frost) to evaluate the biomass yield, nutrient concentration and removal. Across these two years, the biomass yield was negatively related to the latitude of the original collection sites. A significant increase in biomass production was observed in the second growth year relative to that in the first growth year among almost all of the Miscanthus accessions. The accessions of MS267 and MS321 only yielded 1.32 and 1.91 ton ha(-1) in 2010, respectively, but the biomass yield increased dramatically to 11.23 and 22.76 ton ha(-1) in 2011, leading to greater nutrient removal by the final harvest and thus the requirement of much more fertilizer in the following years. The accessions MS92, MS145, MS262, MS436 and MS438 established poor biomass yields, averaging <1 ton ha(-1) in the first two years, which suggests that they may be unsuitable for planting in the present environment. Significant differences between accessions were found for the nutrient concentration at maturity and after frost. Notable differences in the nutrient concentration after frost and nutrient removal were presented among the Miscanthus accessions. In addition, the significant difference conferred the possibility of achieving a desirable cultivar with significant biomass yield and relative nutrient removal by harvest. The accessions MS434, MS461 and MS296 had consistently high biomass yield and relatively low nutrient removal, demonstrating desirable characteristics as a low-input bioenergy crop. The results are important for guiding the agronomical practices of nutrient management and genetic improvement for nutrient-use efficiency to increase biomass production with low fertilizer input.
