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Two experiments were conducted to test the hypothesis that there are no differences in composition, apparent total tract digestibility (ATTD) of gross energy (GE), or standardized ileal digestibility (SID) of amino acids (AA) in wheat middlings sourced from flour mills in Europe or in the U.S. For both experiments, ten sources of wheat middlings were used. Five sources were procured from Europe and the other five sources were procured from the U.S. The ten sources of wheat middlings varied in starch from 79 to 286 g/kg (as-fed) and total dietary fiber varied from 324 to 508 g/kg. In experiment 1, 88 castrated male pigs (27.2 ± 2.5 kg) were individually housed in metabolism crates and allotted to eleven diets with eight replicate pigs per diet. A corn-soybean meal diet and ten diets containing corn, soybean meal, and each source of wheat middlings as the only energy sources were formulated. Feces and urine were collected using the marker-to-marker approach with 5-day adaptation and 4-day collection periods. The ATTD of GE and the concentration of digestible energy (DE) in wheat middlings from one of the European sources were less (P < 0.05) than in the other sources. Likewise, wheat middlings from Europe had reduced concentrations of DE and metabolizable energy (12.10 and 11.42 MJ/kg, dry matter basis) compared with wheat middlings from the U.S (12.69 and 12.32 MJ/kg, dry matter basis). In experiment 2, eleven pigs (52.8 ± 3.6 kg) with a T-cannula in the distal ileum were allotted to an 11 × 8 Youden square design with eleven diets and eight periods resulting in eight replicates per diet. A nitrogen-free diet and ten diets containing each source of wheat middlings as the only AA-containing ingredient were formulated. Results indicated that the SID of most AA in wheat middlings from two of the European sources was less (P < 0.05) than in the other sources. As a consequence, the average SID of AA for wheat middling from Europe was less than the SID of AA in wheat middlings from the U.S. In conclusion, energy concentrations and AA digestibility values for wheat middling from Europe were less than in wheat middlings from the U.S., which is likely due to increased concentration of dietary fiber in wheat middlings from Europe. Greater variability in energy and AA digestibility values was also observed in the five sources of wheat middlings from Europe compared with wheat middlings from the U.S., which is possibly a result of differences among European flour mills in the production process. • Wheat middlings from Europe contain more fiber than U.S. wheat middlings. • Wheat middlings from Europe contain less energy than wheat middlings from the U.S. • Amino acid digestibility is greater in U.S. than in European wheat middlings. [ABSTRACT FROM AUTHOR]

Nitrogen fertilization is one of the major issues of crop productions in west-Europe. Every year, large quantities of synthetic nitrogen are used to fertilize crops, such as winter wheat (Triticum aestivum), and ensure them high yielding conditions. In return, substantial amount of nitrogen ends up in the environment where it generates pollutions. The combination of strategic and tactical approaches has been suggested to improve the accuracy of nitrogen fertilization decisions and their implementation. Combining strategic and tactical approaches requires a detailed understanding of the dynamic of nitrogen use by the plant to both anticipate and adapt fertilization practices. Inspired by the concept of yield component phenotypic plasticity, this study aimed to analyze the influence of nitrogen fertilization dynamics on yield elaboration and infer strategic decision rules dedicated to wheat yield optimization in a Belgian context. The analysis, implemented from ten-year experiment, was conducted in two different steps. (1) We characterized the effect of nitrogen fertilization on yield and yield components when the crop was submitted to different agro-pedo-climatic contexts, (2) we analyzed the specific influence of nitrogen fertilization dynamic on yield elaboration, normalizing the variables of the experiment to exclude genetic and environmental influences. The study revealed that highest nitrogen fertilization did not automatically lead to the highest yields. High nitrogen fertilization contributed to increase the negative trade-offs between yield components, which limited the efficiency of nitrogen supplies. Conversely, a balanced dynamic of nitrogen supplies was essential to reach high yields while supplying effective amount of nitrogen. From this Belgian dataset, optimal nitrogen fertilization strategies supposed early nitrogen supplies split in two applications to support the initiation phases of grains per m² and another nitrogen supply at flag leaf stage to maintain components of grain per m² while still allowing grain filling. This fertilization structures, adapted to different pedoclimatic contexts would support strategic approach in crop nitrogen nutrition. • The effect of N on yield components plasticity was analyzed in a ten-year experiment. • Environmental influences were excluded by the normalization of experiment variables. • Highest yields did not always result from highest nitrogen fertilization. • Balanced nitrogen fertilization ensures high yields and rational nitrogen supply. • Decision rules were infered from the analysis to support N fertilization strategical approach. [ABSTRACT FROM AUTHOR]

Stakeholders, policy makers, government planners and agricultural market participants in Central Eastern Europe require accurate and timely information about wheat and maize yield and production. The study site, the lowlands (altitude below 200 m) of the Tisza river catchment is by far the most important wheat and corn producing region in the Carpathian basin, and even in Central Eastern Europe. The conventional sampling of on-field data and data processing for crop forecasting requires significant amounts of time before official reports can be released. Several studies have shown that wheat and maize yield can be effectively forecast using satellite remote sensing. In this study, a freely available MODIS NDVI satellite data based wheat and maize yield forecasting methodology was developed and evaluated for estimating yield losses effected by drought. Wheat and maize yield was derived by regressing reported yield values against time series of 15 different peak-season MODIS-derived NDVI. The lowest RMSE values at the river basin level for both wheat and maize yield forecast versus reported yield were found when using at least six or more years of training data. Wheat forecast for the 2000 to 2015 growing seasons were within 0.819% and 19.08% of final reported yield values. Maize forecast at county level for the 2000 to 2015 growing seasons were within 0.299% and 17.14% of final reported yield values. The Nash–Sutcliffe efficiency index (E 1 ) is positive with E 1  = 0.322 in the case of wheat forecast, and with E 1  = 0.401 in the case of maize forecast, which means the developed and evaluated forecasting method performs acceptable forecast efficiency. Nevertheless the occurrence of extreme drought or extreme precipitation can alter the forecasting efficiency resulting over or underestimation. Overall statement, which based on MODIS NDVI, possible yield losses can easily be forecasted 6–8 weeks before harvesting and applying simple threshold levels, yield losses can be mapped simply. [ABSTRACT FROM AUTHOR]

Intercropping is a cropping practice with the potential to increase the sustainability of the agricultural systems. Field pea has been largely studied in intercrop with wheat and barley in Northern and Central Europe whereas much less research has been carried out in semiarid environments of Southern Europe. A two-year field experiment was conducted in Southern Italy with the aim to assess yields and yield components and N use of field pea and four different cereals – wheat, barley, oat and triticale – grown in additive and replacement intercrop. The cereal was the dominant partner in intercrop, strongly outcompeting pea. Cereal height and biomass yield and intercrop density affected yield component parameters of pea causing a severe reduction of number of pods per plant and death of pea plants. Pea yields were generally lower in intercrop than in sole crop. Consequently, nitrogen accumulation in intercrop and Land Equivalent Ratio (LER) N yields-based values resulted negatively affected. LER values were highest in barley-pea intercrops for both grain and straw nitrogen yields. Cereal grain and straw N content increased in intercrop compared to the sole crop while pea grain N content was reduced. The results of this study indicate that cereal-pea intercropping can be a way of improving the grain and straw quality of the intercropped cereal and reducing N inputs into agricultural systems compared with the sole cropping. The choice of the companion cereal and the intercrop density should, however, be carefully evaluated in drought-prone environments like those of Southern Europe. [ABSTRACT FROM AUTHOR]

[Display omitted] • Predict the presence of one or more mycotoxins in wheat on a regional basis in Europe using machine learning (random forest). • Mycotoxin monitoring data, crop phenological data, weather data, and satellite images were linked, based on year and grid, and used as model input. • Results showed high prediction performance of the model: internal and external validation resulted in 0.90–0.99 prediction accuracy. • Satellite images showed to improve the overall model performance. Wheat is susceptible to fungal infection and mycotoxin contamination during its cultivation period, under opportune environmental conditions. The presence of mycotoxins, such as deoxynivalenol and zearalenone, in wheat destined for feed and food can affect animal and human health. This study aimed to develop a machine learning algorithm to predict the risk levels of one or more mycotoxins in wheat on a regional basis in Europe using crop phenological data, weather data, and satellite images as input. A dataset was obtained with 11 years of mycotoxin monitoring data (2010–2020), including historical records of the concentration of deoxynivalenol, zearalenone, T-2 toxin and HT-2 toxin, fumonisins, aflatoxins, and/or ochratoxin A in wheat in Europe. This dataset was linked, based on year and grid (25 × 25 km), to wheat phenology data, weather data, and satellite image data. The complete dataset for the years 2010–2018 was split into a model training (80%) and an internal model validation set (20%). Data for the years 2019 and 2020 were used for external validation. The random forest (RF) algorithm was applied to train the model using the model training data. The model predicts the probability (low, medium, high) of wheat grown in a certain grid in Europe to be contaminated with at least one of the six mycotoxins under study. Results showed high prediction performance of the model: internal and external validation resulted in 0.90–0.99 prediction accuracy. Based on the data for the Netherlands (case study), satellite images showed to improve the overall model performance. The current model with its mycotoxin predictions can be used by stakeholders to increase logistics in the wheat supply chain and for risk-based monitoring, in this way contributing to improving the safety of wheat derived products, and improving food security. For future development and improvement of prediction models, more mycotoxin data with detailed locations of the cultivated crop are needed. [ABSTRACT FROM AUTHOR]

Numerous Life Cycle Analysis of bread pointed out that wheat production and transportation have important impacts on the environment. But wheat is grown all around the world and it is not always consumed where it is produced. In this paper an analysis of the wheat movements around Europe is done, taking special attention on the Spanish situation. An optimization of wheat exchanges is done eliminating the import–export overlapping. This optimization entails a reduction of the number of trips by 34% and the CO 2 emissions reduction due to transportation is calculated to be 121.175 tones. Consequently less trips, fewer trucks, less traffic and lower emissions that brings economic, social and environmental benefits. [ABSTRACT FROM AUTHOR]

• Empirical models of winter survival of winter wheat and triticale were developed. • Different weather variables affected the winter survival of both species. • Wheat was more susceptible than triticale to severe winter weather. • In a warmer climate, deacclimation from warm spells can reduce winter survival. Winter hardiness depends on the ability of plants to tolerate a wide spectrum of environmental stresses, which can be affected by climate change in complex ways. Here, empirical Partial Least Squares Regression (PLSS) models of winter survival (WS) of winter wheat (Triticum aestivum L.) and triticale (Triticosecale x Wittmack) were created using data from six years of field experiments at multiple locations throughout Poland. These included 553 winter wheat and 155 triticale accessions. Our aims were to: 1) predict WS on the basis of meteorological data; 2) identify the most critical weather events affecting WS of winter wheat and triticale under Polish conditions; and 3) predict WS for the simulated winters of 2040, 2060 and 2080 under climate change scenarios RCP2.6, RCP4.5, RCP6.0 and RCP8.5 for the experimental site with the lowest mean WS rate during the field experiments. The empirical models showed a high R2 for winter wheat (0.751), and a low R2 for winter triticale (0.160), because of the low winter damage to triticale observed during the experiments. The key climate factors affecting WS varied between species. Winter wheat was affected by winter severity, the number of freezing-thawing cycles, the thermal vegetation index and the freezing index in various winter months. Triticale was affected by late winter ice encasement and high numbers of freeze-thaw events. The predictions indicated that the WS of both winter wheat and triticale may decrease in the future, especially when more extreme climate change scenarios were considered. The main issue will be cold deacclimation connected with climate warming which will be more important for WS than the general increase in minimum winter temperatures. This finding indicates that deacclimation tolerance should be included in wheat and triticale breeding programs as a trait crucial for WS under future winters, at least in Central Europe. [ABSTRACT FROM AUTHOR]

Einkorn (Triticum monocum L.) is an old variety of wheat and is considered an ancient grain. Currently, limited amounts of einkorn are produced within a few regions of Europe and the US, and therefore it is sold at higher prices than common wheat. Either for unfair economic gain (adulteration) or to compensate its weaker gluten structure, einkorn flour tends to be adulterated with bread wheat flour, which is frequently encountered in commercial einkorn flour or einkorn baked products. In this study, einkorn and bread wheat flours were initially analyzed for their common quality properties following the traditional analytical methods. Then, two rapid methods, Computer-Based Image (CBI) Analysis and Near-Infrared Spectroscopy (NIRS), were evaluated to rapidly estimate the % level of bread wheat flour in both einkorn-wheat flour mixtures and the bread made of those mixtures. For this purpose, binary mixtures of einkorn flour and the adulterating bread wheat flour were prepared for calibration (46 samples) and external validation (18 samples) sets, with wheat flour content in the mixtures ranging between 5 and 95% (w/w). Then, for each binary mixture, a loaf of conventional bread was produced. Flour mixtures and loaves of bread samples produced were analyzed by both CBI and NIRS. Our results suggested that CBI could only yield high correlation levels between the wheat flour content and some color properties in bread samples (>0.96), while no sufficient correlations were observed in flour mixtures. Regarding the NIRS, highly accurate models were developed for both flour mixtures (correlation coefficients > 0.99, standard errors < 1.39% and RPD level of 19.3) and bread samples (correlation coefficients > 0.94, standard errors < 2.64% and RPD level of 10.1). Our results indicate that both NIRS and CBI may be implemented in the rapid and easy screening of wheat flour adulteration in einkorn bread, while only NIRS is suggested to be used for the same purpose in flour mixtures. • Pure einkorn and bread wheat flour samples were characterized in this study. • Binary mixtures of einkorn-bread wheat flour and bread samples were prepared. • Fourth-six calibration and eighteen validation samples were included. • CBI was successful in the screening of wheat flour content in the flour mixtures. • NIRS can detect flour adulteration in flour mixtures and bread samples. [ABSTRACT FROM AUTHOR]

• APSIM was calibrated and validated for pure cultures of wheat and faba bean. • APSIM was evaluated for wheat-faba bean pure cultures and intercrops in Europe. • APSIM reproduced pure culture aboveground dry matters and, for wheat, yields. • APSIM overestimates faba bean performance relative to wheat in intercrops. • APSIM must incorporate an alternative approach to simulate height growth. Cereal-legume intercropping can increase yields, reduce fertilizer input and improve soil quality compared with pure culture. Designing intercropping systems requires the integration of plant species trait selection with choice of crop configuration and management. Crop growth models can facilitate the understanding and prediction of the interactions between plant traits, crop configuration and management. However, currently no existing crop growth model has been calibrated and tested for cereal-legume intercrops throughout Europea. We calibrated the Agricultural Production Systems sIMulator (APSIM) for pure cultures of wheat and faba bean using data from Dutch field trials, and determined the phenological parameters to simulate pure cultures and intercrops from seven field experiments across Europe. APSIM successfully reproduced aboveground dry matters and, for wheat only, grain yields in pure cultures. In intercrops, APSIM systematically overestimated the aboveground dry matter and grain yield of faba bean and underestimated those of wheat. APSIM was reasonably capable of simulating plant heights in pure cultures, but respectively overestimated and underestimated the height of faba bean and wheat in intercrops. In order to simulate wheat-faba bean intercrops better, APSIM should be improved regarding the calculation of biomass partitioning to grains in faba bean and of height growth in both species. [ABSTRACT FROM AUTHOR]

• A lightweight concrete based on lime binder and wheat husk aggregate was designed. • Comparison was made with lime hemp concrete manufactured by the same route. • Comparable insulation properties and strength were found. • Wheat husk can be valorised without energy-consuming pre-treatment. • Lightweight concrete is a technically viable recycling solution for wheat husk. The huge annual production of wheat husk in Europe (10 million tons) creates management problems. Valorization options are thus sought. Here, insulting lime concrete was designed using native wheat husk as lightweight aggregate. Physical-chemical and technological properties of both particles and concretes were determined. Comparisons with hemp concrete manufactured with the same process were made. Similar thermal conductivities for the two types of concretes were obtained (ca. 0.09 W/(m·K)), whereas slightly lower compressive strength was found for wheat husk concrete due to weaker particle-binder interface. Nevertheless, results highlight the high potential of raw wheat husk for development of bio-based materials with interesting performances. [ABSTRACT FROM AUTHOR]

• Benchmarks of wheat N utilisation efficiency (NUtE) in Mediterranean conditions are needed. • We compiled a large set of data from Mediterranean and non-Mediterranean environments of Europe. • Mediterranean growing conditions narrowed N uptake contributing to lower final yields than in N Europe. • But they also reduced consistently NUtE (considering both average and maximum yields at each level of N uptake). • These effects on NUtE produced a trade-off with grain N concentration. Water and temperature stress during critical periods of grain yield formation are distinctive of wheat crops in Mediterranean environments. However, nitrogen (N) availability may also constrain grain yields in these environments. Benchmarks of yield response to N uptake in Mediterranean conditions are lacking, and extrapolation from non-Mediterranean environments is not warranted. We hypothesised that under Mediterranean environments (1) maximum N uptake would be lower, thus the range of N uptake would be narrower, and (2) N utilisation efficiency (NUtE, yield per unit N uptake) would be reduced along the whole range of N uptake than under non-Mediterranean conditions. To test these hypotheses, we compiled published data of yield and N uptake from Mediterranean (n = 340) and non-Mediterranean environments (n = 563) of Europe. Wheat in Mediterranean environments had lower average grain yield (4.1 vs 7.1 Mg ha−1), lower average N uptake (131 vs 166 kg N ha−1), lower average NUtE (33 vs 47 kg grain kg N−1), and higher average grain N concentration (2.4 vs 1.8%) than crops in non-Mediterranean environments. Boundary functions relating yield and nitrogen uptake captured the lower yield of wheat along the whole range of N uptake as hypothesised; these functions could be used for benchmarking wheat crops in Mediterranean regions of Europe, and possibly other Mediterranean environments. [ABSTRACT FROM AUTHOR]

• Farm level data were used to compare yields of cereals and break crops with wheat. • Wheat was the highest yielding and least variable crop. • All break -crops were more sensitive to low yielding environments than wheat. • Canola was the most consistent broadleaf break crop. • In order to increase species diversity yields need to be improved relative to wheat. Typically dryland rain fed cropping systems in much of the world (Australia, North America, Europe and the Middle East) are dominated by cereals, such as wheat, even though the rotational benefits of other crops are well documented. Presumably farmers see an advantage to wheat and this paper tested the hypothesis that on-farm break-crop yields are lower compared to wheat, and more variable. Farm level yields for wheat, barley, hay, oats, triticale, canola, lupin, chickpea, and field pea were taken from a survey of Western Australian grain farms (180–302 farms per year). In general, the yield of broad leaf crops was less than cereals and more variable. Additional data were sourced from published experiments and then yields were compared with wheat using linear regression with wheat as the x-axis and break crop as the y-axis. All break -crops were more sensitive to low yielding environments than wheat, as indicated by a positive intercept with the x-axis. Barley and wheat yields were closely related (R2 = 0.63), but in environments where yield was less than 1.25 t/ha wheat tended to yield more, while barley out yielded wheat when yields were greater than 1.25 t/ha. There was a poor relationship between either oat grain (R2 = 0.26) or hay (R2 = 0.10) yields and wheat indicating that these maybe potential income diversification options. Canola was the least variable (R2 = 0.54) broadleaf crop compared to wheat, with an intercept of 0.15 t/ha and for every 1 t/ha increase in wheat yield, canola yield increased by 0.56 t/ha. If increased diversity of crop species on-farm is the objective, then varieties and management packages that increase the yield and reliability of broadleaf crops relative to wheat will need to be developed. [ABSTRACT FROM AUTHOR]