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The paper purpose was to assess the impact of climate change on wheat, maize and sunflower yield in the period 2017-2021, using statistical data from National Institute of Statistics (NIS) and National Administration of Meteorology (NAM) and other sources. Comparison method was used to evaluate the deviations between the registered air temperatures and precipitations and the 1981-2010 climatological norm. Graphic method reflected the dynamics of monthly air temperatures and rainfalls in each year. Descriptive statistics for mean, standard deviation and coefficient of variation reflected an more comprehensive image upon air temperature, precipitations and yield. Correlations and regression equations were used to establish the intensity of the kinks between climate factors and yield. The highest average air temperature In Romania was 12.130C in 2019. In the period 2017-2020, the average annual temperatures exceeded the climatological norm 1981-2010 accounting for 9.10C. The lowest rainfalls, 614.2 mm, were recorded in 2019, being below of 633.1 mm the norm for the period 1981-2010. The high temperatures associated with drought and low precipitations have deeply affected yield of many agricultural crops, including maize, wheat and sunflower. The highest wheat yield 4,888 kg/ha was achieved in 2017, and the lowest one, 2,966 kg/ha in 2020. Maize registered the highest performance of 7,644 kg/ha in 2018, and the lowest one, 3,977 kg/ha in 2020. Sunflower carried out the high performance 3,041 kg/ha in 2018, and the lowest one, 1,858 kg/ha in 2020. The worst agricultural years for these three crops was 2020, but 2017 favored wheat, while 2018 favored maize and sunflower. The correlation coefficient had in general small values between average temperature and yield, but a higher link with precipitations level. The multiple correlation between yield, air temperatures and precipitations was: r= 0.817 for wheat, r = 0.116 for maize and r = 0.504 for sunflower. In the South Eastern Dobrogea, the driest area in Romania, the rainfalls declined by 65% in the period 2018-2020 having a deep negative impact on sunflower seeds yield, which decreased from 4,282 kg/ha in 2018, to 1,503 kg/ha in 2020. The correlation between precipitations and sunflower yield positive and very strong (r = 0.737). As a conclusion, the climate conditions should be analyzed in each farm and farmers have to take measure to adapt the technologies for sustaining production. [ABSTRACT FROM AUTHOR]

The increased frequency of climate extremes associated with ongoing climate change has the potential for significant impacts on maize grain yield in maize-producing regions worldwide. In this study, we used a modeling approach to investigate the effects of different types of climatic extremes on maize grain yield in Northeast China. We combined annual mean air temperature and accumulated precipitation data and divided the climate years into 9 categories, using the 10th and 90th percentiles as extreme thresholds. The climate data were represented by 1 normal climate type, 4 individual climate extremes, and 4 combined climate extremes. Changes in the frequencies of climate extremes and their impacts on maize grain yields were analyzed for two 30-year periods (period I: 1960–1989; period II: 1990–2019) using the Agricultural Production Systems sIMulator (APSIM-Maize). Compared with period I, the occurrences of the normal climate and all 3 cold-related climate extremes (i.e., cold-normal, cold-humid, and cold-dry) decreased during period II, while occurrences of the other climate extremes increased. Moreover, according to the APSIM-Maize model, the estimated yield in the years with a normal climate decreased by 4.01%; the 3 cold-related climate extremes increased yields by 26.56%, 12.10%, and 6.68%, respectively; the 2 warm-related climate extremes (warm-normal and warm-dry) and normal-humid years decreased estimated yields by 6.39%, 24.12%, and 5.10%, respectively. The increase in the occurrence of warm-humid years increased the estimated yield by 11.69%. This work confirms the adverse effects of warmer temperatures in the absence of excess rainfall on grain yield and highlights the importance of extremely dry or wet conditions under normal temperature conditions. [ABSTRACT FROM AUTHOR]

Recent global warming and more frequent droughts are causing significant damage to maize production. A reliable estimate of drought intensity and duration is essential for testing maize hybrids to drought tolerance. For this purpose, the self-calibrating 10-day palmer drought severity index (scPDSI) and standardized precipitation index (SPI) for 1, 2, 3, 6, 9, 18, 27, and 36 10-day scales were used to estimate the effects of drought on grain yield of 32 maize hybrids evaluated in 2017 and 2018 at eight experimental locations in the Pannonian part of Croatia. Time series of observed 10-day mean air temperature, relative humidity, and precipitation totals for a set of "reference" weather stations of the croatian meteorological and hydrological service (DHMZ) for the period 1981–2018 were used to calculate the scPDSI and SPI indices. According to the 10-day scPDSI and SPI for different time scales, 2018 proved to be a "normal year," while 2017 experienced a "mild to moderate drought," which resulted in a 13% reduction in maize grain yield at eight experimental locations compared to 2018. The correlation between grain yield and drought indices for summer months was the highest for the 10-day scPDSI. To some extent, correlations between summer months' SPI for the 3 10-day time scale and maize grain yield were comparable to the corresponding correlations for the 10-day scPDSI. However, for other SPI time scales considered, the corresponding correlations were weaker and less informative. The dependence of grain yield on scPDSI values was not the same for all hybrids, indicating their different tolerance to drought. The reduction in grain yield due to drought was primarily caused by insufficient grain filling (lower 1000-grain weight) and, to some extent, by a reduction in the number of grains. In this study, application of 10-day scPDSI data proved to be more relevant in detecting effects of drought on agronomic traits than application of SPI data for the most time scales. [ABSTRACT FROM AUTHOR]

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In this study, the AquaCrop model was used to quantify climate change impact on yield and net irrigation in maize and soybean production. Daily observed climate data (1961-1990) from Osijek weather station were used for past climate simulation, and output data from ECHAM model were dynamically downscaled under two IPCC SRES scenarios (A1B, A2) for two integration periods 2041-2070 and 2071- 2100. The soil properties and crop data were presented from 6-year-long (2010-2015) field study of the Agricultural Institute in Osijek, Osijek-Baranja County. The climate results showed expected rise in air temperature up to 5 ºC and significantly lower precipitation up to 43.5%. According to results from the AquaCrop model, there is no change in maize yield in non-irrigated conditions, while in irrigated conditions there is a yield increase of 1.4 t ha-1 of dry matter (dm), with 80 mm higher net irrigation in comparison with the 1961-1990 period. As for soybean production, the increase in yield is expected in both non-irrigated and irrigated conditions. The yield increases up to 1.9 dm t ha-1 in irrigated conditions with 90 mm higher net irrigation in comparison with the 1961-1990 period. As for crop water indices, in non-irrigated conditions the water use efficiency (WUE) has a trend to decrease in the future, while in irrigated conditions it can slightly increase. Irrigation water use efficiency (IWUE) showed significantly higher increase in irrigated maize and soybean production. [ABSTRACT FROM AUTHOR]

Aflatoxins (AFs) are one of the most frequent contaminants in maize. The Republic of Serbia represents a leader in terms of maize production and exports in Europe. In recent years, Serbia faced climate changes. Therefore, the main objective of this study was to examine AF occurrence in 3000 maize samples collected during 2012-2016. In maize samples from 2012, 2013, 2015, and 2016, AFs were detected in 72.3%, 24.7%, 36.7%, and 5.0% of the samples, in concentration ranges of 1.0-111.2, 1.2-65.2, 1.1-76.2, and 1.3-6.9 µg kg−1, respectively. Contrary to this, in maize samples from 2014, no AFs were detected. Analysis of weather conditions indicates that 2012 was characterised by extreme drought conditions, 2013 and 2015 by lack of precipitation and high air temperatures, 2014 as the rainiest year in these years, while 2016 had moderate weather conditions. [ABSTRACT FROM AUTHOR]