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Accurate evaluation of crop performance and yield prediction at a sub-field scale is essential for achieving high yields while minimizing environmental impacts. Two important approaches for improving agronomic management and predicting future crop yields are the spatial stability of historic crop yields and in-season remote sensing imagery. However, the relative accuracies of these approaches have not been well characterized. In this study, we aim to first, assess the accuracies of yield stability and in-season remote sensing for predicting yield patterns at a sub-field resolution across multiple fields, second, investigate the optimal satellite image date for yield prediction, and third, relate bi-weekly changes in GCVI through the season to yield levels. We hypothesize that historical yield stability zones provide high accuracies in identifying yield patterns compared to within-season remote sensing images. To conduct this evaluation, we utilized biweekly Planet images with visible and near-infrared bands from June through September (2018–2020), along with observed historical yield maps from 115 maize fields located in Indiana, Iowa, Michigan, and Minnesota, USA. We compared the yield stability zones (YSZ) with the in-season remote sensing data, specifically focusing on the green chlorophyll vegetative index (GCVI). Our analysis revealed that yield stability maps provided more accurate estimates of yield within both high stable (HS) and low stable (LS) yield zones within fields compared to any single-image in-season remote sensing model. For the in-season remote sensing predictions, we used linear models for a single image date, as well as multi-linear and random forest models incorporating multiple image dates. Results indicated that the optimal image date for yield prediction varied between and within fields, highlighting the instability of this approach. However, the multi-image models, incorporating multiple image dates, showed improved prediction accuracy, achieving R2 values of 0.66 and 0.86 by September 1st for the multi-linear and random forest models, respectively. Our analysis revealed that most low or high GCVI values of a pixel were consistent across the season (77%), with the greatest instability observed at the beginning and end of the growing season. Interestingly, the historical yield stability zones provided better predictions of yield compared to the bi-weekly dynamics of GCVI. The historically high-yielding areas started with low GCVI early in the season but caught up, while the low-yielding areas with high initial GCVI faltered. In conclusion, the historical yield stability zones in the US Midwest demonstrated robust predictive capacity for in-field heterogeneity in stable zones. Multi-image models showed promise for assessing unstable zones during the season, but it is crucial to link these two approaches to fully capture both stable and unstable zones of crop yield. This study provides opportunities to achieve better precision management and yield prediction by integrating historical crop yields and remote sensing techniques. [ABSTRACT FROM AUTHOR]

Attaining high crop yields and increasing carbon storage in agricultural soils, while avoiding negative environmental impacts on water quality, soil erosion, and biodiversity, requires accurate and precise management of crop inputs and management practices. The long-term analysis of spatial and temporal patterns of crop yields provides insights on how yields vary in a field, with parts of field constantly producing either high yields or low yields and other parts that fluctuate from one year to the next. The concept of yield stability has shown to be informative on how plants translate the effects of environmental conditions (e.g., soil, climate, topography) across the field and over the years in the final yield, and as a valuable layer in developing prescription maps of variable fertilizer rate inputs. Using known relationships between soil health and crop yields, we hypothesize that areas with measured constantly low yield will return low carbon to the soil affecting its heath. On this premises, yield stability zones (YSZ) provide an effective and practical integrative measure of the small-scale variability of soil health on a field relative basis. We tested this hypothesis by measuring various metrics of soil health from commercial farmers' fields in the north central Midwest of the USA in samples replicated across YSZ, using a soil test suite commonly used by producers and stakeholders active in agricultural carbon credits markets. We found that the use of YSZ allowed us to successfully partition field-relative soil organic carbon (SOC) and soil health metrics into statistically distinct regions. Low and stable (LS) yield zones were statistically lower in normalized SOC when compared to high and stable (HS) and unstable (US) yield zones. The drivers of the yield differences within a field are a series of factors ranging from climate, topography and soil. LS zones occur in areas of compacted soil layers or shallow soils (edge of the field) on steeper slopes. The US zones occurring with high water flow accumulation, were more dependent on topography and rainfall. The differences in the components of the overall soil health score (SHS) between these YSZ increased with sample depth suggesting a deeper topsoil in the US and HS zones, driven by the accumulation of water, nutrients, and carbon downslope. Comparison of the field management provided initial evidence that zero tillage reduces the magnitude of the variance in SOC and soil health metrics between the YSZ. [ABSTRACT FROM AUTHOR]

In pulmonary fibrosis, the proliferation of fibroblasts and their differentiation into myofibroblasts is often caused by tissue damage, such as oxidative damage caused by reactive oxygen species, which leads to progressive rupture and thus destruction of the alveolar architecture, resulting in cell proliferation and tissue remodeling. Bezafibrate (BZF) is an important member of the peroxisome proliferator-activated receptor (PPARs) family agonists, used in clinical practice as antihyperlipidemic. However, the antifibrotic effects of BZF are still poorly studied. The objective of this study was to evaluate the effects of BZF on pulmonary oxidative damage in lung fibroblast cells. MRC-5 cells were treated with hydrogen peroxide (H2O2) to induce oxidative stress activation and BZF treatment was administered at the same moment as H2O2 induction. The outcomes evaluated were cell proliferation and cell viability; oxidative stress markers such as reactive oxygen species (ROS), catalase (CAT) levels and thiobarbituric acid reactive substances (TBARS); col-1 and α-SMA mRNA expression and cellular elasticity through Young's modulus analysis evaluated by atomic force microscopy (AFM). The H2O2-induced oxidative damage decreased the cell viability and increased ROS levels and decreased CAT activity in MRC-5 cells. The expression of α-SMA and the cell stiffness increased in response to H2O2 treatment. Treatment with BZF decreased the MRC-5 cell proliferation, ROS levels, reestablished CAT levels, decreased the mRNA expression of type I collagen protein (col-1) and α-smooth muscle actin (α-SMA), and cellular elasticity even with H2O2 induction. Our results suggest that BZF has a potential protective effect on H2O2-induced oxidative stress. These results are based on an in vitro experiment, derived from a fetal lung cell line and may emerge as a possible new therapy for the treatment of pulmonary fibrosis. [ABSTRACT FROM AUTHOR]

Agricultural soils can act as a sink for large quantities of soil organic carbon (SOC) but can also be sources of carbon to the atmosphere. The international standard for assessing SOC stock and measuring stock change stipulates fixed depth sampling to at least 30 cm. The tendency of bulk density (BD) to decrease with decreasing disturbance and increasing SOC concentration and the assumption of constant SOC and BD within this depth profile promotes error in the estimates of SOC stock. A hypothetical but realistic change in BD from 1.5 to 1.1 g cm−3 from successive fixed depth sampling to 30 cm underestimates SOC stock change by 17%. Significant effort has been made to evaluate and reduce this fixed depth error by using the equivalent soil mass (ESM) approach, but with limited adoption. We evaluate the error in SOC stock assessment and change generated from fixed depth measurements over time relative to the ESM approach and propose a correction that can be readily adopted under current sampling and analytical methods. Our approach provides a more accurate estimate of SOC stock accumulation or loss that will help incentivize management practice changes that reduce the environmental impacts of agriculture and further legitimize the accounting practices used by the emerging carbon market and organizations that have pledged to reduce their supply chain greenhouse gas (GHG) footprints. [ABSTRACT FROM AUTHOR]

Acute lung injury (ALI) is a life-threatening acute inflammatory disease with high rates of morbidity and mortality worldwide. 4-Allyl-2,6-dimethoxyphenol (methoxyeugenol), a phenylpropanoid from a synthetic source, exhibits strong anti-inflammatory activity, but its effects on the inflammation of ALI have not yet been reported. In our study, the anti-inflammatory effects of methoxyeugenol were investigated on RAW 264.7 cells and a mice model of ALI. Our results showed that methoxyeugenol (7.5 and 30 µM) attenuated the proliferation and gene expression of interleukin (IL)-6 in LPS-stimulated RAW 264.7 cells. In a mice model of ALI induced with LPS, methoxyeugenol exhibited a significant protective effect, based on influx reduction of macrophages and neutrophils into the lungs; reduction in release of the cytokines IL-6, TNF-α, and IL-10; and in reactive oxygen species (ROS) formation. We show that the anti-inflammatory effects of methoxyeugenol are associated with the suppression of the NFκB signaling pathway. Moreover, we demonstrated for the first time that a phenolic compound, from a synthetic source, protects against lung tissue inflammation and promotes a reduction of NET formation. These findings provided evidence for the use of methoxyeugenol as a new strategy to control inflammation in ALI disease. [ABSTRACT FROM AUTHOR]

Understanding subfield crop yields and temporal stability is critical to better manage crops. Several algorithms have proposed to study within-field temporal variability but they were mostly limited to few fields. In this study, a large dataset composed of 5520 yield maps from 768 fields provided by farmers was used to investigate the influence of subfield yield distribution skewness on temporal variability. The data are used to test two intuitive algorithms for mapping stability: one based on standard deviation and the second based on pixel ranking and percentiles. The analysis of yield monitor data indicates that yield distribution is asymmetric, and it tends to be negatively skewed (p < 0.05) for all of the four crops analyzed, meaning that low yielding areas are lower in frequency but cover a larger range of low values. The mean yield difference between the pixels classified as high-and-stable and the pixels classified as low-and-stable was 1.04 Mg ha−1 for maize, 0.39 Mg ha−1 for cotton, 0.34 Mg ha−1 for soybean, and 0.59 Mg ha−1 for wheat. The yield of the unstable zones was similar to the pixels classified as low-and-stable by the standard deviation algorithm, whereas the two-way outlier algorithm did not exhibit this bias. Furthermore, the increase in the number years of yield maps available induced a modest but significant increase in the certainty of stability classifications, and the proportion of unstable pixels increased with the precipitation heterogeneity between the years comprising the yield maps. [ABSTRACT FROM AUTHOR]

Excessive phosphorus (P) applications to croplands can contribute to eutrophication of surface waters through surface runoff and subsurface (leaching) losses. We analyzed leaching losses of total dissolved P (TDP) from no-till corn, hybrid poplar (Populus nigra X P. maximowiczii), switchgrass (Panicum virgatum), miscanthus (Miscanthus giganteus), native grasses, and restored prairie, all planted in 2008 on former cropland in Michigan, USA. All crops except corn (13 kg P ha−1 year−1) were grown without P fertilization. Biomass was harvested at the end of each growing season except for poplar. Soil water at 1.2 m depth was sampled weekly to biweekly for TDP determination during March–November 2009–2016 using tension lysimeters. Soil test P (0–25 cm depth) was measured every autumn. Soil water TDP concentrations were usually below levels where eutrophication of surface waters is frequently observed (> 0.02 mg L−1) but often higher than in deep groundwater or nearby streams and lakes. Rates of P leaching, estimated from measured concentrations and modeled drainage, did not differ statistically among cropping systems across years; 7-year cropping system means ranged from 0.035 to 0.072 kg P ha−1 year−1 with large interannual variation. Leached P was positively related to STP, which decreased over the 7 years in all systems. These results indicate that both P-fertilized and unfertilized cropping systems may leach legacy P from past cropland management. [ABSTRACT FROM AUTHOR]

Warming generally leads to increased evaporative demand, altering the amount of water needed for growing crops. For the Midwest, some studies have suggested that reaching yield targets by 2050 will not be possible without additional precipitation or large expansion of irrigation. Here, we show that this claim is not supported by the historical summer climate trends, which indicate that the warming of daily average temperatures is largely driven by increases in minimum temperatures, while maximum temperatures have decreased. This has translated into a net decrease in vapor pressure deficit (VPD) and potential evapotranspiration (PET). With the increasing rainfall, this suggests that crop water deficits have likely become less frequent in the region despite the warming climate. By projecting these trends into 2050 and ancillary use of a crop model, we estimate minor changes in PET that would have minimal effects on corn yields (<6%) under persistence of these trends. Warming in the US Midwest is believed to increase the water needed to grow crops. This study finds that, on the contrary, due to rising rainfall and minimum temperature, and decreasing maximum temperature, potential crop water demand remains unchanged despite the warming climate. [ABSTRACT FROM AUTHOR]

Summary: Hepatocellular carcinoma (HCC) is the most prevalent type of tumor among primary liver tumors and is the second highest cause of cancer-related deaths worldwide. Current therapies are controversial, and more research is needed to identify effective treatments. A new synthetic compound, potassium 5-cyano-4-methyl-6-oxo-1,6-dihydropyridine-2-olate (CPBMF65), is a potent inhibitor of the human uridine phosphorylase-1 (hUP1) enzyme, which controls the cell concentration of uridine (Urd). Urd is a natural pyrimidine nucleoside involved in cellular processes, such as RNA synthesis. In addition, it is considered a promising biochemical modulator, as it may reduce the toxicity caused by chemotherapeutics without impairing its anti-tumor activity. Thus, the objective of this study is to evaluate the effects of CPBMF65 on the proliferation of the human hepatocellular carcinoma cell line (HepG2). Cell proliferation, cytotoxicity, apoptosis, senescence, autophagy, intracellular Urd levels, cell cycle arrest, and drug resistance were analyzed. Results demonstrate that, after incubation with CPBMF65, HepG2 cell proliferation decreased, mainly through cell cycle arrest and senescence, increasing the levels of intracellular Urd and maintaining cell proliferation reduced during chronic treatment. In conclusion, results show, for the first time, the ability of a hUP1 inhibitor (CPBMF65) to reduce HepG2 cell proliferation through cell cycle arrest and senescence. [ABSTRACT FROM AUTHOR]

Short term food security issues require reliable crop forecasting data to identify the population at risk of food insecurity and quantify the anticipated food deficit. The assessment of the current early warning and crop forecasting system which was designed in mid 80's identified a number of deficiencies that have serious impact on the timeliness and reliability of the data. We developed a new method to forecast maize yield across smallholder farmers' fields in Tanzania (Morogoro, Kagera and Tanga districts) by integrating field-based survey with a process-based mechanistic crop simulation model. The method has shown to provide acceptable forecasts (r2 values of 0.94, 0.88 and 0.5 in Tanga, Morogoro and Kagera districts, respectively) 14–77 days prior to crop harvest across the three districts, in spite of wide range of maize growing conditions (final yields ranged from 0.2–5.9 t/ha). This study highlights the possibility of achieving accurate yield forecasts, and scaling up to regional levels for smallholder farming systems, where uncertainties in management conditions and field size are large. [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]

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]

Predicting and accounting for the nitrogen (N) supplied by organic amendments can reduce the application of mineral N fertilizer without yield penalty as well as decreasing NO emissions. Automated chambers were employed over 12 months to measure NO emissions together with soil mineral N and crop yields from optimized organic and conventional N management in an intensive, irrigated vegetable rotation in subtropical Australia. Five different fertilizer strategies were investigated. The conventional urea application rate (CONV) was compared to raw (Ma) and composted (Co) chicken manure at a conventional (Ma + CONV, Co + CONV) and reduced urea rate (Ma + Rd, Co + Rd). The reduced rates represented an 18-20 % less urea being applied and were calculated by accounting for the potential N mineralized from organic amendments. Three consecutive crops (green beans, broccoli, and lettuce) plus a cover crop (sorghum) showed no significant differences in yield and biomass production between treatments receiving either organic or mineral fertilizer. Overall, fertilizer-induced emissions were low and were unaffected by compost addition. Raw organic amendments increased NO emissions with the first crop in the rotation contributing the highest emissions, 38-57 % of the annual cumulative NO. The incorporation of post-harvest crop residues was a substantial trigger for NO emissions, while the application of N fertilizer and heavy rainfall events had only marginal effects. Highest cumulative NO emissions of 1748 g NO-N ha yr were measured in the Ma + Rd treatment, with the compost treatments reducing NO emissions by up to 45 % with emissions similar to the zero N application (0N). This study demonstrated that the strategic application of composted organic amendments integrated with reducing N fertilizer rates by up to 20 % can be an effective pathway to reduce greenhouse gas (GHG) emissions without compromising crop growth and yield. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer application can lead to increased crop yields but its use efficiency remains generally low which can cause environmental problems related to nitrate leaching as well as nitrous oxide emissions to the atmosphere. The objectives of this study were to: (i) to demonstrate that properly identified variable rates of N fertilizer lead to higher use efficiency and (ii) to evaluate the capability of high spectral resolution satellite to detect within-field crop N response using vegetation indices. This study evaluated three N fertilizer rates (30, 70, and 90 kg N ha) and their response on durum wheat yield across the field. Fertilizer rates were identified through the adoption of the SALUS crop model, in addition to a spatial and temporal analysis of observed wheat grain yield maps. Hand-held and high spectral resolution satellite remote sensing data were collected before and after a spring side dress fertilizer application with FieldSpec, HandHeld Pro and RapidEye™, respectively. Twenty-four vegetation indices were compared to evaluate yield performance. Stable zones within the field were defined by analyzing the spatial stability of crop yield of the previous 5 years (Basso et al. in Eur J Agron 51: 5, ). The canopy chlorophyll content index (CCCI) discriminated crop N response with an overall accuracy of 71 %, which allowed assessment of the efficiency of the second N application in a spatial context across each management zone. The CCCI derived from remotely sensed images acquired before and after N fertilization proved useful in understanding the spatial response of crops to N fertilization. Spectral data collected with a handheld radiometer on 100 grid points were used to validate spectral data from remote sensing images in the same locations and to verify the efficacy of the correction algorithms of the raw data. This procedure was presented to demonstrate the accuracy of the satellite data when compared to the handheld data. Variable rate N increased nitrogen use efficiency with differences that can have significant implication to the NO emissions, nitrate leaching, and farmer's profit. [ABSTRACT FROM AUTHOR]

At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of −1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha) of the distribution. [ABSTRACT FROM AUTHOR]

Capsaicin, the active component of chili pepper, has been reported to have antiproliferative and anti-inflammatory effects on a variety of cell lines. In the current study, we aimed to investigate the effects of capsaicin during HSC activation and maintenance. Activated and freshly isolated HSCs were treated with capsaicin. Proliferation was measured by incorporation of EdU. Cell cycle arrest and apoptosis were investigated using flow cytometry. The migratory response to chemotactic stimuli was evaluated by a modified Boyden chamber assay. Activation markers and inflammatory cytokines were determined by qPCR, immunocytochemistry, and flow cytometry. Our results show that capsaicin reduces HSC proliferation, migration, and expression of profibrogenic markers of activated and primary mouse HSCs. In conclusion, the present study shows that capsaicin modulates proliferation, migration, and activation of HSC in vitro. [ABSTRACT FROM AUTHOR]

Crop models are one of the most commonly used tools to assess the impact of climate variability and change on crop production. However, before the impact of projected climate changes on crop production can be addressed, a necessary first step is the assessment of the inherent uncertainty and limitations of the forcing data used in these crop models. In this paper, we evaluate the simulated crop production using separate crop models for maize (summer crop) and wheat (winter crop) over six different locations in the Southeastern United States forced with multiple sources of actual and simulated weather data. The paper compares the crop production simulated by a crop model for maize and wheat during a historical period, using daily weather data from three sources: station observations, dynamically downscaled global reanalysis, and dynamically downscaled historical climate model simulations from two global circulation models (GCMs). The same regional climate model is used to downscale the global reanalysis and both global circulation models' historical simulation. The average simulated yield derived from bias-corrected downscaled reanalysis or bias-corrected downscaled GCMs were, in most cases, not statistically different from observations. Statistical differences of the average yields, generated from observed or downscaled GCM weather, were found in some locations under rainfed and irrigated scenarios, and more frequently in winter (wheat) than in summer (maize). The inter-annual variance of simulated crop yield using GCM downscaled data was frequently overestimated, especially in summer. An analysis of the bias-corrected climate data showed that despite the agreement between the modeled and the observed means of temperatures, solar radiation, and precipitation, their intra-seasonal variances were often significantly different from observations. Therefore, due to this high intra-seasonal variability, a cautious approach is required when using climate model data for historical yield analysis and future climate change impact assessments. [ABSTRACT FROM AUTHOR]

Turkey oak ( Quercus cerris L.) is characterized by some technological and aesthetical factors limiting its market value from its great potential. In this study, the effect of direct and indirect steaming on reduction in equilibrium moisture content (EMC) and colour variations was evaluated using a hyperspectral radiometer. Steaming treatments were carried out at 80°C for 48 h, and 120°C for 18 and 24 h, showing a reduction in EMC in the order of 8.1, 28.5 and 13.5, respectively, as well as very significant lightness (L) and hue (h°) modifications in comparison with untreated specimens. The spectral signature analysis confirmed that hydrothermal treatments modify wood sensibility to the light source in the entire spectrum range. The study supports the validity of hydrothermal treatments for improving technological and aesthetical properties of Turkey oak. [ABSTRACT FROM AUTHOR]

An objective for applying a Crop Simulation Model (CSM) in precision agriculture is to explain the spatial variability of crop performance and to help guide decisions related to the site-specific management of crop inputs. CSMs require inputs related to soil, climate, management, and crop genetic information to simulate crop yield. In practice, however, measuring these inputs at the desired high spatial resolution is prohibitively expensive. We propose a Bayesian modeling framework that melds a CSM with sparse data from a yield monitoring system to deliver location specific posterior predicted distributions of yield and associated unobserved spatially varying CSM parameter inputs. These products facilitate exploration of process-based explanations for yield variability. The proposed Bayesian melding model consists of a systemic component representing output from the physical model and a residual spatial process that compensates for the bias in the physical model. The spatially varying inputs to the systemic component arise from a multivariate Gaussian process, while the residual component is modeled using a univariate Gaussian process. Due to the large number of observed locations in the motivating dataset, we seek dimension reduction using low-rank predictive processes to ease the computational burden. The proposed model is illustrated using the Crop Environment Resources Synthesis (CERES)-Wheat CSM and wheat yield data collected in Foggia, Italy. [ABSTRACT FROM AUTHOR]

Loss of reactive nitrogen (N) from agricultural fields in the U.S. Midwest is a principal cause of the persistent hypoxic zone in the Gulf of Mexico. We used eight years of high resolution satellite imagery, field boundaries, crop data layers, and yield stability classes to estimate the proportion of N fertilizer removed in harvest (NUE) versus left as surplus N in 8 million corn (Zea mays) fields at subfield resolutions of 30 × 30 m (0.09 ha) across 30 million ha of 10 Midwest states. On average, 26% of subfields in the region could be classified as stable low yield, 28% as unstable (low yield some years, high others), and 46% as stable high yield. NUE varied from 48% in stable low yield areas to 88% in stable high yield areas. We estimate regional average N losses of 1.12 (0.64–1.67) Tg N y−1 from stable and unstable low yield areas, corresponding to USD 485 (267–702) million dollars of fertilizer value, 79 (45–113) TJ of energy, and greenhouse gas emissions of 6.8 (3.4–10.1) MMT CO2 equivalents. Matching N fertilizer rates to crop yield stability classes could reduce regional reactive N losses substantially with no impact on crop yields, thereby enhancing the sustainability of corn-based cropping systems. [ABSTRACT FROM AUTHOR]

Not all areas of a farmer’s field are equal; some always produce more relative to the rest of the field, others always less, while still other areas fluctuate in their production capacity from one year to the next, depending on the interaction between climate, soil, topography and management. Understanding why the yield in certain portions of a field has a high variability over time—we call these areas unstable—is of paramount importance both from an economic and an environmental point of view, as it is through the better management of these areas that we can improve yields or reduce input costs and environmental impact. In this research, we analyzed data from 338 fields cultivated with maize, soybean, wheat and cotton in the US Midwest to understand how topographic attributes and rain affect yield stability over time. In addition to this high resolution yield monitor dataset, we used publicly available data on topography, rain and soil information to test the hypothesis that within-field areas characterized by a low topographic wetness index (proxy for areas with probability of lower water content) always perform poorly (low and stable yield) compared to the rest of the field because they are drier, and that areas of a field characterized by a mid-high wetness index (high and stable yield) always perform well relative to rest of the field because they have greater water availability to plants. The relative performance of areas of a field with a very high wetness index (e.g. depressions) strongly depends on rain patterns because they may be waterlogged in wet years, yielding less than the rest of the field, or wetter during dry years, yielding more than the rest of the field. We present three different observations from this dataset to support our hypothesis. First, we show that the average topographic wetness index in the different stability zones is lower in low and stable yield areas, high in high and stable yield areas and even higher in unstable yield areas (p < 0.05). Second, we show that in dry years (low precipitation at plant emergence or in July), unstable zones perform relatively better compared to the rest of the field. Third, we show that temporal yield variability is positively correlated (p < 0.05) with the probability of observing gleying processes associated with waterlogging for part of the year. These findings shed light on mechanisms underlying temporal variability of yield and can help guide management solutions to increase profit and improve environmental quality. [ABSTRACT FROM AUTHOR]

A correction to the article "Effect of organic and mineral N fertilizers on N2O emissions from an intensive vegetable rotation" published in the June 11, 2016 is presented.

A letter to the editor is presented in response to an article published in the previous issue by D. B. Lobell and colleagues about the effects of temperature and rainfall on maize yield in the U.S.