Given the importance of crop yield and yield progress, this review endeavours to clearly define the different representations of yield, discuss their measurement, and elucidate some controlling ...factors in yield change. For a field, farm, district or region, average farm or actual yield (FY) is central, but potential (and water-limited potential) yield (PY, PYw) is also an important yardstick. PY is defined here as the measured yield of the best cultivar, grown with optimal agronomy and without manageable biotic and abiotic stresses, under natural resource and cropping system conditions representative of the target area. Economic yield, governed by considerations of profit and risk, and record and theoretical yield, complete the picture. Yield gap is defined as the difference between PY and FY under the same environment. Across most crop-region combinations in the last 2 to 3 decades, FY progress has been associated with both PY progress and yield gap closing, and a simple model, based on linear regression against time, is proposed for understanding this. PY advance is the result of plant breeding and new agronomy (and their interaction, usually positive), while yield gap closing arises with the adoption by farmers of known innovations faster than new ones are invented. Unravelling the true technological component in apparent progress in PY, and especially in FY, is not necessarily simple, and confounding factors are listed and discussed.
The aim of this paper is to describe the evolving yield behavior of dual-phase steels during plastic deformation characterized for ten loading paths using a series of mechanical tests including ...uniaxial tension, uniaxial compression, in-plane torsion and cruciform biaxial tension with the aid of digital image correlation techniques for strain measurement. Large plastic strains in the gauge area of cruciform specimens tested were enabled by a laser deposition process to strengthen the arms in order to measure deformation behavior of the sheet without arbitrarily thinning the gauge section. Experimental yield loci were determined for three dual phase steels with different strength levels up to equivalent plastic strains of ˜0.11 for DP590, ˜0.07 for DP780, ˜0.05 for DP980, respectively. Several existing anisotropic yield criteria under both associated flow rule (AFR) and non-associated flow rule (non-AFR) were applied to describe the anisotropic yield behavior of these DP steels. A comparative study was preformed to validate prediction accuracy of yield criteria with experimental measurements including yield loci, yield stresses and rφ -values under uniaxial tension in seven orientations as well as yield stresses and rb -value under equi-biaxial tension. The results show that non-AFR significantly improved prediction accuracy of both stresses and r-values simultaneously. Under non-AFR, an order of two in the yield stress function is sufficient to accurately predict flow stresses. The evolution of both yield stress and plastic potential surfaces of DP steels were illustrated by changing parameters in the yield criterion as functions of equivalent compliance λ¯.
Yield development of agricultural crops over time is not merely the result of genetic and agronomic factors, but also the outcome of a complex interaction between climatic and site‐specific soil ...conditions. However, the influence of past climatic changes on yield trends remains unclear, particularly under consideration of different soil conditions. In this study, we determine the effects of single agrometeorological factors on the evolution of German winter wheat yields between 1958 and 2015 from 298 published nitrogen (N)‐fertilization experiments. For this purpose, we separate climatic from genetic and agronomic yield effects using linear mixed effect models and estimate the climatic influence based on a coefficient of determination for these models. We found earlier occurrence of wheat growth stages, and shortened development phases except for the phase of stem elongation. Agrometeorological factors are defined as climate covariates related to the growth of winter wheat. Our results indicate a general and strong effect of agroclimatic changes on yield development, in particular due to increasing mean temperatures and heat stress events during the grain‐filling period. Except for heat stress days with more than 31°C, yields at sites with higher yield potential were less prone to adverse weather effects than at sites with lower yield potential. Our data furthermore reveal that a potential yield levelling, as found for many West‐European countries, predominantly occurred at sites with relatively low yield potential and about one decade earlier (mid‐1980s) compared to averaged yield data for the whole of Germany. Interestingly, effects related to high precipitation events were less relevant than temperature‐related effects and became relevant particularly during the vegetative growth phase. Overall, this study emphasizes the sensitivity of yield productivity to past climatic conditions, under consideration of regional differences, and underlines the necessity of finding adaptation strategies for food production under ongoing and expected climate change.
Climatic changes influence the long‐term yield development of crops. This study, therefore, determines the influence of single agrometeorological factors on the winter wheat yield development in Germany between 1958 and 2015 at sites of lower and higher soil quality. Except for the number of heat stress days with more than 31°C, yields were in particular afflicted at sites with lower soil quality by increasing mean temperatures and heat stress events during the grain‐filling period. Sites with higher soil quality were less prone to adverse weather effects.
ABSTRACT
Climate variability and change can have important impacts for crop production. Therefore, the aim of this study is to investigate projections of the wheat yield in an increasingly warm ...climate. To address our objectives, we determined relationships between wheat yield in Spain and large‐scale variables. Partial least squares regression was applied to determine the modes of the climate variables that drive wheat‐yield variability, revealing a significant influence of surface solar radiation. Based on seasonal patterns of solar radiation, we determine models to estimate inter‐annual wheat‐yield variability. We find that the performance of the models based on solar radiation is better than that of earlier studies based on temperatures and precipitation variables. In this way, we use simulations of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to project wheat‐yield trend under warming climate by implementing direct statistical downscaling. The expected range of projected wheat yield trend for 21st century indicates decreases of about 6–8% across Spain. The suggested models could be applied for adaptation and planning.
► We define the concepts relevant for yield gap analysis. ► We review different methods for local and global yield gap analyses. ► Global methods are coarse and local studies use different methods. ► ...A number of methods is compared using data sets from three regions. ► Components of a protocol for global yield gap analysis with local relevance are proposed.
Yields of crops must increase substantially over the coming decades to keep pace with global food demand driven by population and income growth. Ultimately global food production capacity will be limited by the amount of land and water resources available and suitable for crop production, and by biophysical limits on crop growth. Quantifying food production capacity on every hectare of current farmland in a consistent and transparent manner is needed to inform decisions on policy, research, development and investment that aim to affect future crop yield and land use, and to inform on-ground action by local farmers through their knowledge networks. Crop production capacity can be evaluated by estimating potential yield and water-limited yield levels as benchmarks for crop production under, respectively, irrigated and rainfed conditions. The differences between these theoretical yield levels and actual farmers’ yields define the yield gaps, and precise spatially explicit knowledge about these yield gaps is essential to guide sustainable intensification of agriculture. This paper reviews methods to estimate yield gaps, with a focus on the local-to-global relevance of outcomes. Empirical methods estimate yield potential from 90 to 95th percentiles of farmers’ yields, maximum yields from experiment stations, growers’ yield contests or boundary functions; these are compared with crop simulation of potential or water-limited yields. Comparisons utilize detailed data sets from western Kenya, Nebraska (USA) and Victoria (Australia). We then review global studies, often performed by non-agricultural scientists, aimed at yield and sometimes yield gap assessment and compare several studies in terms of outcomes for regions in Nebraska, Kenya and The Netherlands. Based on our review we recommend key components for a yield gap assessment that can be applied at local to global scales. Given lack of data for some regions, the protocol recommends use of a tiered approach with preferred use of crop growth simulation models applied to relatively homogenous climate zones for which measured weather data are available. Within such zones simulations are performed for the dominant soils and cropping systems considering current spatial distribution of crops. Need for accurate agronomic and current yield data together with calibrated and validated crop models and upscaling methods is emphasized. The bottom-up application of this global protocol allows verification of estimated yield gaps with on-farm data and experiments.
•Cruciform biaxial tensile specimens in RD/TD and 45°/135° directions are tested.•Developed new material parameters calibration procedure for Poly6 yield criterion.•Improved evaluation strategy to ...verify validity and applicability of yield criteria.•Biaxial data measured in RD/TD are insufficient to confirm the material models.•Directions of plastic strain rate are critical to evaluate plastic potential functions.
Uniaxial and cruciform biaxial tensile tests are performed on a face-centered cubic material AA6016-T4 and a body-centered cubic material DP490 under 19 different loading paths, i.e., uniaxial tension in seven directions, simple shear along the rolling direction, and biaxial tension in rolling/transverse and 45°/135° directions, with seven and four stress ratios, respectively. The ability of several yield criteria to describe the plastic anisotropy for the tested materials, under the associated and non-associated flow rules, is evaluated systematically. A new evaluation strategy to check the validity and applicability of the material models is proposed in this study. This strategy is different from the traditional evaluation strategy in that the biaxial tensile mechanical properties measured in the 45°/135° sampling direction are included in the investigation scope, and it is not limited to the rolling/transverse sampling direction, i.e., the yield stress functions are evaluated by comparing the experimental and predicted uniaxial yield stresses and plastic work contours on the normal and diagonal planes. Further, the plastic potential functions are confirmed by the description accuracy of uniaxial rα-values and the directions of plastic strain rate in the rolling/transverse and 45°/135° directions. A new analytical calibration program is developed for the material parameters of the Poly6 yield criterion related to normal (a1,a2,...,a7) and shear stress components (a8,a9,...,a16), which can further introduce the yield stresses under the near plane strain states (σPS0, σPS45, and σPS90) and pure shear yield stress along the rolling direction (τ0). The results indicate that the new calibration strategy of Analytical Poly6-II&2 can accurately describe the anisotropic yield behavior of the tested materials compared with other advanced yield criteria, especially for plastic work contours on the diagonal plane. Significant anisotropic yield behavior was observed under biaxial tensile stress states with the same loading ratio in different sampling directions. Therefore, investigating the prediction accuracy of the biaxial tensile mechanical properties in only the rolling/transverse sampling direction is insufficient for evaluating the effectiveness of the material models; the mechanical properties at the initial yield point cannot fully reflect the plastic anisotropy of the materials. The material parameters of the Analytical Poly6-II&2 yield criterion are expressed as functions of equivalent plastic strain, which can continuously capture the evolution of the anisotropic yield behavior for AA6016-T4 and DP490. Three different calibration strategies of the material parameter a16 are evaluated in this study. These strategies do not affect the description ability of the uniaxial yield stresses, rα-values, and plastic work contours on the normal plane; however, they influence the calculation results of plastic work contours on the diagonal plane. For attaining a balanced prediction accuracy, it is recommended to provide the values of both τ0 and σPS45.
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Yield curve modeling and forecasting Diebold, Francis X; Diebold, Francis X; Rudebusch, Glenn D
2013., 20130115, 2013, 2012-12-26, 20130101
eBook
Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, ...structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed.
Based on the Econometric and Tinbergen Institutes Lectures,Yield Curve Modeling and Forecastingcontains essential tools with enhanced utility for academics, central banks, governments, and industry.
The potential yield of crops is not usually realised on farms creating yield gaps. Methods are needed to diagnose yield gaps and to select interventions. One method is the boundary line model in ...which the upper bound of a plot of yield against a potentially limiting factor is viewed as the most efficient response to that factor and anything below it has a yield gap caused by inefficiency of other factors. If many factors are studied, the cause of the yield gap can be identified (yield gap analysis, YGA). Though the boundary line is agronomically interpretable, its estimation and statistical inference are not straightforward and there is no standard method to fit it to data.
We review the different methods used to fit the boundary line, their strengths and weaknesses, interpretation, factors influencing the choice of method and its impact on YGA.
We searched for articles that used boundary lines for YGA, using the Boolean “Boundary*” AND “Yield gap*” in the Web of Science.
Methods used to fit boundary lines include heuristic methods (visual, Binning, BOLIDES and quantile regression) and statistical methods (Makowski quantile regression, censored bivariate model and stochastic frontier analysis). In contrast to heuristic methods, which in practice require ad hoc decisions such as the quantile value in the quantile regression method, statistical methods are typically objective, repeatable and offer a consistent basis to quantify parameter uncertainty. Nonetheless, most studies utilise heuristic methods (87% of the articles reviewed) which are easier to use. The boundary line is usually interpreted in terms of the Law of the Minimum or the Law of Optimum to explain yield gaps. Although these models are useful, their interpretation holds only if the modelled upper limit represents a boundary and not just a particular realization of the upper tail of the distribution of yield. Therefore, exploratory and inferential analysis tools that inform boundary characteristics in data are required if the boundary line is to be useful for YGA.
Statistical methods to fit boundary line models consistently and repeatably, with quantified uncertainty and evidence that there is a boundary limiting the observed yields, are required if boundary line methods are to be used for YGA. Practical and conceptual obstacles to the use of statistical methods are required. Bayesian methods should also be explored to extend further the capacity to interpret uncertainty of boundary line models.
•The boundary line model for the yield gap can be interpreted under different agronomic hypotheses.•Boundary lines are widely-used for yield gap analysis but there is no standard method as yet.•Heuristic methods are more widely-used than statistical models, with no formal account of uncertainty.•Consistent methods for outliers, and exploratory examination of the proposed boundary are needed.•Agronomists need user-friendly software which encodes repeatable and robust boundary line methods.
Arbuscular mycorrhizal fungi (AMF) are ubiquitous in agroecosystems and often stated to be critical for crop yield and agroecosystem sustainability. However, should farmers modify management to ...enhance the abundance and diversity of AMF? We address this question with a focus on field experiments that manipulated colonisation by indigenous AMF and report crop yield, or investigated community structure and diversity of AMF. We find that the literature presents an overly optimistic view of the importance of AMF in crop yield due, in part, to flawed methodology in field experiments. A small body of rigorous research only sometimes reports a positive impact of high colonisation on crop yield, even under phosphorus limitation. We suggest that studies vary due to the interaction of environment and genotype (crop and mycorrhizal fungal). We also find that the literature can be overly pessimistic about the impact of some common agricultural practices on mycorrhizal fungal communities and that interactions between AMF and soil microbes are complex and poorly understood. We provide a template for future field experiments and a list of research priorities, including phosphorus-efficient agroecosystems. However, we conclude that management of AMF by farmers will not be warranted until benefits are demonstrated at the field scale under prescribed agronomic management.
For sustainable biomass production of Miscanthus × giganteus (hereafter miscanthus), understanding the impact of stand age and nitrogen (N) fertilization on biomass yield is crucial. This study ...investigated the effects of varying N fertilization rates (0, 56, 112, and 168 kg N ha−1) on yield components (tiller height, density, and weight) and their correlations with end‐of‐season biomass yield in miscanthus. We also explored end‐of‐season biomass yield prediction using in‐season traits (canopy height, leaf area index, and leaf chlorophyll content LCC). The study was conducted at two sites in Illinois: a previously unfertilized 10‐year‐old miscanthus research stand at Urbana and a 16‐year‐old commercial stand at Pesotum with a history of annual 56N application. Results from 2018 to 2021 in Urbana and 2020 to 2021 in Pesotum showed increased biomass yields with N fertilization, varying by rate, year, and location. Biomass yield in Pesotum peaked at 56N, while in Urbana, it increased significantly at 112 kg N ha−1. Biomass yield was strongly correlated with tiller height and weight measured at Urbana across N rates. Morphological traits measured every 2–3 weeks during the 2020 and 2021 growing seasons showed that canopy height was the strongest single predictor of miscanthus biomass yield, followed by LCC. Mid‐August to September measurements of these traits were the best predictors of biomass yield. Multiple regressions involving the canopy height and LCC further improved yield predictions. We conclude that while N enhances biomass yields of aging miscanthus, the optimum rate depends on the site, environmental conditions, and management history.
Nitrogen enhances the biomass yield of mature miscanthus, but optimum rates may vary depending on site‐specific factors, environmental conditions, and management history.
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