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1

Asthir, Bavita, Shashi Bala, and Navtej Singh Bains. "Effect of Terminal Heat Stress on Yield and Yield Attributes of Wheat." Indian Journal of Applied Research 4, no. 6 (October 1, 2011): 1–2. http://dx.doi.org/10.15373/2249555x/june2014/1.

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2

Altay, F., and N. Bolat. "Effect of soilborne wheat mosaic virus on winter wheat yield and yield components." Acta Agronomica Hungarica 52, no. 3 (November 1, 2004): 309–17. http://dx.doi.org/10.1556/aagr.52.2004.3.12.

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Soil-borne wheat mosaic virus (SBWMV) is an important disease of wheat production areas throughout the world, causing a great reduction in wheat and barley yields. The most effective way of controlling the disease is the use of resistant varieties in infested areas. In this study, the effects of SBWMV on yields and some yield components of eight susceptible, one moderately susceptible/resistant and nine resistant varieties were evaluated using data from 9 virus-infested and 6 non-infested sites in Eskisehir, Turkey over 6 years. The susceptible varieties yielded 5.35% more than resistant varieties in non-infested sites, while they gave 28.98% lower yield in infested sites. Significant yield loss differences were observed between the varieties in infested sites. Decreases were also observed in yield components at various levels. This study showed that SBWMV is an important disease, which survives in soil for long periods and causes significant yield decreases in wheat. Recently developed varieties have good resistance to the disease and are recommended to farmers in infested areas. Abbreviations: SBWMV, soil-borne wheat mosaic virus
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3

Jan, Křen, Houšť Martin, Tvarůžek Ludvík, and Jergl Zdeněk. "Are intensification and winter wheat yield increase efficient?" Plant, Soil and Environment 63, No. 9 (September 26, 2017): 428–34. http://dx.doi.org/10.17221/482/2017-pse.

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The results of small-plot field trials of international comparisons of a series of crop management practices for winter wheat grown during 2014–2016 on fertile soils of Central Moravia were assessed. The objective of the experiments was to obtain the highest gross margin (GM), which is the difference between revenues and direct costs. The analyses showed that an optimal level of inputs and costs for obtaining the highest GM could exist. In the assessed series of crop management practices, the optimum input costs corresponded to 11 000–12 000 CZK/ha and 6–9 input measures. At high levels of grains (above 10 t/ha), higher values of GM were obtained by increased efficiency of inputs, but not by increasing their amount to maximize the yields. This indicates the multifunctional and synergic effects of production factors, which can be used at the so-called ecological intensification. Optimizations of inputs can be obtained rather by crop protection than by crop nutrition, which means rather in protection of high yields than in their maximization. Under field conditions, soil and plant processes affected by weather cannot be controlled. Therefore, optimisation of production factors is based both on scientific findings and practical agronomic experience. That is why a universal crop management practice with increased economic and ecological effects cannot be practically proposed.
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4

Lin, M., and P. Huybers. "Reckoning wheat yield trends." Environmental Research Letters 7, no. 2 (May 16, 2012): 024016. http://dx.doi.org/10.1088/1748-9326/7/2/024016.

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5

Bahrani, M. J., M. Kheradnam, Y. Emam, H. Ghadiri, and M. T. Assad. "EFFECTS OF TILLAGE METHODS ON WHEAT YIELD AND YIELD COMPONENTS IN CONTINUOUS WHEAT CROPPING." Experimental Agriculture 38, no. 4 (August 20, 2002): 389–95. http://dx.doi.org/10.1017/s001447970200042x.

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A three-year field experiment was undertaken to evaluate the effects of tillage methods on grain yield and yield components of wheat (Triticum aestivum) in continuous cropping. The experiment was conducted on a Ramjerd, fine, mixed, mesic, typic Calcixerepts soil. Wheat was sown: (1) after burning residues followed by conventional tillage, (2) after complete residue removal followed by conventional tillage, (3) after soil incorporation of residues followed by conventional tillage, (4) into untilled residues, (5) using chisel seeder after field irrigation, (6) using chisel seeder plus herbicide application, and (7) after disking. Residue burning and removal increased spikes per square metre, grain per spike, 1000-grain weight, grain yield and harvest index compared with other treatments. This was due primarily to weed interference and lack of uniform crop establishment in the presence of residues. Reduced tillage methods retained more residues on the soil surface, which provided unsuitable conditions for crop emergence and growth. The incorporation of residues led to a build up of carbon in the soil, with lower grain yields compared with residue burning and removal, but these yields were higher than those of chisel-seeded plots.
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6

Sweeney, G., RS Jessop, and H. Harris. "Yield and yield structure of triticales compared with wheat in northern New South Wales." Australian Journal of Experimental Agriculture 32, no. 4 (1992): 447. http://dx.doi.org/10.1071/ea9920447.

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The yields and yield structure of cultivars of triticales and bread wheats (with a range of phasic development patterns in both species) were compared in 2 field experiments at Narrabri in northern New South Wales. The experiments were performed on a grey cracking clay soil with irrigation to prevent severe moisture stress. Triticales, both early and midseason types, appeared to have reached yield parity with well-adapted wheat varieties. Meaned over the 2 experiments and all sowings, the triticales yields were 19% greater than the bread wheats. Triticales were generally superior to wheat in all components of yield of the spike (1000-grain weight, grain number/spikelet and spikelet number/spike), whilst the wheats produced more spikes per unit area. The triticales also had higher harvest indices than the wheats. The results are discussed in relation to the overall adaptability of triticale for Australian conditions.
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7

Budzyński, W. S., K. Bepirszcz, K. J. Jankowski, B. Dubis, A. Hłasko-Nasalska, M. M. Sokólski, J. Olszewski, and D. Załuski. "The responses of winter cultivars of common wheat, durum wheat and spelt to agronomic factors." Journal of Agricultural Science 156, no. 10 (December 2018): 1163–74. http://dx.doi.org/10.1017/s0021859619000054.

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AbstractA field experiment with the 35–1 fractional factorial design and five factors (k = 5) at three levels (s = 3) was performed in 2007–2010 at the Agricultural Experiment Station in Bałcyny, north-eastern (NE) Poland. The results of the experiment carried out under the agro-ecological conditions of NE Poland confirmed the high yield potential of common wheat and satisfactory yield potential of spelt and durum wheat. On average, durum wheat and spelt yields were 2.14 and 2.55 t/ha lower, respectively, than common wheat yields. Sowing date was not correlated with the yields of analysed Triticum species. Seed rate (350, 450 and 550 seeds/m2) had no significant influence on the grain yield of winter cultivars of common wheat, durum wheat and spelt. Common wheat cv. Oliwin and durum wheat cv. Komnata were characterized by the highest yields in response to nitrogen (N) fertilizer rates calculated based on the Nmin content of soil. An increase in the spring fertilizer rate by 40 kg N/ha in excess of the balanced N rate was not justified because it did not induce a further increase in the grain yield of common wheat and durum wheat. The grain yield of spelt cv. Schwabenkorn continued to increase in response to the highest rate of N fertilizer in spring (40 kg N/ha higher than the optimal rate). Intensified fungicide treatments improved grain yield in all Triticum species.
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8

Hnilička, F., J. Petr, H. Hniličková, and J. Martinková. "The yield formation in the alternative varieties of wheat." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 295–301. http://dx.doi.org/10.17221/6197-cjgpb.

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9

Waines, J. G., and B. Ehdaie. "Breeding for root characters and grain yield in wheat." Czech Journal of Genetics and Plant Breeding 41, Special Issue (July 31, 2012): 326–30. http://dx.doi.org/10.17221/6212-cjgpb.

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10

Akcura, M., Y. Kaya, S. Taner, and R. Ayranci. "Parametric stability analyses for grain yield of durum wheat." Plant, Soil and Environment 52, No. 6 (November 17, 2011): 254–61. http://dx.doi.org/10.17221/3438-pse.

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Grain yield of 15 durum wheat (Triticum durum Desf.) genotypes consisting of 13 cultivars and 2 advanced lines, tested in a randomized complete block design with four replications across 8 environments of Central Anatolian Region of Turkey was analyzed using nine parametric stability measures. The objectives were to assess genotype-environment interactions (GEI), determine stable genotypes, and compare mean grain yield with the parametric stability parameters. To quantify yield stability, nine stability statistics were calculated (b<sub>i</sub>, S<sup>2</sup><sub>di</sub>, R<sub>i</sub><sup>2</sup>, W&thinsp;<sub>i</sub><sup>2</sup>, &sigma;<sub>i</sub><sup>2</sup>, S<sup>2</sup><sub>i</sub>, &alpha;<sub>i</sub> and&nbsp;&lambda;<sub>i</sub>). Yilmaz-98, Cakmak-79, Kiziltan-91, Selcuklu-97 and C-1252 were more stable cultivars, which had 9, 8, 6, 6, 6 out of all 9 stability statistics used, respectively. Especially, among these cultivars, Yilmaz-98 and Cakmak-79 were the most stable cultivars. Furthermore, three-dimensional plots of mean response versus each stability statistic were shown to visually evaluate the yield potential and stability estimates of the genotypes. Genotype mean yield (&ndash;x) was significantly positively correlated to the regression coefficient (b<sub>i</sub>), environmental variance and genotype to the environmental effects (&alpha;<sub>i</sub>), indicating that high grain yielding genotypes had larger values b<sub>i</sub>, S<sup>2</sup><sub>i</sub>, and &alpha;<sub>i</sub>, S<sup>2</sup><sub>i</sub>, W&thinsp;<sub>i</sub><sup>2</sup>, CV<sub>i</sub>,&nbsp;&alpha;<sub>i</sub> and b<sub>i</sub>, were significantly correlated, indicating that they measured similar aspects of stability
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11

Roloff, G., R. de Jong, R. P. Zentner, C. A. Campbell, and V. W. Benson. "Estimating spring wheat yield variability with EPIC." Canadian Journal of Soil Science 78, no. 3 (August 1, 1998): 541–49. http://dx.doi.org/10.4141/s97-063.

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The Environmental Policy Integrated Climate (EPIC) model has been used on the semiarid temperate Canadian Prairies to estimate crop yield, soil erosion loss, and water and nitrate dynamics. While its estimates of long-term average yields are accurate for most purposes, additional model development is desirable to fully reflect year-to-year variability. We tested the precision of EPIC (version 5300) in estimating mean yields and in replicating yearly yield variability as influenced by the potential evapotranspiration (PET) method, using field data from a 27-yr crop rotation experiment at Swift Current, Saskatchewan. Rotations tested ranged from continuous wheat (Triticum aestivum L.) to fallow-wheat-wheat. Mean estimated yields were compared with measured yields (MY) and detrended yields (DY). Estimated yields and MYs were further compared by regression, ratio of variances due to lack-of-fit and to experimental errors (R), and model efficiency (EF). Mean yields estimated using the Penman-Monteith and the Priestly-Taylor PET methods resulted in significant underestimations, associated with high annual PET values, and were not analysed further. The Hargreaves (H) and Baier-Robertson (BR) PET methods resulted in mean yields not different than MY or DY for most cases, especially the BR method. EPIC with the H method accounted for 18 to 66% of the variability in annual yield estimation, whereas the BR method accounted for 29 to 60%. These were slightly, but not significantly, lower than results obtained with regionally derived statistical crop models. Overall EPIC with the BR PET method provided yield estimates accurate and precise enough for long term studies. The relatively high R and low EF values obtained, though, suggest further improvements in EPIC are necessary to better replicate yearly yield variability. Analysis of yield residuals indicated that EPIC may not be simulating accurately enough the water balance and its effects throughout the off-season and in the early part of the growing season. Key words: Semiarid temperate climate, crop model, potential evapotranspiration
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12

Hannah, MC, and GJ O'Leary. "Wheat yield response to rainfall in a long-term multi-rotation experiment in the Victorian Wimmera." Australian Journal of Experimental Agriculture 35, no. 7 (1995): 951. http://dx.doi.org/10.1071/ea9950951.

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Seventy-six years of wheat yield data from a long-term rotation experiment at Dooen in the Victorian Wimmera were analysed to describe the response of wheat yield to seasonal rainfall, crop sequence, and time. Wheat yields from 7 different 1- to 4-course rotations involving wheat, barley, oat, field pea, grass pasture and fallow were compared as a function of growing-season (May-November) rainfall. The field layout had no within-year replication, but each phase of each rotation was represented once in each year. An approximate quadratic response of wheat yield to both current year and previous year May-November rainfall was observed for each rotation. Previous year May-November rainfall boosted wheat yields grown on fallow, but decreased the yield of wheat grown on field pea or wheat stubble. Highest wheat yields followed fallow preceded by pasture, high yields followed fallow preceded by a cereal, moderate yields followed field pea, and low yields occurred for continuous wheat. Long-term trends in wheat yields adjusted for rainfall depended on crop sequence and fluctuated more in the non-fallow, 3-course rotations. Over the 76 years, average yield declined in all rotations except the continuous wheat, which was always low, but there was evidence that yield of all continuous cropped rotations had increased during the last 2 decades.
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13

Širlová, L., J. Vacke, and M. Chaloupková. "Reaction of selected winter wheat varieties to autumnal infection with Wheat dwarf virus." Plant Protection Science 41, No. 1 (February 8, 2010): 1–7. http://dx.doi.org/10.17221/2732-pps.

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The response of 25 registered winter wheat varieties to autumnal infection with Wheat dwarf virus (WDV) was studied in small plot trials in two years. The materials were infected by vectors, leafhopper Psammotettix alienus Dahlbom, 1851 from three-leaf stage to tillering. The symptoms expression was monitored in spring and plant height, weight of above ground biomass and grain yield were observed in summer. All tested varieties were evaluated as susceptible and divided into three groups: varieties Banquet and Svitava with 87.3–93.1% grain yield reduction as moderately susceptible, varieties Clever, Drifter, Niagara and Rialto with 95.6–97.68% grain yield reduction as susceptible and varieties Apache, Batis, Bill, Complet, Contra, Corsaire, Ludwig, Mladka, Nela, Record, Rheia, Semper, Sepstra, Solara, Sulamit, Tower, Trend, Vlasta and Winsdor with 99.7–100% grain yield reduction as very susceptible. Statistically significant differences were observed between moderately susceptible and susceptible varieties as well as very susceptible ones in absorbency values by means of DAS-ELISA.
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14

P.K.SINGH, K.K.SINGH, PRIYANKA SINGH, R. BALASUBRAMANIAN, A.K.BAXLA, B.KUMAR, AKHILESH GUPTA, L.S.RATHORE, and NAVEEN KALRA. "Forecasting of wheat yield in various agro-climatic regions of Bihar by using CERES-Wheat model." Journal of Agrometeorology 19, no. 4 (December 14, 2017): 346–49. http://dx.doi.org/10.54386/jam.v19i4.604.

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Forecasting yield of crops is important for planners in taking tactical decisions for ensuring food availability. Crop simulation models are useful tool to forecast the crop yield. The CERES-wheat model calibrated and validated with experimental data was used to predict the district wise yield in Bihar. Based on the areas under different dates of sowing and crop cultivars, a correction factor was applied on simulated yield to predict the district wise and regional wheat yield. The simulated yield were higher than the actual yield in all the three agro-climatic zones, while the forecasted yields were very close to actual. The percentage deviation of the forecasted yield from the actual was ±4.0 %. The results clearly indicated that the CERES-Wheat model can be used to regional production estimates of wheat in Bihar.
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15

Hu, Naiyue, Chenghang Du, Wanqing Zhang, Ying Liu, Yinghua Zhang, Zhigan Zhao, and Zhimin Wang. "Did Wheat Breeding Simultaneously Improve Grain Yield and Quality of Wheat Cultivars Releasing over the Past 20 Years in China?" Agronomy 12, no. 9 (September 5, 2022): 2109. http://dx.doi.org/10.3390/agronomy12092109.

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Grain yield and quality of wheat are both important components for food security. Great effort has been made in the genetic improvement of wheat grain yield in China. However, wheat grain quality (i.e., protein concentration and protein quality) has received much less attention and is often overlooked in efforts to improve grain yield. A timely summary of the recent process of wheat breeding for increasing yield and quality (which can be used to guide future breeding strategies) is essential but still lacking. This study evaluated the breeding efforts on grain yield and grain quality of 1908 wheat varieties in China over the past two decades, from 2001 to 2020. We found wheat yields show a 0.64–1.03% annual growth in the three-dominant wheat-growing regions in China. At the same time, there was no significant decrease in wheat protein concentration. Genetic yield potential was increased, and the genetic yield gap was closed. High grain yields and better quality can likely be achieved simultaneously by genomic selection in future wheat breeding.
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16

Carew, Richard, Elwin G. Smith, and Cynthia Grant. "Factors Influencing Wheat Yield and Variability: Evidence from Manitoba, Canada." Journal of Agricultural and Applied Economics 41, no. 3 (December 2009): 625–39. http://dx.doi.org/10.1017/s1074070800003114.

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Production functions to explain regional wheat yields have not been studied extensively in the Canadian prairies. The objective of this study is to employ a Just-Pope production function to examine the relationship between fertilizer inputs, soil quality, biodiversity indicators, cultivars qualifying for Plant Breeders' Rights (PBR), and climatic conditions on the mean and variance of spring wheat yields. Using regional-level wheat data from Manitoba, Canada, model results show nitrogen fertilizer, temporal diversity, and PBR wheat cultivars are associated with increased yield variance. Mean wheat yield is reduced by the proportion of land in wheat, the interaction of growing temperature and precipitation, and spatial diversity. By contrast, higher soil quality and PBR wheat cultivars increase mean yield. The wheat yield increases attributed to PBR range from 37.2 (1.4%) to 54.5 kg/ha (2.0%). Plant Breeders' Rights may have enhanced royalties from increased certified seed sales, but the benefits in terms of higher wheat yield or lower yield variability are limited. Future research is required to understand the interactive effects of fertilization practices, genetic diversity, and environmental conditions on regional wheat yield stability.
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17

Chu, Lin, Chong Huang, Qingsheng Liu, Chongfa Cai, and Gaohuan Liu. "Spatial Heterogeneity of Winter Wheat Yield and Its Determinants in the Yellow River Delta, China." Sustainability 12, no. 1 (December 23, 2019): 135. http://dx.doi.org/10.3390/su12010135.

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Understanding spatial differences of crop yields and quantitatively exploring the relationship between crop yields and influencing factors are of great significance in increasing regional crop yields, promoting sustainable development of regional agriculture and ensuring regional food security. This study investigates spatial heterogeneity of winter wheat yield and its determinants in the Yellow River Delta (YRD) region. The spatial pattern of winter wheat in 2015 was mapped through time series similarity analysis. Winter wheat yield was estimated by integrating phenological information into yield model, and cross-validation was performed using actual yield data. The geographical detector method was used to analyze determinants influencing winter wheat yield. This study concluded that the overall classification accuracy for winter wheat is 88.09%. The estimated yield agreed with actual yield, with R2 value of 0.74 and root mean square error (RMSE) of 1.02 t ha−1. Cumulative temperature, soil salinity and their interactions were key determinants affecting winter wheat yield. Several measures are recommended to ensure sustainable crop production in the YRD region, including improving irrigation and drainage systems to reduce soil salinity, selecting salt-tolerant winter wheat varieties, and improving agronomy techniques to extend effective cumulative temperature.
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18

Evans, J., G. Scott, D. Lemerle, A. Kaiser, B. Orchard, G. M. Murray, and E. L. Armstrong. "Impact of legume 'break' crops on the yield and grain quality of wheat and relationship with soil mineral N and crop N content." Australian Journal of Agricultural Research 54, no. 8 (2003): 777. http://dx.doi.org/10.1071/ar02224.

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The effect of annual 'break' crops on the yield and protein content of wheat was investigated over 3 seasons on a Red Kandasol on the south-western slopes of New South Wales. The 'break' crops included lupin and pea grown for grain, pea and vetch managed for silage, clovers managed for silage or hay, and vetch and clovers managed for green manuring. Wheat was sown for 2 years following the legume year, or canola and wheat followed the legumes. Averaged over 3 experiments the yields of first crop wheat following pea or vetch silage crops were comparable with those after grain pea. Yields following clover forage conservation crops or green manures exceeded those after grain pea by at least 0.41 t/ha; average yield increase after clover green manure was 0.93 t/ha. In one experiment, yields of second crop wheat were greater, by up to 0.37 t/ha, after forage conservation or green manure legume 'breaks' than after grain legumes. In 2 experiments, second crop wheat yields were greater after a first crop of canola than a first crop of wheat. Compared with continuous wheat yield, aggregate mean wheat yield increases were 3.5–4 t/ha following grain legumes, pea, and vetch silage crops, but 5.3–6.3 t/ha following clover forage conservation and green manure crops. However, the relative effects of legume treatments on wheat yield were significantly seasonally dependent. Yield and grain protein variation in wheat after legumes was significantly correlated with variation in mineral N at wheat establishment. However, in one experiment, yield was correlated only with variation in mineral N below the 20-cm soil depth, whereas protein was correlated only with variation in mineral N above the 20 cm soil depth. Yield increases in first crop wheat did not occur at the expense of grain protein.
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19

Roell, Yannik E., Amélie Beucher, Per G. Møller, Mette B. Greve, and Mogens H. Greve. "Comparing a Random Forest Based Prediction of Winter Wheat Yield to Historical Yield Potential." Agronomy 10, no. 3 (March 14, 2020): 395. http://dx.doi.org/10.3390/agronomy10030395.

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Predicting wheat yield is crucial due to the importance of wheat across the world. When modeling yield, the difference between potential and actual yield consistently changes because of advances in technology. Considering historical yield potential would help determine spatiotemporal trends in agricultural development. Comparing current and historical yields in Denmark is possible because yield potential has been documented throughout history. However, the current national winter wheat yield map solely uses soil properties within the model. The aim of this study was to generate a new Danish winter wheat yield map and compare the results to historical yield potential. Utilizing random forest with soil, climate, and topography variables, a winter wheat yield map was generated from 876 field trials carried out from 1992 to 2018. The random forest model performed better than the model based only on soil. The updated national yield map was then compared to yield potential maps from 1688 and 1844. While historical time periods are characterized by numerous low yield potential areas and few highly productive areas, current yield is evenly distributed between low and high yields. Advances in technology and farm practices have exceeded historical yield predictions, mainly due to the use of fertilizer, irrigation, and drainage. Thus, modeling yield projections could be unreliable in the future as technology progresses.
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20

Semenov, Mikhail A., Rowan A. C. Mitchell, Andrew P. Whitmore, Malcolm J. Hawkesford, Martin A. J. Parry, and Peter R. Shewry. "Shortcomings in wheat yield predictions." Nature Climate Change 2, no. 6 (April 11, 2012): 380–82. http://dx.doi.org/10.1038/nclimate1511.

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21

Reynolds, Matthew, M. John Foulkes, Gustavo A. Slafer, Peter Berry, Martin A. J. Parry, John W. Snape, and William J. Angus. "Raising yield potential in wheat." Journal of Experimental Botany 60, no. 7 (April 10, 2009): 1899–918. http://dx.doi.org/10.1093/jxb/erp016.

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22

REYNOLDS, MATTHEW, JOHN FOULKES, ROBERT FURBANK, SIMON GRIFFITHS, JULIE KING, ERIK MURCHIE, MARTIN PARRY, and GUSTAVO SLAFER. "Achieving yield gains in wheat." Plant, Cell & Environment 35, no. 10 (August 20, 2012): 1799–823. http://dx.doi.org/10.1111/j.1365-3040.2012.02588.x.

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23

Winter, S. R., and J. T. Musick. "Grazed Wheat Grain Yield Relationships." Agronomy Journal 83, no. 1 (January 1991): 130–35. http://dx.doi.org/10.2134/agronj1991.00021962008300010030x.

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24

Ellen, J. "Growth, yield and composition of four winter cereals. I. Biomass, grain yield and yield formation." Netherlands Journal of Agricultural Science 41, no. 2 (June 1, 1993): 153–65. http://dx.doi.org/10.18174/njas.v41i2.628.

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A field experiment with 3 cultivars of each of 4 winter cereals (wheat, rye, triticale and barley), sown at about 320 plants/msuperscript 2, was conducted on a fertile clay soil in the central Netherlands. The N fertilizer was split-dressed: 120 kg/ha in total for wheat and triticale, and 60 kg/ha for rye and barley. The fewest shoots/msuperscript 2 were found in triticale (828/msuperscript 2), and the most in barley (1477/msuperscript 2). The average decrease in number of shoots during shoot/ear development was 51% in wheat, 54% in rye, 49% in triticale and 67% in barley. The rate of crop development was largest in rye and barley; they flowered and matured earlier than wheat and triticale. Rye was the first to attain a closed canopy (LAI >3), and had the lowest maximum LAI and shortest leaf area duration. Wheat and triticale stayed green longest. Average specific leaf weight was 4.3 mg/cmsuperscript 2 in wheat and triticale, and 3.7 mg/cmsuperscript 2 in rye and barley. The growth rate of the grains at the linear stage was fastest in barley (1.89 mg grain-1 d-1) and slowest in rye (0.89 mg grain-1 d-1). Total aboveground DM production was 18 790 kg/ha in wheat, 15 230 kg/ha in rye, 18 300 kg/ha in triticale and 12 460 kg/ha in barley. Grain yields (t/ha) were 8.74 (wheat), 6.64 (rye), 8.20 (triticale) and 6.62 (barley). Cultivar differences in grain yield and in yield components were mostly smaller in wheat and rye than in triticale and barley. The harvest index was highest in barley (53.3%) and lowest in rye (43.7%); in some plant species there were marked differences between cultivars, but in others there were not.
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NAIN, A. S., V. K. DADHWAL, and T. P. SINGH. "Use of CERES-Wheat model for wheat yield forecast in central Indo-Gangetic Plains of India." Journal of Agricultural Science 142, no. 1 (February 2004): 59–70. http://dx.doi.org/10.1017/s0021859604004022.

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A methodology was developed for large area yield forecast using a crop simulation model and a discrete technology trend, and was applied to the coherent wheat yield variability zones of Eastern Uttar Pradesh, India. The approach consisted of three major steps: (a) prediction of technology trend yield using historical yield series of the region; (b) prediction of weather-induced deviation in wheat yield using CERES-Wheat simulation model and relating weather-induced deviation in simulated yield to deviation in observed yield deviations from technology trend; and (c) final yield forecast by incorporating predicted yield deviation in trend predicted yield. The regression coefficients for step (b) were generated using 10 years' data (1984/85–1994/95) and the reliability of the approach was tested on a data set of 5 years' independent data (1995/96–1999/2000). The results showed that this approach could capture year-to-year variability in large area wheat yield with reasonable accuracy. The Root Mean Square Error (RMSE) between observed and predicted yield was reported as 0·098 t/ha for the mean yield of 2·072 t/ha (4·72%). However, the RMSE was slightly higher in the forecasting period in comparison to the calibration period. The use of this methodology for issuing the pre-harvest forecast and the effect of upgrading the technology trend were also studied. The pre-harvest forecasts were made using in-season weather data up to the end of February and climatic-normal for the rest of the wheat-growing season, which showed good agreement with observed wheat yields. The forecasts of wheat yield for the season 1999/2000 were made using the technology trend up to 1994/95 and the updated technology trend up to 1998/99, which showed that the RMSE fell in the latter case, from 4·10 to 2·50%.
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26

Bittman, S., J. Waddington, and D. A. Pulkinen. "Effect of N and P fertilizer on establishment of alfalfa with a wheat companion crop." Canadian Journal of Plant Science 71, no. 1 (January 1, 1991): 105–13. http://dx.doi.org/10.4141/cjps91-012.

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This study examines the effect of fertilizer applied before seeding on the grain yield of a wheat (Triticum aestivum L.) companion crop and on the forage yield and crude protein content of the underseeded alfalfa (Medicago media Pers.) in subsequent years. The crops were seeded into stubble at five sites in northeast Saskatchewan on soils ranging in texture from silty loam to silty clay. Combinations of three N rates (0, 57 and 114 kg ha−1) and three P rates (0, 28.5, 57 kg ha−1) were applied before seeding to the companion crop plots. Alfalfa was also seeded alone (clear-seeded) at the three P rates. Application of N increased wheat yield but lowered yield of companion-seeded alfalfa to a range of 65–95% of clear-seeded alfalfa in the year after seeding, depending on wheat yield. Alfalfa yields in subsequent years were more variable where wheat yields were high than where wheat yields were low. The wheat crop yielded 1300–2600 kg ha−1 of grain but reduced alfalfa yield over three years by 400–2100 kg ha−1. Phophorus increased yield of wheat without decreasing accumulated yield of alfalfa over 3 yr. The results of this study support the practice in northeast Saskatchewan of supplying N to the requirement of wheat and P to the greater requirement of alfalfa if these crops are seeded together. Key words: Forage, underseeding, yield, protein, Medicago media Pers., Triticum aestivum L.
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Biberdzic, Milan, Midrag Djordjevic, Sasa Barac, Nebojsa Deletic, and Slavisa Stojkovic. "Productivity of some winter wheat genotypes." Genetika 37, no. 2 (2005): 131–36. http://dx.doi.org/10.2298/gensr0502131b.

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Yields given by different genotypes are affected by many factors, but mostly by genotype, climatic conditions and applied growing practice. Therefore, the aim of this study was to establish productivity of many winter wheat genotypes in southern Serbia, through macro-trials. The results showed the difference of grain yield mean between the investigated seasons, and that difference amounted about 1300 kg/ha. The average yield was the highest in cultivars Toplica, Stamena, Evropa, NS-rana 5, and Renesansa. The lowest grain yield was given by cultivars Tina, Sara, Sreca, and Mina.
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28

Barber, J. S., and R. S. Jessop. "Factors affecting yield and quality in irrigated wheat." Journal of Agricultural Science 109, no. 1 (August 1987): 19–26. http://dx.doi.org/10.1017/s002185960008093x.

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SummaryTwo field experiments examined the effects of nitrogen fertilizer, irrigation frequency and three wheat varieties on the yield and quality of irrigated wheat on a heavy clay soil. In the first experiment, with irrigation supplied to all plots at mid-tillering and close to ear emergence, there were negative effects of nitrogen fertilizer on grain yield with the reverse occurring with grain protein. The variety Songlen had one of the highest grain yields combined with higher milling yields and flour protein. In the second experiment, yield was maximized with at least two irrigations, whilst increasing irrigation frequency reduced flour protein and dough development time. While WW15 gave the highest yields irrespective of nitrogen or irrigation treatments, this variety had the lowest flour protein. With only one irrigation or without irrigation, nitrogen fertilizer increased grain protein; more frequent irrigation reduced mean flour protein.
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29

Tarkivskiy, V. E., A. B. Ivanov, and D. A. Petukhov. "On the Issue of Forecasting Winter Wheat Yield." Machinery and Equipment for Rural Area, no. 11 (November 30, 2022): 18–22. http://dx.doi.org/10.33267/2072-9642-2022-11-18-22.

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The main methods for forecasting crop yields are given. The possibility of forecasting the yield of winter wheat based on the maximum values of the normalized vegetation index (NDVI) using real yield statistics has been demonstrated. Comparative indicators of the average actual yield and that calculated using the proposed models with predictive accuracy are presented.
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30

Gan, Y. T., G. P. Lafond, and W. E. May. "Grain yield and water use: Relative performance of winter vs. spring cereals in east-central Saskatchewan." Canadian Journal of Plant Science 80, no. 3 (July 1, 2000): 533–41. http://dx.doi.org/10.4141/p99-138.

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Changing economic conditions have provided strong incentives for grain producers to choose the most profitable cereal crops to grow. We determined grain yield and water use efficiency (WUE) for winter wheat (Triticum aestivum L.), fall rye (Secale cereale L.), hard red spring (HRS) wheat, Canada prairie spring (CPS) wheat, amber durum (Triticum turgidum L.), and barley (Hordeum vulgare L.) under no-till systems. Over 60% of yield variability existing among site/years was due to water use or evapotranspiration (ET) in semiarid east-central Saskatchewan. Mean grain yield increased by 16.3 kg ha−1 with each millimetre of increase in ET. Barley produced 3748 kg ha−1 of grain on average, or 21% higher than winter wheat, 27% higher than CPS wheat, 39% higher than rye or durum, and 50% higher than HRS wheat. Average yields differed less than 5% between winter wheat and CPS wheat, but in water-stressed environments, CPS wheat had 19 to 34% lower grain yield than winter wheat. In one of the five cases where winter wheat was seeded much later than the recommended seeding date, CPS wheat yields were 16% higher than winter wheat. With every millimetre of increased ET, CPS or barley increased grain yield by 22 kg ha−1, while winter wheat increased yield by 17 kg ha−1. Winter wheat and rye had no yield differences in general, but in more moist environments, winter wheat produced higher (up to 28%) grain yield than fall rye, and in the year when winter wheat was seeded late, winter wheat yielded 11% lower than rye. As fertiliser N increased from 50 to 100 kg ha−1, barley grain yield increased by 347 kg ha−1, and durum grain yield increased by only 5 kg ha−1. Winter wheat, fall rye and barley had greater WUE than the other spring cereals, but soil profile (0–120 cm) water in the spring did not differ among crops. In maximising grain yield and water use in east-central Saskatchewan, barley, winter wheat, and CPS wheat would provide the best options. Key words: Water-use efficiency, protein, winter wheat, Triticum aestivum, Secale cereale, Triticum turgidum, Hordeum vulgare
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31

Kozlovský, O., J. Balík, J. Černý, M. Kulhánek, M. Kos, and M. Prášilová. "Influence of nitrogen fertilizer injection (CULTAN) on yield, yield components formation and quality of winter wheat grain." Plant, Soil and Environment 55, No. 12 (December 28, 2009): 536–43. http://dx.doi.org/10.17221/165/2009-pse.

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The CULTAN (Controlled Uptake Long Term Ammonium Nutrition) system is based on one-time injection of the whole dose of nitrogen required for the vegetation period. The effect of this method on yield and grain quality of winter wheat was observed in a 2-year small-plot trial at 4 different experimental sites in the Czech Republic. The experiment comprised two treatments with the total amount of nitrogen applied during fertilization of 150 kg N/ha. At the CULTAN treatment the whole dose was applied all at once using the GFI 3A injection machine (Maschinen und Antriebstechnik GmbH Güstrow), whereas at the control treatment, the dose was divided into three applications. The average grain yield of winter wheat in 2007 was 9.56 t/ha (control) and 8.78 t/ha (CULTAN); in 2008 it was 9.91 t/ha (control) and 9.63 t/ha (CULTAN). The differences in 2008 were not statistically significant. The contents of nitrogen and gluten were significantly lower at CULTAN treatment in both years. The values of falling number, Zeleny test and bulk density were generally similar at both treatments.
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Das, A., Sharma RP, N. Chattopadhyaya, and R. Rakshit. "Yield trends and nutrient budgeting under a long-term (28 years) nutrient management in rice-wheat cropping system under subtropical climatic condition." Plant, Soil and Environment 60, No. 8 (August 10, 2014): 351–57. http://dx.doi.org/10.17221/46/2014-pse.

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We measured the long-term (28 years) sustainability of rice-wheat cropping system under integrated nutrient management practices emphasizing the trends in grain yields, sustainable yield index (SYI) and nutrient budgeting. The data of long-term experiment revealed that grain yield of both rice and wheat declined under control and sub-optimal fertilizer inputs (50% or 75% recommended fertilizer NPK). Negative yield trend (slope) was observed in control plots for rice (&ndash;0.0296) and wheat (&ndash;0.0070); whereas positive yield trend was observed under treatments receiving organic supplements. The SYI values indicate that rice yields are more sustainable than wheat. Data on apparent nutrient balance showed a deficit of N (&ndash;42.2 kg/ha/year), P (&ndash;9.1 kg/ha/year) and K (&ndash;52.2 kg/ha/year) under control plots. Surprisingly, there was net depletion of K under the organic supplemented plots. Correlation study revealed that apparent balance of K was negatively correlated with SYI (r = &ndash;0.921 for rice; r = &ndash;0.914 for wheat) and yield slope (r = &ndash;0.870 for rice; r = &ndash;0.896 for wheat). If the trend of K imbalance is not reversed, the potential to improve N and P fertilizer use efficiency and crop yields will be limited.
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33

Amgain, LP, NR Devkota, J. Timsina, and B. Bijay-Singh. "Effect of Climate Change and CO2 Concentration on Growth and Yield of Rice and Wheat in Punjab: Simulations Using CSM-CERES-Rice and CSM-CERES-Wheat Models." Journal of the Institute of Agriculture and Animal Science 27 (May 1, 2006): 103–10. http://dx.doi.org/10.3126/jiaas.v27i0.702.

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Recent trends of a decline or stagnation in the yield of rice and wheat in rice-wheat (RW) systems of the Indo-Gangetic Plains (IGP) have raised serious concerns about the regional food security. The effect of future climate change on crop production adds to this complex problem. The validated CSM-CERES-Rice and CSM-CERES-Wheat (Ver. 4.0) data were used to test the sensitivity of the models in Punjab, India. The models were sensitive to climatic parameters (temperature, CO2 concentration, solar radiation and rainfall) on yields of both crops. Simulated rice yields were sensitive to weather as there was 13% less yield of rice in 1999 than in 2001. Similarly, simulated wheat yields were also sensitive to weather, with the highest yield in 2001, and the lowest in 2003. Increments in both maximum and minimum temperatures by 4°C, decreased rice yield by 34% and wheat yield by 4% as compared to base scenario with current weather data. By increasing 4°C for both maximum and minimum temperature along with an increase in solar radiation by 1MJ/m2/day, rice yield decreased by 32% as compared to base scenario while wheat yields were not affected. With the increase in maximum and minimum temperatures by 4°C, and also an increase in CO2 concentration by 20 ppm from the standard CO2 concentration of 335 ppm, the reduction in rice yield was 33%, but in wheat yield was only 3%. Rainfed wheat yield increased by 7%, by increasing daily rainfall by 1.5 times, and by 13%, by doubling the rainfall, both after 96 days of sowing (DAS) to maturity. Lowering rainfall to zero, for each day after 96 DAS to until maturity reduced wheat yield by 18%. The increasing maximum and minimum temperatures irrespective of whether the CO2 concentration increased or not, seemed to have more adverse effects on rice than to wheat. Simulations demonstrated that CSM-CERES-Rice and CSM-CERES- Wheat are sensitive to CO2 and climatic parameters, and can be used to study the impact of future climate change on rice and wheat productivity in RW systems in Asia. Key words: CSM-CERES-Rice, CSM-CERES-Wheat, climate change, yield, phenology J. Inst. Agric. Anim. Sci. 27:103-110 (2006)
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34

Schillinger, William F., and Timothy C. Paulitz. "Canola versus wheat rotation effects on subsequent wheat yield." Field Crops Research 223 (June 2018): 26–32. http://dx.doi.org/10.1016/j.fcr.2018.04.002.

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35

WALKER, G. K. "WEATHER SENSITIVITY OF WESTERN CANADA WHEAT YIELD, 1900–1988." Canadian Journal of Soil Science 69, no. 4 (November 1, 1989): 857–65. http://dx.doi.org/10.4141/cjss89-086.

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Recent work suggests that climate change will impact negatively on Canadian prairie wheat through more severe and frequent droughts and increased yield variability, and adaptive strategies have been called for to meet the coming change. However, previous studies have not determined if climate change has already affected wheat yields, nor has the entire prairie region been examined. Using a prairie wheat yield simulation model (PWYSM) at current (constant) technology, it is shown that the weather as it affects wheat, has had a zero trend over the 1900–1988 period. Also, there is no evidence that yield variability has recently increased. Prairie wheat yields therefore appear so far unconnected to the global warming trend this century, suggesting no current need to adapt to a changing climatic regime. Results also show that, at current technology, departures from mean weather may cause decade-long average yield fluctuations as large as ± 10% from the long-term mean, and climate change effects must be detected against this background fluctuation. Also, a 35% decline in actual wheat yields from the first to fourth decades of this century was not matched by deteriorating weather although weather contributed to the decline, and improved yields since 1940 are not explained by better weather. The study of Williams et al. (1988) concluded that a 1930s type dry spell would reduce Saskatchewan wheat yield by 20%, compared to the 1961–1979 mean That applied only to stubble-sown wheat. When adjusted here for the contribution of fallow-sown wheat, the reduction became 16.7%. With Alberta and Manitoba included, the yield reduction for the whole prairie became 13.8% — in good agreement with a 14.0% reduction obtained with the PWYSM. Yield reductions for Saskatchewan are larger than for the prairie as a whole. The reference period chosen also significantly affects findings, and, because the last decade has been relatively unfavourable, PWYSM results show that 1930s type weather would lower mean prairie wheat yield by only 11.0% relative to the 1979–1988 mean. Grain industry decision makers would more likely refer to the last decade than to a more distant period such as 1961–1979, and applying relative yield reductions to the 1979–1988 mean would result in substantial yield underestimates for drought scenarios. Reference periods must be carefully selected for consistent results. Key words: Climate change, wheat yield
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36

SZUMIŁO, GRZEGORZ, LESZEK RACHOŃ, and BARBARA KROCHMAL-MARCZAK. "Effect of algae Ecklonia maxima extract (Kelpak SL) on yields of common wheat, durum wheat and spelt wheat." Agronomy Science 74, no. 1 (April 30, 2019): 5–14. http://dx.doi.org/10.24326/2019.1.1.

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The 3-year experiment was concerned with the response of spring forms of common wheat (Triticum aestivum L. subsp. aestivum), durum wheat (Triticum durum Desf.) and spelt wheat (Triticum aestivum subsp. spelta L. em. Thell.) to the foliar application of a plant growth stimulant (extract from marine algae Ecklonia maxima), with the commercial name of Kelpak SL (GS), as compared to control treatment (C). The following parameters were analysed: yield of grain, yield components (number of ears, weight of 1000 kernels, number and weight of kernels per ear) and physical indicators of grain quality (test weight, uniformity and vitreosity of grain). The study showed that the level of yielding and the yield components were related primarily with the wheat genotype, but they depended also on the agro-climatic conditions and on the algae extract and control experimental treatments. The application of algae extract, compared to the control, caused a significant increase in the yields of the spring wheat species under study, on average by 7.0%. Canopy spraying with algae extract had a favourable effect on the number of ears, on he number and weight of kernels per ear, but it had no effect on the weight of 1000 kernels. The grain quality of durum wheat, spelt wheat and common wheat was affected more strongly by the weather conditions in the successive years of the study and by the genotype than by the foliar application of algae extract. The spelt genotypes were characterised by lower yields and lower grain quality than common wheat and the durum wheat genotypes.
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37

Angus, J. F., J. A. Kirkegaard, J. R. Hunt, M. H. Ryan, L. Ohlander, and M. B. Peoples. "Break crops and rotations for wheat." Crop and Pasture Science 66, no. 6 (2015): 523. http://dx.doi.org/10.1071/cp14252.

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Wheat crops usually yield more when grown after another species than when grown after wheat. Quantifying the yield increase and explaining the factors that affect the increase will assist farmers to decide on crop sequences. This review quantifies the yield increase, based on >900 comparisons of wheat growing after a break crop with wheat after wheat. The mean increase in wheat yield varied with species of break crop, ranging from 0.5 t ha–1 after oats to 1.2 t ha–1 after grain legumes. Based on overlapping experiments, the observed ranking of break-crop species in terms of mean yield response of the following wheat crop was: oats < canola ≈ mustard ≈ flax < field peas ≈ faba beans ≈ chickpeas ≈ lentils ≈ lupins. The mean additional wheat yield after oats or oilseed break crops was independent of the yield level of the following wheat crop. The wheat yield response to legume break crops was not clearly independent of yield level and was relatively greater at high yields. The yield of wheat after two successive break crops was 0.1–0.3 t ha–1 greater than after a single break crop. The additional yield of a second wheat crop after a single break crop ranged from 20% of the effect on a first wheat crop after canola, to 60% after legumes. The mean yield effect on a third wheat crop was negligible, except in persistently dry conditions. The variability of the break-crop effect on the yield of a second wheat crop was larger than of a first wheat crop, particularly following canola. We discuss the responses in relation to mechanisms by which break crops affect soil and following crops. By quantifying the magnitude and persistence of break-crop effects, we aim to provide a basis for the decision to grow continuous cereal crops, strategic rotations or tactically selected break crops. In many wheat-growing areas, the large potential yield increases due to break crops are not fully exploited. Research into quantifying the net benefits of break crops, determining the situations where the benefits are greatest, and improving the benefits of break crops promises to improve the efficiency of wheat-based cropping systems.
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Kuresova, Gabriela, Jan Haberle, Pavel Svoboda, Jana Wollnerova, Michal Moulik, Jana Chrpova, and Ivana Raimanova. "Effects of Post-Anthesis Drought and Irrigation on Grain Yield, Canopy Temperature and 13C Discrimination in Common Wheat, Spelt, and Einkorn." Agronomy 12, no. 12 (November 24, 2022): 2941. http://dx.doi.org/10.3390/agronomy12122941.

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Fluctuations in precipitation and higher evapotranspiration due to rising temperatures are reflected in reduced wheat yields, even in areas with a low historical incidence of drought. In this study, the effects of drought (S) and irrigation (IR) on spelt, einkorn wheat, and two common wheat cultivars were assessed in a field experiment in the years 2018–2021. Water availability was differentiated from the flowering stage using a mobile cover and drip irrigation. Grain yield, canopy temperature, and discrimination of 13C in grain (Δ 13C) were monitored. Drought reduced the average grain yield of common wheat to 5.24 t.ha−1, which was 67.00% of the rain-fed control (C) yield, and 62.09% of the irrigated wheat yield. For spelt and einkorn wheat, the average grain yield from stressed plants was 2.02 t.ha−1; this was 79.97% of the C-variant yield, and 70.82% of the IR-variant yield. Higher stand temperatures were an excellent indicator of water deficit in the stressed crops. The relationship between temperature and final grain yield in the monitored variants was always negative. In all years, discrimination of 13C in grain corresponded to water availability; in its effect on yields, the correlation was always positive. Between 2018 and 2020, spelt and einkorn exhibited lower Δ 13C in comparison with common wheat in all variants, suggesting a greater impact of differentiated water supply. The results of the experiment conclusively demonstrated systematic effects of drought after flowering upon yields and other studied characteristics.
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39

Zhang, X., and P. M. Evans. "Grain yield production in relation to plant growth of wheat and canola following clover pastures in southern Victoria." Australian Journal of Experimental Agriculture 44, no. 10 (2004): 1003. http://dx.doi.org/10.1071/ea03064.

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The plant growth and grain yield of crops following a pasture phase in 1:1 pasture–crop rotations were studied in southern Victoria in 2001 (wheat and canola at Hamilton, and wheat at Streatham and Gnarwarre). Both the wheat and canola crops produced high grain yields with no application of nitrogen fertiliser. In experiment 1 (at Hamilton) where the crops were dependent on nitrogen input from subterranean clover pasture, canola produced 4.1 t/ha of grain and wheat averaged 6.0 t/ha. The 3 canola cultivars (Charlton, Mystic and Surpass 400) had similar grain yields. However, for wheat, the late-maturing spring wheat cv. Kellalac and the early-maturing spring wheat cv. Silverstar produced significantly higher grain yields (6.6 and 6.3 t/ha, respectively) than the late-maturing winter cv. Brennan (5.0 t/ha). The 3 cultivars of each crop differed markedly in their major yield components. The most striking differences were those shown by Silverstar, which had the highest yield, together with Kellalac, but had lower biomass and lower leaf area index than the 2 late-maturing wheats. Silverstar compensated by having 50% more grains per head than the late-maturing Brennan. While Silverstar flowered on average 34 days earlier than the 2 other wheats, it took some 3 weeks longer to mature after anthesis. In experiment 2, the wheat crop (cv. Silverstar) produced grain yields of 5.4 t/ha over 6 different treatments, with higher grain yields at Streatham (6.1 t/ha) than at Gnarwarre (4.7 t/ha). Across the 2 sites, the grain yields following clovers reached over 5.7 t/ha, in contrast with low grain yields from the continuous crop (3.7 t/ha) and fallow/crop treatments (3.7 t/ha). Grain yields were closely related to the herbage dry matter production of previous pasture legumes, indicating a positive crop response. This may, in turn, reflect the nutrient status of the treatments, particularly the nitrogen status.
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40

Kirkland, K. J., and J. H. Hunter. "Competitiveness of Canada prairie spring wheats with wild oat (Avena fatua L.)." Canadian Journal of Plant Science 71, no. 4 (October 1, 1991): 1089–92. http://dx.doi.org/10.4141/cjps91-151.

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Three spring wheat (Triticum aestivum L.) genotypes (Neepawa, a hard red spring, and HY320 and HY355 both Canada Prairie Spring wheats) were subjected to four levels of wild oat density at two locations over 4 yr to assess the effects of wild oat competition on biomass production, culm formation and yield. Wheat biomass and culm production were reduced at all wild oat density levels in each of the three cultivars. There were no significant differences among cultivars. In general, yields of all cultivars were reduced as wild oat density levels increased. Actual yield reductions at comparable wild oat densities tended to be greater at Regina than at Scott. There was a significant cultivar-by-density interaction for yield with yield reductions in HY320 > HY355 > Neepawa. Key words: Triticum aestivum, wheat (spring), wild oat density, competition, plant biomass, culms
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41

Macholdt, J., H. P. Piepho, B. Honermeier, S. Perryman, A. Macdonald, and P. Poulton. "The effects of cropping sequence, fertilization and straw management on the yield stability of winter wheat (1986–2017) in the Broadbalk Wheat Experiment, Rothamsted, UK." Journal of Agricultural Science 158, no. 1-2 (March 2020): 65–79. http://dx.doi.org/10.1017/s0021859620000301.

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AbstractThe development of resilient cropping systems with high yield stability is becoming increasingly important due to future climatic and agronomic challenges. Consequently, it is essential to compare the effects of different agronomic management practices, such as cropping sequences and nutrient supply, on the stability of crop yields. Long-term experiments are a valuable resource for investigating these effects, as they provide enough time to accurately estimate stability parameters. The objective of the current study was to compare the effects of different cropping sequencing (#1: continuous v. rotational), fertilization (#2: mineral v. organic) and straw management techniques (in the case of continuous wheat; #3: removal v. incorporation) on the yield stability of winter wheat; yield risk (the probability of yield falling below a threshold yield level) and inter-annual yield variability were used as stability indicators of the effects. Long-term yield data from the Broadbalk Wheat Experiment (Rothamsted, UK) were analysed using a mixed model. Overall, the results showed that rotational cropping combined with sufficient mineral N fertilizer, with or without organic manure, ensured stable wheat yields while reducing yield risk. In contrast, higher yield risks and inter-annual yield variabilities were found in continuous wheat sections with less mineral N fertilizer or with organic manure only.
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42

Gairhe, Janma Jaya, Mandeep Adhikari, Deepak Ghimire, Arun Khatri-Chhetri, and Dinesh Panday. "Intervention of Climate-Smart Practices in Wheat under Rice-Wheat Cropping System in Nepal." Climate 9, no. 2 (January 20, 2021): 19. http://dx.doi.org/10.3390/cli9020019.

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Besides a proper agronomic management followed by Nepalese farmers, wheat (Triticum aestivum L.) production has been severely affected by changing climate. There are many interventions, including climate-smart practices, to cope with this situation and possibly enhance crop and soil productivity. Field experiments were set up in a randomized complete block design with six treatments (TRT) with four replications in three locations (LOC) during wheat-growing seasons in Nepal from 2014 to 2016. Treatments included (i) Controlled Practice (CP), (ii) Improved Low (IL), (iii) Improved High (IH), (iv) Climate Smart Agriculture Low (CSAL), (v) Climate Smart Agriculture Medium (CSAM), and (vi) Climate Smart Agriculture High (CSAH), whereas those LOC were Banke, Rupandehi and Morang districts. There was a significant main effect of TRT and LOC on grain yield and a significant interactionn effect of TRT × LOC on biomass yield in 2014–2015. About 55.5% additional grain yield was produced from CSAM treatment compared to CP in 2014–2015. Among locations, grain yield was the highest in Banke (3772.35 kg ha−1) followed by Rupandehi (2504.47 kg ha−1) and Morang districts (2504.47 kg ha−1). In 2015–2016, there was a significant interaction effect of TRT × LOC on grain and biomass yields. The highest grain yield was produced from CSAH treatment in Banke district in 2015–2016. Overall, grain yield and other parameters showed a better response with either of the climate-smart interventions (mostly CSAH or CSAM) despite variability in geography, climate, and other environmental factors indicating the potential of climate-smart practices to improve wheat production in southern plains of Nepal.
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43

Lin, Haixia, Na Li, Yi Li, Hongguang Liu, Jian Liu, Linchao Li, Puyu Feng, Deli Liu, and Chuncheng Liu. "Quantitative Analysis of Winter Wheat Growth and Yields Responding to Climate Change in Xinjiang, China." Water 13, no. 24 (December 16, 2021): 3624. http://dx.doi.org/10.3390/w13243624.

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The knowledge of climate change effects on variations of winter wheat yields are crucial for productions. Our objectives were to investigate the relationship between yield-related indices of winter wheat and the related climatic variables (selected using variance inflation factors) at the 20 sites of Xinjiang, China over 1981–2017. The background of climate and yield changes was analyzed from temporal and spatial respects. The number of independent climatic variables was selected with the variance inflation factor method to remove the multicollinear feature. The Pearson correlation was conducted between the first difference values of climatic variables and yield-related indices of winter wheat (namely plant height, growth period duration, 1000-kernel weight, kernel number per ear, biomass and yield) to find the key climatic variables that impacted winter wheat growth and yields. The multi-variate linear and nonlinear functions were established step by step using the selected key climatic variables. The best function was determined for each site (significant for p < 0.05). From the results, there were general wetter and warmer trends of the climatic variables. Correspondingly, shortened winter wheat phenology and increased growth and yields were observed for most sites. Still, the climatic trends had mixed effects on winter wheat yields. The effects of precipitation, mean air temperature and relative humidity on plant height and growth period duration agreed well. Different sites had different major climatic drivers for winter wheat growth or yields, and the best functions of growth and yields could be linearly or nonlinearly, mostly described by multi-variate functions. The winter wheat growth or yield indices were also found to be closely connected with the soil water content status at the eight sites. The relationship between winter wheat growth or yield and climate provided useful references for forecasting crop production and for projecting the impact of future climate changes.
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44

Neogi, MG, JC Biswas, MM Khan, and MM Rashid. "Wheat–Lentil Mixed Cropping System Productivity Under Varied Irrigation Levels." Annals of Bangladesh Agriculture 25, no. 1 (March 21, 2022): 1–10. http://dx.doi.org/10.3329/aba.v25i1.58150.

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The study on mixed cropping of lentil and wheat was conducted under three levels of irrigation. Wheat at 10, 15, 20, 25, 30, 35, 40, 45 and 50% of the normal seed rates were mixed with full seed rate of lentil to find out a suitable mixing rate of wheat for maximum total yield from unit land. The study was conducted in a split plot design with three replications. Lentil yields obtained with single and two irrigations were identical and higher than with no irrigation. The highest wheat yield was obtained with two irrigations. Total yield was the highest with application of two irrigations. Mixing different proportions of wheat with lentil produced 95-171% additional yield over sole cropping of lentil. Mixing of wheat at 25-35% with lentil was found to be judicious for obtaining maximum total yields. The highest protein yield was obtained with 30-35% and 35% mixing rates of wheat at zero and single irrigation levels. Growing wheat with lentil resulted in increased protein yield in wheat than sole cropping. The highest land equivalent ratio (LER) values were obtained when 30-35% of wheat seed rate were mixed with lentil. Application of two irrigations resulted in high LER values. It is concluded that use of 35% of wheat seed rate along with full seed rate of lentil under two levels of irrigations would be the best mixing ratio for obtaining the highest wheat and total grain yield. Ann. Bangladesh Agric. (2021) 25 (1) : 1-10
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45

PRAGYAN KUMARI and A.WADOOD. "Impact assessment of intra seasonal temperature variations on wheat yield using CERES Wheat model." Journal of Agrometeorology 18, no. 2 (December 1, 2016): 245–48. http://dx.doi.org/10.54386/jam.v18i2.942.

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A field experiment was conducted at Ranchi (Jharkhand) during rabi season of 2009-10 to 2011-12 with wheat cultivar K 9107 sown on three dates (Nov 20,Dec 5 and Dec 20) to calibrate and validate the CERES-wheat model. There was a good agreement between simulated and observed wheat yields, days to anthesis and days to maturity. The validated model was used to study the impact of intra seasonal temperature variation on wheat. The sensitivity analysis of CERES wheat model, with respect to temperature variations and wheat yield, revealed that increase in temperature above the normal values to 3 oC, showed considerable yield reduction (12- 17 per cent) under different sowing dates. Similarly, with decrease in seasonal temperature up to 3oC, the yield enhancement by 12-16 per cent was observed. Sensitivity of CERES wheat model to incremental units of intra seasonal temperature showed a gradual decrease in yield as well as days to maturity under varied sowing dates. Increase in temperature ( 3 oC from normal) during 2nd fortnight of January (16-31st ) was observed to be the most detrimental for wheat crop with respect to its yield for timely sowing date (20thNov) whereas it would be maximum during 2nd fortnight of February (15-28th) for moderately normal sown (5th Nov) and late sown crops (20thDec).
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46

Gou, Fang, Martin K. van Ittersum, Guoyu Wang, Peter E. L. van der Putten, and Wopke van der Werf. "Yield and yield components of wheat and maize in wheat–maize intercropping in the Netherlands." European Journal of Agronomy 76 (May 2016): 17–27. http://dx.doi.org/10.1016/j.eja.2016.01.005.

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47

Zhang, Rui, Yingnan Yang, Tinghui Dang, Yuanjun Zhu, and Mingbin Huang. "Responses of Wheat Yield under Different Fertilization Treatments to Climate Change Based on a 35-Year In Situ Experiment." Agriculture 12, no. 9 (September 18, 2022): 1498. http://dx.doi.org/10.3390/agriculture12091498.

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Fertilization, as one of many important field management practices, can increase crop yields. However, whether different levels of fertilization will affect the response of wheat yields to inter-annual climate variations and long-term climate trends is not clear. In this study, 35-year wheat yields were used to investigate the responses of wheat yield to inter-annual climate variations and long-term climate trends under different fertilization treatments. The first difference method was used to de-trend wheat yields and climate variables and stepwise regression analysis was used to quantify the yield–climate relationship. The experimental design consisted of a control treatment (CK without fertilization) and three fertilizer treatments: nitrogen, phosphorus, and manure (NPM with 120 kg ha−1 N, 26.2 kg ha−1 P, and 75 t ha−1 manure), nitrogen and phosphorus (NP with 120 kg ha−1 N and 26.2 kg ha−1 P), and manure (M with 75 t ha−1 manure). Compared to the CK treatment, the NPM, NP, and M treatments increased wheat yield by an average of 201.9, 161.7, and 130.6% and increased yield inter-annual variability by an average of 191.2, 149.3, and 144.2%, respectively, during the study period (1985–2020). Inter-annual climate fluctuations in the study area explained 45, 38, 27, and 29% of wheat yield variations and 35-year climatic trends contributed to wheat yield decreases of 0.3, 0.7, 1.6, and 1.8% for the NPM, NP, M, and CK treatments, respectively. The results show the impact of inter-annual climate fluctuations on yield increases with the increasing level of fertilization, while the effect of long-term climate trends on yield decreases with the increasing level of fertilization.
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48

Banks, PM, JL Davidson, H. Bariana, and PJ Larkin. "Effects of barley yellow dwarf virus on the yield of winter wheat." Australian Journal of Agricultural Research 46, no. 5 (1995): 935. http://dx.doi.org/10.1071/ar9950935.

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Yield responses were measured of six winter wheats to field infections with Barley Yellow Dwarf Virus (BYDV). In addition to the natural incidence of virus, the range of infection levels was widened by aphicide spraying of some plots and the addition of artificially propagated viruliferous aphids to others. Significant grain yield losses attributable to natural infections by BYDV were found for all wheats despite the main infection period being in the spring. The addition of viruliferous aphids only marginally decreased yields further. Spraying with aphicides did not exclude infection but did reduce the incidence of BYDV and increase yields. A significant negative linear correlation between grain yield and percentage infection applied to each wheat genotype. The slope of the yield response appears to be a more useful measurement for comparing tolerance to BYDV of differing cereal lines than do proportional yield losses. Of the six wheats tested, Lawson, Birch 41, Birch 75, Owlet and Isis had similar tolerances to BYDV, despite substantial differences in absolute yields, while W71 was considerably more vulnerable. The mean natural incidence of BYDV in the main trial was 67%, producing an expected grain yield loss of about 2.2 t ha-1 for W71 and about 1.1 t ha-1 for the other five wheats. Effects on grain protein and potential control measures are also discussed.
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49

Milan, Mirosavljevic, Momcolovic Vojislava, Maksimovic Ivana, Putnik-Delic Marina, Pržulj Novo, Hristov Nikola, and Mladenov Novica. "Pre-anthesis development of winter wheat and barley and relationships with grain yield." Plant, Soil and Environment 64, No. 7 (June 21, 2018): 310–16. http://dx.doi.org/10.17221/202/2018-pse.

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The aim of this study was to improve understanding of (1) the effect of genotypic and environmental factors on pre-anthesis development and leaf appearance traits of barley and wheat; (2) the relationship of these factors with grain yield, and (3) the differences between these two crops across different environments/sowing dates. Therefore, trials with six two-row winter barley and six winter wheat cultivars were carried out in two successive growing seasons on four sowing dates. Our study showed that the observed traits varied between species, cultivars and sowing dates. In both growing seasons, biomass at anthesis and grain yield declined almost linearly by delaying the sowing date. There was no clear advantage in grain yield of wheat over barley under conditions of later sowing dates. Generally, barley produced more leaf and had shorter phyllochron than wheat. Both wheat and barley showed a similar relationship between grain yield and different pre-anthesis traits.
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50

Qiao, Shengchao, Han Wang, I. Colin Prentice, and Sandy P. Harrison. "Optimality-based modelling of climate impacts on global potential wheat yield." Environmental Research Letters 16, no. 11 (October 22, 2021): 114013. http://dx.doi.org/10.1088/1748-9326/ac2e38.

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Abstract Evaluation of potential crop yields is important for global food security assessment because it represents the biophysical ‘ceiling’ determined by variety, climate and ambient CO2. Statistical approaches have limitations when assessing future potential yields, while large differences between results obtained using process-based models reflect uncertainties in model parameterisations. Here we simulate the potential yield of wheat across the present-day wheat-growing areas, using a new global model that couples a parameter-sparse, optimality-based representation of gross primary production (GPP) to empirical functions relating GPP, biomass production and yield. The model reconciles the transparency and parsimony of statistical models with a mechanistic grounding in the standard model of C3 photosynthesis, and seamlessly integrates photosynthetic acclimation and CO2 fertilization effects. The model accurately predicted the CO2 response observed in FACE experiments, and captured the magnitude and spatial pattern of EARTHSTAT ‘attainable yield’ data in 2000 CE better than process-based models in ISIMIP. Global simulations of potential yield during 1981–2016 were analysed in parallel with global historical data on actual yield, in order to test the hypothesis that environmental effects on modelled potential yields would also be shown in observed actual yields. Higher temperatures are thereby shown to have negatively affected (potential and actual) yields over much of the world. Greater solar radiation is associated with higher yields in humid regions, but lower yields in semi-arid regions. Greater precipitation is associated with higher yields in semi-arid regions. The effect of rising CO2 is reflected in increasing actual yield, but trends in actual yield are stronger than the CO2 effect in many regions, presumably because they also include effects of crop breeding and improved management. We present this hybrid modelling approach as a useful addition to the toolkit for assessing global environmental change impacts on the growth and yield of arable crops.
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