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Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures., This study was a part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Phase 4 and was supported by the French National Research Institute for Agriculture, Food (INRAE) and the International Maize and Wheat Improvement Center (CIMMYT) through the International Wheat Yield Partnership (IWYP, grant IWYP115). SD and PM acknowledge support from the metaprogram Agriculture and forestry in the face of climate change: adaptation and mitigation (CLIMAE) of INRAE. YC and FT acknowledge support from the National Natural Science Foundation of China (No. 31761143006). RPR and GBM acknowledge financial support from BARISTA project (031B0811A) through ERA-NET SusCrop under EU-FACCE JPI. KCK was funded by the German Federal Ministry of Education and Research (BMBF) through the BonaRes project ’’I4S’’ (031B0513I). AS and TG acknowledge funding by the German Federal Ministry of Education and Research (BMBF) through the BonaRes Project “Soil3” (FKZ 031B0026A). KCK and JEO were supported by the Ministry of Education, Youth and Sports of Czech Republic through SustES—Adaption strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16_019/000797). FE acknowledges support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2070 – 390732324”. TKDW was funded by the German Research Foundation (DFG, Grant Agreement SFB 1253/1 2017). MAS and NS at Rothamsted Research received grant-aided support from the Biotechnology and Biological Sciences Research Council (BBSRC) through Designing Future Wheat [BB/P016855/1] and Achieving Sustainable Agricultural Systems [NE/N018125/1] jointly funded with NERC. TP and FT are supported by the DivCSA project funded by the Academy of Finland (decision no. 316215).

This repositoty contains crop model campaign and output files from the gridded version of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to support the following publication: Partridge, T.F., Winter, Kendall, A.D. Pei, L., Basso, B., Hyndman, D.W., Projecting the value of current and expanded irrigation from groundwater as a climate adaptation strategy. Model Campaign Files: Historic and future campaign files for simulating maize and soybean growth across cultivated areas in the United States. Maize campaign files contain state level oberseved planting dates aquired from the USDA NASS quickstats repository andannual approximations of planted cultivars based on plant progress data and growing degree days. A calibrated soil producitivty coefficient (pDSSAT_calibrated_slpf_maize.nc)is included to adjust simulated maize yields to reported county level yield values through minimzing30-year RMSE values. Future planting dates and cultivar parameters are scaled by changes in growing season meterological metrics for each time period and downscaled global climate model included in this analysis.Please see the corresponding paper for a full description of phenology and yield approximation and estimation of future adaptations. Soybeancampaignfiles contain state level observed planting dates from the USDA NASS quickstats repository and annual estimates of soybean cultivar parameters. Future soybean planting dates are approximated based on changes in growing season conditions for each time period and global climate model inlcuded in this analysis, but cultivar parameters are held constant during future periods.Please see the corresponding paper for a full description of phenology and yield approximation and estimation of future planting dates. Model Output: Gridded crop model simulation outputfor both rainfed and fully irrigated maize and soybean across all cultivated areas in the Conterminous United States from the parallelizedDecision Support System for Agrotechnology Transfer model (pDSSAT). Model runs include three time periods:historical (1981-2010), mid-century (2036-2065), and end-of-century (2071-2100) conditions under moderate and high emissions trajectories(SSP245 and SSP585) from five statistically downscaled CMIP6 global climate models. Future crop simulations approximate changes in planting date andcultivar selection (maize only) and historically planted cultivars. Model output variables include annual values of crop yield (HWAM), total biomass (CWAM), applied Irrigation (IRCM), planting date (PDAT), crop anthesis date (ADAT), crop maturity date (MDAT), seasonal ET (ETCM), growing season ET (ETCP), seasonal drainage from the bottom of the model (DRCM), seasonal precipitation (PRCM), growing season precipitation (PRCP), seasonal runoff (ROCM), growing season average maximum temperature (TMAXA), growing season average minimum temperature (TMINA). water stress during the growing season (WSPDGS), water stress during flowering (WSPDGF), water stress during grain filling (WSPDGS, crop yield irrigation productivity (YPIM), and crop yield precipitation productivity (YPPM).&nbsp

Wheat is the most widely grown food crop, with 761 Mt produced globally in 2020. To meet the expected grain demand by mid-century, wheat breeding strategies must continue to improve upon yield-advancing physiological traits, regardless of climate change impacts. Here, the best performing doubled haploid (DH) crosses with an increased canopy photosynthesis from wheat field experiments in the literature were extrapolated to the global scale with a multi-model ensemble of process-based wheat crop models to estimate global wheat production. The DH field experiments were also used to determine a quantitative relationship between wheat production and solar radiation to estimate genetic yield potential. The multi-model ensemble projected a global annual wheat production of 1050 +/- 145 Mt due to the improved canopy photosynthesis, a 37% increase, without expanding cropping area. Achieving this genetic yield potential would meet the lower estimate of the projected grain demand in 2050, albeit with considerable challenges.

A fibrose hep?tica ? uma doen?a que tem o seu desenvolvimento ligado ao dano cr?nico no f?gado, sendo muitas vezes consequ?ncia de infec??es virais, abuso alco?lico, toxinas, ou ac?mulo de metais. O dano cr?nico no f?gado leva a um processo inflamat?rio que pode resultar na perda do equilibro da s?ntese e degrada??o de elementos de matriz extracelular, sendo a ativa??o das c?lulas hep?ticas estreladas um dos principais fatores respons?veis por iniciar o processo fibr?tico. Geralmente, a progress?o da fibrose hep?tica, ? detectada somente em est?gios avan?ados, podendo resultar no ?ltimo est?gio de doen?as cr?nicas hep?ticas, conhecido como cirrose, com isso levando ao risco de insufici?ncia hep?tica. Atualmente, n?o existe um tratamento bem estabelecido, por?m, se busca primeiramente identificar e remover o agente causador do dano cr?nico e utilizar juntamente terapias capazes de reduzir a ativa??o, prolifera??o ou at? mesmo induzir apoptose em c?lulas estreladas hep?ticas. No entanto, mol?culas com efeito antioxidante t?m mostrado efeitos significativos na diminui??o do dano por estresse oxidativo. Sendo assim, a busca por novos candidatos ao tratamento da fibrose hep?tica ? necess?ria, e para isso, a investiga??o de mol?culas de fontes naturais e renov?veis parece ser promissora, pois sabe-se que os metab?litos secund?rios de muitas esp?cies de plantas possuem potencial para o desenvolvimento de novos f?rmacos. Dessa forma, o presente estudo investigou os efeitos de dois tratamentos que possuem em comum, sua fonte de origem natural e sua composi??o fitoqu?mica, composta principalmente por compostos fen?licos. No primeiro estudo in vitro e in vivo, a mol?cula do metoxieugenol, 5 demonstrou efeito modulador em c?lulas hep?ticas estreladas ativadas, reduzindo seus marcadores de ativa??o (Col-1, ?-SMA e TGF-? e) e revertendo ao seu fen?tipo quiescente. Da mesma forma, o tratamento foi capaz de ativar o fator de transcri??o PPAR-?, e quando na presen?a do seu inibidor, GW9662, o efeito do metoxieugenol foi suprimido, mostrando a intera??o da ativa??o de PPAR-? nos efeitos observados. O efeito hepatoprotetor in vivo em camundongos foi observado, atenuando o desenvolvimento da fibrose e diminuindo a ativa??o de vias inflamat?rias mediadas por NF-kB. No segundo estudo in vivo, o tratamento com o extrato de Baccharis anomala DC. diminui o dano por estresse oxidativo (TBARS e DCFH-DA), reduziu a ativa??o de genes pro inflamat?rios (TNF-?, NF-kB, IL-6 e iNOS) e protegeu o f?gado dos animais do desenvolvimento da fibrose. Os principais componentes do extrato identificados por HPLC foram os ?cidos fen?licos caf?ico, g?lico e cum?rico. Liver fibrosis is a disease that has its development linked to chronic liver damage, often due to viral infections, alcohol and drugs abuse toxins or metal accumulation. Chronic liver damage leads to a continuous inflammatory process that can result in activation of hepatic stellate cells. The activated phenotype of hepatic stellate cells disrupts the balance between synthesis and degradation of extracellular matrix elements, and this process is responsible for initiating the fibrotic process. The progression of liver fibrosis is often detected in late stages of disease and may result in the last stage of chronic liver disease, known as cirrhosis, leading to the risk of liver failure. Currently, liver fibrosis has no well-established treatment, however, the first goal for therapy is to identify and remove the cause of chronic damage and to use therapies capable of reducing activation, proliferation or even inducing apoptosis in hepatic stellate cells. In addition, molecules with an antioxidant effect have shown good effects in decreasing oxidative stress damage. Thus, the search for new candidates for the treatment of liver fibrosis is necessary, and for this, the investigation of molecules from natural and renewable sources seems to be promising, since it is currently known that the secondary metabolites of many plant species have high applicability for the development of new drugs. Thus, the present study investigated the effects of two treatments that have in common, their natural source and their phytochemical composition, mainly composed of phenolic compounds. In the first in vitro and in vivo study, the methoxyeugenol molecule demonstrated a modulatory effect on activated hepatic stellate cells, reducing its activation markers (Col-1, ?-SMA and 7 TGF-? e) and inducing to its quiescent phenotype. Also, the treatment was able to activate the PPAR-? transcription factor, and when in the presence of its inhibitor, GW9662, the effect of methoxyeugenol was suppressed, showing the interaction of PPAR-? activation in the observed effects. Furthermore, it showed hepatoprotective effect in vivo in mice, attenuating the development of fibrosis and decreasing the activation of NF-kB-mediated inflammatory pathways. In the second in vivo study, treatment with B.anomala extract decreases oxidative stress damage (TBARS and DCFH-DA), reduced activation of pro-inflammatory genes (TNF-?, NF-kB, IL-6 and iNOS ) and protected the animals' livers from the development of fibrosis. The main components of the extract identified by HPLC were caffeic, gallic and coumaric phenolic acids. Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES

International audience; Crop yield can be affected by crop water use (evapotranspiration, ET) and vice versa, so when trying to simulate one or the other, it can be important to simulate both well. Method: To determine how well 29 maize growth models can simulate ET, an inter-comparison study was initiated under the umbrella of AgMIP (Agricultural Model Inter-Comparison and Improvement Project) using eddy cova-riance data from Ames, IA as the standard for comparison (Kimball et al., 2019).

Octyl gallate (OG) is an antioxidant commonly used in food, although there is no definition of its acceptable daily intake. There are reports in vitro and in vivo showing that food additives and drugs can alter lipid metabolism. Lipid droplet accumulation in hepatic cells is one of the main findings in the unregulated lipid metabolism and is strongly related to the development of nonalcoholic fatty liver disease (NAFLD). In this study, we investigated the effects of OG on lipid metabolism in the hepatocellular carcinoma cell line (HepG2). The results have shown, for the first time, that treatment with OG increased the overall amount of lipids, the triglyceride concentration, the lipid droplet area, and SREBP-1c and PPAR-γ gene expression. Taken together, the findings indicate that OG induces lipid droplet accumulation in HepG2 cells through the regulation of SREBP-1c and PPAR-γ gene expression without involving mTOR/S6K1 and may contribute to NAFLD when used as a food additive., EXCLI Journal;Vol. 19 2020