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Maintaining or even increasing crop yields while reducing nitrous oxide (N2O) emissions is necessary to reconcile food security and climate change, while the metric of yield‐scaled N2O emission (i.e., N2O emissions per unit of crop yield) is at present poorly understood. Here we conducted a global meta‐analysis with more than 6000 observations to explore the variation patterns and controlling factors of yield‐scaled N2O emissions for maize, wheat and rice and associated potential mitigation options. Our results showed that the average yield‐scaled N2O emissions across all available data followed the order wheat (322 g N Mg−1, with the 95% confidence interval [CI]: 301–346) > maize (211 g N Mg−1, CI: 198–225) > rice (153 g N Mg−1, CI: 144–163). Yield‐scaled N2O emissions for individual crops were generally higher in tropical or subtropical zones than in temperate zones, and also showed a trend towards lower intensities from low to high latitudes. This global variation was better explained by climatic and edaphic factors than by N fertilizer management, while their combined effect predicted more than 70% of the variance. Furthermore, our analysis showed a significant decrease in yield‐scaled N2O emissions with increasing N use efficiency or in N2O emissions for production systems with cereal yields >10 Mg ha−1 (maize), 6.6 Mg ha−1 (wheat) or 6.8 Mg ha−1 (rice), respectively. This highlights that N use efficiency indicators can be used as valuable proxies for reconciling trade‐offs between crop production and N2O mitigation. For all three major staple crops, reducing N fertilization by up to 30%, optimizing the timing and placement of fertilizer application or using enhanced‐efficiency N fertilizers significantly reduced yield‐scaled N2O emissions at similar or even higher cereal yields. Our data‐driven assessment provides some key guidance for developing effective and targeted mitigation and adaptation strategies for the sustainable intensification of cereal production. [ABSTRACT FROM AUTHOR]

Concerns about the effects of global warming on crop yields have been raised due to stagnating yield progress in recent years. However, an understanding of the effects of changes in temperature and rainfall throughout the crop cycle on historical yield progress is lacking in Europe (EU). In this study, positive wheat, barley, rice, and maize yield progress in the EU (1961–2019) was significant, with rates of 0.05, 0.04, 0.05, and 0.07 Tha−1year−1, for the four crops respectively. Much of this progress has been sustained by Eastern European countries (EE), which had the highest yield progress rates. On average, in the case of wheat and barley, a temperature increase of 1°C in the winter resulted in yields increasing by +0.33 Tha−1 in EE. This was potentially due to decreasing cold damage and improved photosynthesis and vegetative growth, supporting positive yield progress. Recent historical (2001–2019) rates of wheat, barley, rice, and maize yield progress were positive in all EU regions except Western Europe (WE), barley in Southern Europe (SE) and wheat in Northern Europe (NE). Stagnated wheat, barley and rice yields in WE were not explained by temperature or rainfall using direct correlations of observed data. However, May and July temperatures were associated with wheat yields in NE (−0.30 Tha−1°C−1), barley in SE (−0.14 Tha−1°C−1) and maize in WE and SE (−0.42 and −0.39 Tha−1°C−1). With increasing temperatures becoming less than optimal for photosynthesis, reducing grain filling duration and increasing drought episodes, crop yields have stagnated for wheat in NE and barley in SE. With consistent increases in temperature and water evaporative demand expected in the future, the interplay among genetic adaptation, increased crop cycle duration, drought tolerance, sowing dates, smart irrigation and sustainable practices may require thorough regional testing to maximise the yields of wheat, barley and maize in Europe. [ABSTRACT FROM AUTHOR]

Highlights • Ecological intensification management (EI) was compared with average farmer practice (FP). • We evaluated resource productivity and its components at the crop sequence level. • Water and radiation productivities were higher in EI than in FP. • Resource use efficiencies increased more than resource capture in EI as compared with FP. • The EI management reduced partial factor productivity of applied N but improved the partial N balance. Abstract The challenge to increase agricultural production with a minimum environmental impact requires to reach the maximum efficiency in the capture and use of resources such as photosynthetically active radiation (PAR), water, and nitrogen (N). Such requisites are encompassed in the ecological intensification (EI) concept. The aims of this work were to evaluate at a crop sequence level: i) crops yields, ii) water and radiation productivity and its components, i.e. resource capture and resource use efficiency, and iii) partial factor productivity of applied N (PFPN), partial nutrient balance for N (PNB), N uptake and N utilization efficiency of a two-year, three-crop sequence (wheat [ Triticum aestivum L.]/soybean [ Glycine max (L.) Merr.] double crop – maize [ Zea mays L.]) carried-out under EI principles in comparison with the same crop sequence under current farmer practices (FP) in two contrasting locations of the Argentinean Pampas, i.e. Paraná (-31°50′; -60°31′) at the northern Pampas and Balcarce (-37°45′, -58°18′) at the southern Pampas. Experiments were carried-out during four consecutive years, covering two complete cycles of the crop sequence. For the accumulated grain production of the crop sequence, EI management outyielded FP from 13 to 42%, depending on environmental conditions. Maize yield accounted for most of the variation (41–64%) of the accumulated grain yield of crop sequence, whether in EI as in FP. Average grain yield differences between EI and FP treatments were 274 g m−2 for maize, 69 g m−2 for wheat and -2 g m−2 for soybean. Water and radiation productivities of the sequence were higher in EI than in FP (26% for water and 17% for radiation; P < 0.0001), mainly because of increases in resource use efficiencies. EI reduced partial factor productivity of applied N, but improved partial nutrient balance for N as compared with FP. These reductions in partial factor productivity of applied N were less than proportional than the increases in N rate. Moreover, in spite of the higher N rate in EI respect to FP, N utilization efficiency (N ut E), i.e. grain per unit N uptake, was higher across all situations in EI. Our results showed that the challenge to obtain high grain yields by increasing N rate in a medium-input system could be achieved even with an increase in N ut E. Grain yields improvements, and increases in radiation and water productivity were reached by applying a set of agronomic practices that included improved genetics, crop and fertilizer N management englobed under EI concept. [ABSTRACT FROM AUTHOR]

Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two-thirds (63%-81%) of observed yield anomalies. Its out-of-sample performance (34%-55%) suggests a robust yield projection capacity when applied to unknown weather. Out-of-sample performance is lower when using remote sensing-derived yield data. The share of weather-driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%-84%). But the out-of-sample performance is lower (15%-42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within-season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high-quality yield monitoring and statistics as critical prerequisites to guide adaptation under climate change. [ABSTRACT FROM AUTHOR]

Inter-annual crop yield variation is driven in large parts by climate variability, wherein the climate components of temperature and precipitation often play the biggest role. Nonlinear effects of temperature on yield as well as interactions among the climate variables have to be considered. Links between climate and crop yield variability have been previously studied, both globally and at regional scales, but typically with additive models with no interactions, or when interactions were included, with implications not fully explained. In this study yearly country level yields of maize, rice, soybeans, and wheat of the top producing countries were combined with growing season temperature and SPEI (standardized precipitation evapotranspiration index) to determine interaction and intensification effects of climate variability on crop yield variability during 1961–2014. For maize, soybeans, and wheat, heat and dryness significantly reduced yields globally, while global effects for rice were not significant. But because of interactions, heat was more damaging in dry than in normal conditions for maize and wheat, and temperature effects were not significant in wet conditions for maize, soybeans, and wheat. Country yield responses to climate variability naturally differed between the top producing countries, but an accurate description of interaction effects at the country scale required sub-national data (shown only for the USA). Climate intensification, that is consecutive dry or warm years, reduced yields additionally in some cases, however, this might be linked to spillover effects of multiple growing seasons. Consequently, the effect of temperature on yields might be underestimated in dry conditions: While there were no significant global effects of temperature for maize and soybeans yields for average SPEI, the combined effects of high temperatures and drought significantly decreased yields of maize, soybeans, and wheat by 11.6, 12.4, and 9.2%, respectively. [ABSTRACT FROM AUTHOR]

Yield-scaled nitrous oxide (N 2 O) emission (YSNE) has been recognized as a means for developing appropriate nitrogen (N) management strategies to balance food security and mitigating N 2 O emissions. To better understand and use the concept of YSNE, it is essential to be assessed under various field conditions. The main objectives of this study were to assess the relationship between N inputs and YSNE with published results and identify response patterns of YSNE to N inputs. We assessed the relationship between N inputs and YSNE using published results encompassing 1800 observations (published from 1980 to 2020) from maize, rice, and wheat crops worldwide. Background yield-scaled N 2 O emission (BYSNE; a YSNE in the condition of zero N input) was significantly different by crop type. Rice (90.8 ± 12.9 g N 2 O−N Mg−1) had lower BYSNE compared to maize (174.2 ± 30.1 g N 2 O−N Mg−1) and wheat (325.4 ± 41.8 g N 2 O−N Mg−1). BYSNE was positively correlated with annual mean temperature in maize, rice, and wheat fields. BYSNE was negatively correlated with soil total nitrogen contents in rice fields. Over 60% data set showed a positive relationship between N inputs and YSNE in all three crops studied. A small proportion of the dataset had an optimum N rate that minimized YSNE. The results suggest that in general, lower N input rates result in lower YSNE in crop production. YSNE can be reduced in three ways: increasing yields (Type 1), reducing N 2 O emissions (Type 2), and both increasing yields and reducing N 2 O emissions (Type 3). To identify appropriate measures, we suggest a N 2 O emission-yield curve combining responses of yields and N 2 O emissions to N inputs. In type 1, 2, and 3 measures, an N 2 O emission-yield curve is shifted to the right, down, and both right and down, respectively. Through identifying direction and magnitude of the shifting, the effects of applied measures on yields and N 2 O emission in N input levels can be easily compared and recognized. This study provided insights into the nature of YSNE and how YSNE responds to N inputs. It also suggested an N 2 O emission-yield curve, which can be useful to identify how certain measures affect both N 2 O emissions and crop yields. The information can be useful for scientific community and policymakers developing appropriate N management strategies to balance food security and the mitigation of N 2 O emissions. [Display omitted] • Background yield-scaled N 2 O emission (BYSNE) varied by crop type. • BYSNE was positively correlated with annual mean temperature. • Over 60% data sets showed consistently lower yield-scaled N 2 O emission as N input decreased. • N 2 O emission yield curve showed the effects of mitigation measures on both yields and N 2 O emission. [ABSTRACT FROM AUTHOR]

Abstract: Phosphate-solubilizing bacteria (PSBs) Pantoea cypripedii (PSB-3) and Pseudomonas plecoglossicida (PSB-5) isolated from organic field were studied for improvement of maize and wheat crop at multilocational sites with and without rock phosphate (RP) fertilization during two year of field study under different agroclimatic regions. Application of both the bacterial strains as bio-inoculants showed significant effect on maize and wheat grain yield and on soil fertility at all different agroclimatic regions. Grain yield, phosphorous (P) uptake, soil organic carbon, available P, enzyme activities and P-solubilizing bacterial population in all the experimental crop fields at different sites significantly increased due to inoculation. Improvement in crop yield and soil fertility at three different sites was more pronounced and significant when RP was supplemented along with seed inoculation compared to uninoculated control treatment. Present study results suggest that P. cypripedii (PSB-3) and P. plecoglossicida (PSB-5) along with RP fertilization play an important role in plant growth promotion and improvement of soil fertility in different agroclimatic regions. [Copyright &y& Elsevier]

Abstract: Efficiency of fertilizer N is becoming increasingly important in modern agricultural production owing to increasing food requirement and growing concern about environments. However, there is almost no study regarding its long-term efficiency in wheat and maize cropping systems. Long-term (15 years) experiments involving wheat (Triticum aestivum L.) and maize (Zea mays L.) rotations at five field sites with various soil and climate characteristics in China were used to determine the nitrogen (N) efficiency, including the physiological efficiency, recovery efficiency and N mass balance of soil–plant systems in response to different fertilization treatments. The present study consisted of nine treatments: unfertilized, N, phosphorus, potassium, straw and manure or their combinations. The contribution of N fertilizers to wheat yield was higher than to maize and suggested that wheat could be given priority over maize when determining N application rates. Uptake of 1kg N produced 35.6kg of wheat grain and 39.5kg of maize grain. The deficit of N in soils without applied N ranged from 40 to 103kgNha−1 year−1, while N surpluses in soils with applied N fertilizers ranged from 35 to 350kgNha−1 year−1. The apparent accumulated N recovery efficiency (NREac) varied widely from 4% to 90%: unbalanced fertilization and other soil limiting factors (such as aluminium toxicity) were associated with low NREac. In the treatments of combination of N, phosphorus and potassium with normal application rates, the average of NREac in four out of five sites reached 80%, which suggested that best management of N fertilizers could recover most of N fertilizers applied to soils. The results will be helpful to understand the long-term fate of N fertilizers and to optimize the N fertilization for agricultural practices and environment protection. [Copyright &y& Elsevier]

The North China Plain (NCP) is the most important agricultural production area in China. Crop production in the NCP is sensitive to changes in both climate and management practices. While previous studies showed a negative impact of climatic change on crop yield since 1980s, the confounding effects of climatic and agronomic factors have not been separately investigated. This paper used 25 years of crop data from three locations (Nanyang, Zhengzhou and Luancheng) across the NCP, together with daily weather data and crop modeling, to analyse the contribution of changes in climatic and agronomic factors to changes in grain yields of wheat and maize. The results showed that the changes in climate were not uniform across the NCP and during different crop growth stages. Warming mainly occurred during the vegetative (preflowering) growth stage of wheat and maize, while there was a cooling trend or no significant change in temperatures during the postflowering stage of wheat (spring) or maize (autumn). If varietal effects were excluded, warming during vegetative stages would lead to a reduction in the length of the growing period for both crops, generally leading to a negative impact on crop production. However, autonomous adoption of new crop varieties in the NCP was able to compensate the negative impact of climatic change. For both wheat and maize, the varietal changes helped stabilize the length of preflowering period against the shortening effect of warming and, together with the slightly reduced temperature in the postflowering period, extend the length of the grain-filling period. The combined effect led to increased wheat yield at Zhengzhou and Luancheng; increased maize yield at Nanyang and Luancheng; stabilized wheat yield at Nanyang, and a slight reduction in maize yield at Zhengzhou, compared with the yield change caused entirely by climatic change. [ABSTRACT FROM AUTHOR]

The effect of elevated carbon dioxide (CO2) on crop yields is one of the most uncertain and influential parameters in models used to assess climate change impacts and adaptations. A primary reason for this uncertainty is the limited availability of experimental data on CO2 responses for crops grown under typical field conditions. However, because of historical variations in CO2, each year farmers throughout the world perform uncontrolled yield ‘experiments’ under different levels of CO2. In this study, measurements of atmospheric CO2 growth rates and crop yields for individual countries since 1961 were compared with empirically determine the average effect of a 1 ppm increase of CO2 on yields of rice, wheat, and maize. Because the gradual increase in CO2 is highly correlated with major changes in technology, management, and other yield controlling factors, we focused on first differences of CO2 and yield time series. Estimates of CO2 responses obtained from this approach were highly uncertain, reflecting the relatively small importance of year-to-year CO2 changes for yield variability. Combining estimates from the top 20 countries for each crop resulted in estimates with substantially less uncertainty than from any individual country. The results indicate that while current datasets cannot reliably constrain estimates beyond previous experimental studies, an empirical approach supported by large amounts of data may provide a potentially valuable and independent assessment of this critical model parameter. For example, analysis of reliable yield records from hundreds of individual, independent locations (as opposed to national scale yield records with poorly defined errors) may result in empirical estimates with useful levels of uncertainty to complement estimates from experimental studies. [ABSTRACT FROM AUTHOR]

The expected increase in population and the pressure posed by climate change on agricultural production require the assessment of future yield levels and the evaluation of the most suitable management options to minimize climate risk and promote sustainable agricultural production. Crop simulation models are widely applied tools to predict crop development and production under different management practices and environmental conditions. The aim of this study was to parameterize CSM-CERES-Wheat and CSM-CERES-Maize models, implemented in the Decision Support System for Agrotechnology Transfer (DSSAT) software, to predict phenology and grain yield of durum wheat, common wheat, and maize in different Italian environments. A 10-year (2001–2010) dataset was used to optimize the genetic parameters for selected varieties of each species and to evaluate the models considering several statistical indexes. The generalized likelihood uncertainty estimation method, and trial and error approach were used to optimize the cultivar-specific parameters of these models. Results show good model performances in reproducing crop phenology and yield for the analyzed crops, especially with the parameters optimized with the trial and error procedure. Highly significant (p ≤ 0.001) correlations between observed and simulated data were found for both anthesis and yield in model calibration and evaluation (p ≤ 0.01 for grain yield of maize in model evaluation). Root mean square error (RMSE) values range from six to nine days for anthesis and from 1.1 to 1.7 t ha−1 for crop yield and index of agreement (d-index) from 0.96 to 0.98 for anthesis and from 0.8 to 0.87 for crop yield. The set of genetic parameters obtained for durum wheat, common wheat, and maize may be applied in further analyses at field, regional, and national scales to guide operational (farmers), strategic, and tactical (policy makers) decisions. [ABSTRACT FROM AUTHOR]