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The perfect knowledge of yield before harvest has been a wish puzzling human being since the beginning of agriculture because seasonal forecast of crop yield plays a critical role in decision making for different stakeholders--from farmers to policy makers to governments for food security, to commodities traders. Different methods have been used to forecast yield with different levels of granularity, accuracy and timing. This chapter presents a critical review of the current seasonal crop yield forecasting methods found in the scientific literature. Extensive research has been conducted on crop yield forecast, particularly for wheat, maize, rice, barley, and soybean. Yield forecast are mainly based on field surveys, statistical regressions between historical yield and in-season variables (agrometeorological, or remotely sensed data), crop simulation models, or on integration between statistical modeling with dynamic process-based crop simulation models. A low number of studies rely on field surveys as a means to forecast yield, but they remain the main methods of yield forecast and estimation in several countries (i.e., USA). This chapter aims to report results found in peer-review journals for different crops, methods, geographies, and accuracies, and to end with a critical perspective on the advantage and disadvantage of the different methods currently employed by researchers and stakeholders. [ABSTRACT FROM AUTHOR]

Highlights • Integrates advantages of the microwave and optical satellite data. • Optical image is better at representing maize field boundaries than the SAR image. • Both off or in-season optical images are useful to increase the flexibility of our proposed method. • Time-series PolSAR images are able to distinguish maize from other crops. • Random Forest can be used to reduce data redundancy without reducing accuracy. Abstract Due to its ability to penetrate the cloud, Synthetic Aperture Radar (SAR) has been a great resource for crop mapping. Previous research has verified the applicability of SAR imagery in object-oriented crop classification, however, speckle noise limits the generation of optimal segmentation. This paper proposed an innovative SAR-based maize mapping method supported by optical image, Gaofen-1 PMS, based segmentation, named as parcel-based SAR classification assisted by optical imagery-based segmentation (os-PSC). Polarimetric decomposition was applied to extract polarimetric parameters from multi-temporal RADARSAT-2 data. One Gaofen-1 image was then used for parcel extraction, which was the basic unit for SAR image analysis. The final step was a multi-step classification for final maize mapping including: the potential maize mask extraction, pure/mixed maize parcel division and an integrated maize map production. Results showed that the overall accuracy of the os-PSC method was 89.1%, higher than those of pixel-level classification and SAR-based segmentation methods. The comparison between optical- and SAR-based segmentation demonstrated that optical-based segmentation would be better at representing maize field boundaries than the SAR-based segmentation. Moreover, the parcel- and pixel-level integrated classification will be suitable for many agricultural systems with small landownership where inter-cropping is common. Through integrating advantages of the SAR and optical data, os-PSC shows promising potentials for crop mapping. [ABSTRACT FROM AUTHOR]

The therapeutic potential of Baccharis anomala DC. extracts was evaluated through its cytotoxic and antiproliferative effect and their phenotypic reversion property in activated hepatic stellate cells (HSCs). Baccharis anomala is distributed in Brazil (southeastern and south regions) and used for diuretic effect in folk medicine. Four fractions were obtained from the fractionation of the methanolic extract. Fractions III and IV decreased cell proliferation without increasing cell necrosis markers levels and induced cell cycle arrest in G1 phase. Fraction III induced phenotypic reversion through PPAR-γ activation pathway, while fraction IV did not alter PPAR-α/γ expression levels, suggesting that there is an independent PPAR-α/γ pathway involved. Hydroxybenzoic, chlorogenic and coumaric acids were identified. Fractions III and IV showed antiproliferative effect and ability to induce reversion of activated phenotype of HSCs. [ABSTRACT FROM AUTHOR]

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32‐multi‐model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures (and also considering changes in CO2 and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1 percentage points, representing a relative change of −8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production. Potential benefits of elevated atmospheric CO2 concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low‐rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO2. Introducing genotypes adapted to warmer temperatures could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by −1.1% points, representing a relative change of −8.6%. [ABSTRACT FROM AUTHOR]

Leucine (Leu) is an essential branched-chain amino acid, present in dairy products, which has been investigated for its important role in cell signaling. The effects of Leu on several kinds of cells have been studied, altough little is known on its action upon bone cells and cell proliferation. Thus, the aim of this study is to investigate the effects of Leu supplementation on the proliferation of pre-osteoblasts from MC3T3-E1 lineage. MC3T3-E1 cells were kept in Alpha medium supplemented with 10% fetal bovine serum and 1% antibiotic-antimitotic. Cells were treated during 48 h by adding 50 μM of Leu, which corresponds to a 12.5% increase of the amino acid in the culture medium. The evaluation of viability and proliferation of cultured cells was performed using Trypan Blue dye. In order to identify the mechanisms related to the decreased cellular proliferation, assays were performed to assess cytotoxicity, apotosis, oxidative stress, inflammation, autophagy, senescence and DNA damage. Results showed that Leu supplementation decreased cell proliferation by 40% through mechanisms not related to cell necrosis, apoptosis, oxidative stress, autophagy or inhibition of the mTORC1 pathway. On the other hand, Leu supplementation caused DNA damage. In conclusion, Leu caused a negative impact on bone cell proliferation by inducing cell senescence through DNA damage. [ABSTRACT FROM AUTHOR]

Abstract: Simulation models are extensively used to predict agricultural productivity and greenhouse gas emissions. However, the uncertainties of (reduced) model ensemble simulations have not been assessed systematically for variables affecting food security and climate change mitigation, within multi‐species agricultural contexts. We report an international model comparison and benchmarking exercise, showing the potential of multi‐model ensembles to predict productivity and nitrous oxide (N2O) emissions for wheat, maize, rice and temperate grasslands. Using a multi‐stage modelling protocol, from blind simulations (stage 1) to partial (stages 2–4) and full calibration (stage 5), 24 process‐based biogeochemical models were assessed individually or as an ensemble against long‐term experimental data from four temperate grassland and five arable crop rotation sites spanning four continents. Comparisons were performed by reference to the experimental uncertainties of observed yields and N2O emissions. Results showed that across sites and crop/grassland types, 23%–40% of the uncalibrated individual models were within two standard deviations (SD) of observed yields, while 42 (rice) to 96% (grasslands) of the models were within 1 SD of observed N2O emissions. At stage 1, ensembles formed by the three lowest prediction model errors predicted both yields and N2O emissions within experimental uncertainties for 44% and 33% of the crop and grassland growth cycles, respectively. Partial model calibration (stages 2–4) markedly reduced prediction errors of the full model ensemble E‐median for crop grain yields (from 36% at stage 1 down to 4% on average) and grassland productivity (from 44% to 27%) and to a lesser and more variable extent for N2O emissions. Yield‐scaled N2O emissions (N2O emissions divided by crop yields) were ranked accurately by three‐model ensembles across crop species and field sites. The potential of using process‐based model ensembles to predict jointly productivity and N2O emissions at field scale is discussed. [ABSTRACT FROM AUTHOR]

Crop production in the Central High Plains is at an all-time high due to increased demand for biofuels, food, and animal products. Despite the need to produce more food by mid-century to meet expected population growth, under current management and genetics, crop production is likely to plateau or decline in the Central High Plains due to groundwater withdrawal at rates that greatly exceed recharge to the aquifer. The Central High Plains has experienced a consistent decline in groundwater storage due to groundwater withdrawal for irrigation greatly exceeding natural recharge. In this heavily irrigated region, water is essential to maintain yields and economic stability. Here, we evaluate how current trends in irrigation demand may impact groundwater depletion and quantify the impacts of these changes on crop yield and production through to 2099 using the well-established System Approach to Land Use Sustainability (SALUS) crop model. The results show that status quo groundwater management will likely reduce irrigated corn acreage by ~60% and wheat acreage by ~50%. This widespread forced shift to dryland farming, coupled with the likely effects of climate change, will contribute to overall changes in crop production. Taking into account both changes in yield and available irrigated acreage, corn production would decrease by approximately 60%, while production of wheat would remain fairly steady with a slight increase of about 2%. [ABSTRACT FROM AUTHOR]

The article examines the need of agricultural system to adapt and become more efficient on less farmland, and under climate change threats, in order to feed a growing population with the help of information technology. Topics discussed include role of technologies such as big data in the production of more food when there is less water and land available; and ways in which precision agriculture technologies can help farmers and policymakers address the challenges that agricultural systems face in both the U.S. and other parts of the world.

Syncronizing plant available water with soil nitrogen (N) remains a critical aspect of agronomic management to enhance crop yield, grain quality, farmers' profit, and environmental sustainability. Their interaction is essential expecially in landscapes characterized by a highly spatial and temporal range of pedoclimatic conditions. To support farmers in making more informed decisions, validate dynamic process based crop simulation models have been successfully used to optimize N fertlization. In this study, we aimed to develop a tactical N fertilizer management strategy to increase profitability, improve grain quality and reduce N losses. The SALUS model was tested against measured durum wheat grain yield and grain quality data collected across independent farmers' fields in Tuscany (Italy). The model was then used to optimize N fertilization under different potential plant extractable soil water (PESW) conditions at the second topdressing N fertilization timing. The model was tested against measurements of grain yield and protein concentration at harvest, as well as phenological stage, biomass, and plant N content during the growing season. Simulations were carried out for 30 years of available weather, using different N rates. The simulations allowed the identification of optimal N rates for each PESW condition and soil type concerning economic and environmental sustainability. Results showed higher yield and higher leaching for the silty clay soil (Quercia; QUE) than for the loamy soil (Arbia; ARB). No major differences were predicted for protein content across soils. Profitability and emissions increased as N rate increased. The N fertilization strategy locally adopted by farmers was also analyzed across different PESW conditions at 2nd topdressing fertilization in comparison to other adopted N management strategies (timing of application and fertilization rates). The model showed that the conventional fertilization strategy does not maximize socio-ecological benefits, but was also the lowest among all the strategies tested. The maximum economic benefit for farmers was reached by applying 90 kg N at 1st and 60 kg N at 2nd topdressing fertilization, both in dry (due to sufficient soil water storage in the soil) and wet years. These results provide valuable insights for developing strategies that balance sustainability, resilience, quality, and profitability in wheat crop production in central Italy. • Use of SALUS model to optimize nitrogen (N) fertilization. • Simulation of different potential plant extractable soil water (PESW) conditions. • Simulations were carried out for 30 years, using different N rates. • Identification of N fertilization strategy that maximizes economic returns. [ABSTRACT FROM AUTHOR]

The feedstock supply chain of a biorefinery is critical in determining the economic and environmental performance of biofuels. This study investigated various feedstock supply chains for a centralized biorefinery based on different objective functions and how the biorefinery responds to supply chain volatility. For the analysis, a hypothetical centralized biorefinery was supplied by switchgrass grown on marginal lands in Michigan. From an economic standpoint, the minimum biofuel selling price is an important metric of the objective function, and the greenhouse gas mitigation potential is a similarly important metric for global warming impact. A trade‐off therefore exists between the economic and environmental performance of biofuels under this system configuration. However, when a carbon tax credit is applied to soil organic carbon sequestration in switchgrass production, the metric of the objective function may not be the key factor in establishing a supply chain as long as it is associated with biorefinery capacity as well as economic or environmental values. Year‐to‐year fluctuations in cellulosic biomass yield (supply chain volatility) might also prevent the biorefinery from operating at full capacity. Cellulosic biomass pellets can serve as an auxiliary feedstock for the centralized cellulosic biorefinery system to minimize the impacts of supply chain volatility. [ABSTRACT FROM AUTHOR]

Switchgrass ( Panicum virgatum) productivity on marginal and fertile lands has not been thoroughly evaluated in a systematic manner that includes soil-crop-weather-management interactions and to quantify the risk of failure or success in growing the crop. We used the Systems Approach to Land Use Sustainability ( SALUS) model to identify areas with low risk of failing to having more than 8000 kg ha−1 yr−1 switchgrass aboveground net primary productivity ( ANPP) under rainfed and unfertilized conditions. In addition, we diagnosed constraining factors for switchgrass growth, and tested the effect of nitrogen fertilizer application on plant productivity across Michigan for 30 years under three climate scenarios (baseline climate in 1981-2010, future climate with emissions using RCP 2.6 and RCP 6.0). We determined that <16% of land in Michigan may have at least 8 Mg ha−1 yr−1 ANPP under rainfed and unfertilized management with a low risk of failure. Of the productive low-risk land, about 25% was marginal land, with more than 80% of which was affected by limited water availability due to low soil water-holding capacity and shallow depth. About 80% of the marginal land was N limited under baseline conditions, but that percentage decreased to 58.5% and 42.1% under RCP 2.6 and RCP 6.0 climate scenarios, respectively, partly due to shorter growing season, smaller plants and less N demand. We also found that the majority of Michigan's land could have high switchgrass ANPP and low risk of failure with no more than 60 kgN ha−1 fertilizer input. We believe that the methodology used in this study works at different spatial scales, as well as for other biofuel crops. [ABSTRACT FROM AUTHOR]

Hepatic fibrosis is an extracellular matrix deposition by hepatic stellate cells (HSC). Fibrosis can be caused by iron, which will lead to hydroxyl radical production and cell damage. Fructose-1,6-bisphosphate (FBP) has been shown to deliver therapeutic effects in many pathological situations. In this work, we aimed to test the effects of FBP in HSC cell line, GRX, exposed to an excess of iron (Fe). The Fe-treatment increased cell proliferation and FBP reversed this effect, which was not due to increased necrosis, apoptosis or changes in cell cycle. Oil Red-O staining showed that FBP successfully increased lipid content and lead GRX cells to present characteristics of quiescent HSC. Fe-treatment decreased PPAR-γ expression and increased Col-1 expression. Both effects were reversed by FBP which also decreased TGF-β1 levels in comparison to both control and Fe groups. FBP, also, did not present scavenger activity in the DPPH assay. The treatment with FBP resulted in decreased proliferation rate, Col-1 expression and TGF-β1 release by HSC cells. Furthermore, activated PPAR-γ and increased lipid droplets induce cells to become quiescent, which is a key event to reversion of hepatic fibrosis. FBP also chelates iron showing potential to improve Cell redox state [ABSTRACT FROM AUTHOR]

Many of the irrigated spring wheat regions in the world are also regions with high poverty. The impacts of temperature increase on wheat yield in regions of high poverty are uncertain. A grain yield-temperature response function combined with a quantification of model uncertainty was constructed using a multimodel ensemble from two key irrigated spring wheat areas (India and Sudan) and applied to all irrigated spring wheat regions in the world. Southern Indian and southern Pakistani wheat-growing regions with large yield reductions from increasing temperatures coincided with high poverty headcounts, indicating these areas as future food security 'hot spots'. The multimodel simulations produced a linear absolute decline of yields with increasing temperature, with uncertainty varying with reference temperature at a location. As a consequence of the linear absolute yield decline, the relative yield reductions are larger in low-yielding environments (e.g., high reference temperature areas in southern India, southern Pakistan and all Sudan wheat-growing regions) and farmers in these regions will be hit hardest by increasing temperatures. However, as absolute yield declines are about the same in low- and high-yielding regions, the contributed deficit to national production caused by increasing temperatures is higher in high-yielding environments (e.g., northern India) because these environments contribute more to national wheat production. Although Sudan could potentially grow more wheat if irrigation is available, grain yields would be low due to high reference temperatures, with future increases in temperature further limiting production. [ABSTRACT FROM AUTHOR]