Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria

2012 ◽  
Vol 151 (6) ◽  
pp. 813-835 ◽  
Author(s):  
J. EITZINGER ◽  
S. THALER ◽  
E. SCHMID ◽  
F. STRAUSS ◽  
R. FERRISE ◽  
...  
Keyword(s):  
Drought Stress ◽  
Winter Wheat ◽  
Crop Yields ◽  
Weather Conditions ◽  
Extreme Weather ◽  
Soil Tillage ◽  
Soil Conditions ◽  
Grain Yields ◽  
Crop Models ◽  
Short Period

SUMMARYThe objective of the present study was to compare the performance of seven different, widely applied crop models in predicting heat and drought stress effects. The study was part of a recent suite of model inter-comparisons initiated at European level and constitutes a component that has been lacking in the analysis of sources of uncertainties in crop models used to study the impacts of climate change. There was a specific focus on the sensitivity of models for winter wheat and maize to extreme weather conditions (heat and drought) during the short but critical period of 2 weeks after the start of flowering. Two locations in Austria, representing different agro-climatic zones and soil conditions, were included in the simulations over 2 years, 2003 and 2004, exhibiting contrasting weather conditions. In addition, soil management was modified at both sites by following either ploughing or minimum tillage. Since no comprehensive field experimental data sets were available, a relative comparison of simulated grain yields and soil moisture contents under defined weather scenarios with modified temperatures and precipitation was performed for a 2-week period after flowering. The results may help to reduce the uncertainty of simulated crop yields to extreme weather conditions through better understanding of the models’ behaviour. Although the crop models considered (DSSAT, EPIC, WOFOST, AQUACROP, FASSET, HERMES and CROPSYST) mostly showed similar trends in simulated grain yields for the different weather scenarios, it was obvious that heat and drought stress caused by changes in temperature and/or precipitation for a short period of 2 weeks resulted in different grain yields simulated by different models. The present study also revealed that the models responded differently to changes in soil tillage practices, which affected soil water storage capacity.

scholarly journals Is Crop Growth model Able to Reproduce Drought Stress Caused by Rain-Out Shelters Above Winter Wheat?

2018 ◽  
Vol 66 (1) ◽  
pp. 225-233
Author(s):  
Markéta Wimmerová ◽  
Petr Hlavinka ◽  
Eva Pohanková ◽  
Kurt Christian Kersebaum ◽  
Miroslav Trnka ◽  
...  
Keyword(s):  
Drought Stress ◽  
Winter Wheat ◽  
Growth Model ◽  
Soil Moisture Content ◽  
Crop Yields ◽  
Weather Conditions ◽  
Crop Growth ◽  
Stress Effect ◽  
Crop Growth Model ◽  
Precipitation Reduction

This study evaluates drought stress effect on winter wheat. Simultaneously, the ability of the HERMES crop growth model to reproduce the process correctly was tested. The field experiment was conducted at Domanínek station in 2014 and 2015, where mobile rain-out shelters were installed on plots of winter wheat (May 2015). Precipitation was reduced in three replications and the findings were compared with results from control plots with ambient precipitation. A precipitation reduction of 93 mm led to reduced growth and decrease in grain yields. The results of this study showed that the model was able to reproduce soil moisture content well and reproduce the drought stress for crop yields of winter wheat to a certain extent. When rain-out shelters were used, real winter wheat yields were reduced by 1.7 t/ha. The model underestimated the yields for the sheltered variant by 0.67 t/ha on average against observed yields and overestimated development of leaf area for both unsheltered and sheltered variants. This overestimation was partly explained by the effect of excluded UV radiation. The outcome of this paper may help to reduce uncertainty within simulated yields of winter wheat under extreme weather conditions through a better understanding of model behavior.

scholarly journals Trends of weather-related impacts on Austrian crop production under changing climate

2021 ◽  
Author(s):  
Sabina Thaler ◽  
Josef Eitzinger ◽  
Gerhard Kubu
Keyword(s):  
Climate Change ◽  
Winter Wheat ◽  
Crop Production ◽  
Crop Yields ◽  
Weather Conditions ◽  
Crop Growth ◽  
Risk Indicators ◽  
Climate Scenarios ◽  
Crop Water

<p>Weather-related risks can affect crop growth and yield potentials directly (e.g. heat, frost, drought) and indirectly (e.g. through biotic factors such as pests). Due to climate change, severe shifts of cropping risks may occur, where farmers need to adapt effectively and in time to increase the resilience of existing cropping systems. For example, since the early 21st century, Europe has experienced a series of exceptionally dry and warmer than usual weather conditions (2003, 2012, 2013, 2015, 2018) which led to severe droughts with devastating impacts in agriculture on crop yields and pasture productivity.</p><p>Austria has experienced above-average warming in the period since 1880. While the global average surface temperature has increased by almost 1°C, the warming in Austria during this period was nearly 2°C. Higher temperatures, changing precipitation patterns and more severe and frequent extreme weather events will significantly affect weather-sensitive sectors, especially agriculture. Therefore, the development of sound adaptation and mitigation strategies towards a "climate-intelligent agriculture" is crucial to improve the resilience of agricultural systems to climate change and increased climate variability. Within the project AGROFORECAST a set of weather-related risk indicators and tailored recommendations for optimizing crop management options are developed and tested for various forecast or prediction lead times (short term management: 10 days - 6 months; long term strategic planning: climate scenarios) to better inform farmers of upcoming weather and climate challenges.</p><p>Here we present trends of various types of long-term weather-related impacts on Austrian crop production under past (1980-2020) and future periods (2035-2065). For that purpose, agro-climatic risk indicators and crop production indicators are determined in selected case study regions with the help of models. We use for the past period Austrian gridded weather data set (INCA) as well as different regionalized climate scenarios of the Austrian Climate Change Projections ÖKS15. The calculation of the agro-climatic indicators is carried out by the existing AGRICLIM model and the GIS-based ARIS software, which was developed for estimating the impact of adverse weather conditions on crops. The crop growth model AQUACROP is used for analysing soil-crop water balance parameters, crop yields and future crop water demand.</p><p>Depending on the climatic region, a more or less clear shift in the various agro-climatic indices can be expected towards 2050, e.g. the number of "heat-stress-days" for winter wheat increases significantly in eastern Austria. Furthermore, a decreasing trend in maize yield is simulated, whereas a mean increase in yield of spring barley and winter wheat can be expected under selected scenarios. Other agro-climatic risk indicators analysed include pest algorithms, risks from frost occurrence, overwintering conditions, climatic crop growing conditions, field workability and others, which can add additional impacts on crop yield variability, not considered by crop models.</p>

scholarly journals Development of Algorithms and Software Systems for Motion Control of a Robotic Tillage Unit

2019 ◽  
Vol 13 (2) ◽  
pp. 48-52 ◽  
Author(s):  
Yakov P. Lobachevsky ◽  
Sergey E. Lonin ◽  
Ilya S. Alekseev ◽  
Nikolay T. Goncharov ◽  
Irina I. Afonina ◽  
...  
Keyword(s):  
Motion Control ◽  
Labor Productivity ◽  
Crop Yields ◽  
Negative Impact ◽  
Weather Conditions ◽  
Field Work ◽  
Soil Tillage ◽  
Research Purpose ◽  
Software Systems ◽  
Random Factor

Abstract. Automation of agricultural machinery is aimed at solving specific practical tasks: control and maintenance of the technological process quality, increasing labor productivity as well as crop yields. The method of "precision farming" is economically expedient, since it is a direct saving of technological material, as well as it helps reducing the negative impact on the environment and farm produce. (Research purpose) The research purpose is to review and analyze the main aspects required to develop the algorithms and software for motion control systems for a robotic tillage unit. (Materials and methods) To implement process control, it is necessary to control the direction of travel along a specified path, change the speed of movement depending on the engine load, switching the transmission gears. Physical-and-mechanical characteristics of the unit are rather heterogeneous and depend on weather conditions. Therefore, the algorithm for controlling the power of the robotic mobile unit must take into account, as much as possible, variations in the external effects of drawbar properties and the motion resistance, as a random factor. (Results and discussion) The authors have developed an imitation model representing the movement of a robotic unit. For the simulation, use has been made of a cyclic trajectory of the unit movement, consisting of two types of sections: the rectilinear ones reflecting the soil tillage pattern, and the turn areas where the unit makes a turn along a curvilinear trajectory around a certain center. (Conclusions) The implementation of robotic technologies in agricultural production result in increased technical, technological, production and economic indicators of agricultural units in field work, increased labor productivity, reduced time required for fieldworks, more rational use of bioenergy resources, increased yields of agricultural crops and reduced environmental impacts.

Methodological approaches to the use of images from uavs to assess the technological stress of crops

2021 ◽  
pp. 27-38
Author(s):  
S. Shvorov ◽  
◽  
N. Pasichnyk ◽  
O. Opryshko ◽  
I. Bolbot ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Crop Yields ◽  
Plant Protection ◽  
Computer Training ◽  
Soil Conditions ◽  
Monitoring Methods ◽  
Prolonged Action ◽  
High Resolution Data ◽  
Distribution Of Stress ◽  
The Impact

The article is devoted to the applied aspects of UAV use, namely the monitoring of winter wheat crops in relation to the stresses caused by technological stresses. First of all, this applies to the prolonged action of herbicides left over from the predecessor crop and which cause stress in new crops. The issue has local specifics related to the inconsistency of plant cultivation technologies and to the insufficient study of the impact of the latest plant protection products in domestic soil conditions. Restoration of crop yields is possible with timely identification of the causes of stress, but decision-making time is limited, which requires the introduction of the latest monitoring technologies suitable for industrial scale. In laboratory studies using phytochambers, the presence of both spectral indicators of healthy and affected plants and the difference in their dimensions were recorded. However, such differences can be explained by other stressors, so it was not possible to establish clear criteria for spectral or spectral-spatial monitoring methods that clearly indicated the stress caused by the after-effects of herbicides. In field studies using the Slantrange complex mounted on a DJI Matrice 600 UAV as an object of study, the distribution of stress areas in the field was analyzed. It was found that, in purely spectral and spectral-spatial monitoring of winter wheat, it was not possible to reliably identify the stressful nature caused by the aftereffects of herbicides, ie ground platforms for spectral sensor equipment are ineffective. It is proved that the maps of stress indices obtained on the basis of high-resolution data from UAVs can be considered as a separate object of research on the interpretation of the causes of stress of complex biotechnical objects such as crops. Improving the reliability and reliability of monitoring data can be achieved by implementing systems of machine data processing and computer training to find correlations between the distribution of stress in plants in the field and the implementation of technological operations, terrain. Key words: UAV, stress, prolonged action of herbicides, Slantrange

EFFECT OF RATE, TIMING AND PLACEMENT OF N FERTILIZER ON STUBBLED-IN WINTER WHEAT GROWN ON A BROWN CHERNOZEM

1990 ◽  
Vol 70 (1) ◽  
pp. 151-162 ◽  
Author(s):  
C. A. CAMPBELL ◽  
J. G. McLEOD ◽  
F. SELLES ◽  
F. B. DYCK ◽  
C. VERA ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Protein Concentration ◽  
Weather Conditions ◽  
Early Spring ◽  
N Fertilizer ◽  
Grain Protein ◽  
N Recovery ◽  
Severe Drought ◽  
Grain Yields ◽  
Brown Soil

Winter wheat (Triticum aestivum L.) production in Saskatchewan has increased in recent years due to the introduction of Norstar, a winter hardy variety, and due to the reduction in winter injury when the crop is seeded directly into standing stubble (stubbling-in). Large variations in the amount and distribution of seasonal precipitation in the Brown soil zone may prove detrimental to the adoption of this system. If implemented, fertilizer recommendations will need to be developed to fit this cropping system. A 4-yr study was conducted at Swift Current, Saskatchewan on an orthic Brown Chernozemic silt loam soil to determine the effect of rate, season of application, and placement of urea-N on grain yields and protein concentration of stubbled-in winter wheat. Plant density was unaffected by N. In 1984–1985 and 1986–1987 adequate weather conditions from seeding to early spring resulted in acceptable plant stands, but in 1985–1986 suboptimal winter temperatures and in 1987–1988 severe drought during fall and early spring reduced over-winter survival of wheat. Only 1 year provided better-than-average growing season weather conditions and thus good yields. Grain protein was < 11.5% (the critical lower level for milling) in two of the 4 years. In 1 year, a dry fall and winter coupled with a prolonged hot, dry early spring resulted in poor grain yields and very high protein concentrations (20–22%). Fertilizer-nitrogen, broadcast at 50 kg ha−1 at seeding, resulted in yields and grain protein concentrations similar to those when N was broadcast in April. Band placement of N was superior to broadcast application only in terms of grain protein concentration and N fertilizer recovery. There was no difference between banding N at 5 and 10 cm depth. In all years studied, application of N at 100 kg ha−1 was excessive for this system. It was concluded that producers should be cautious in attempting to grow stubbled-in winter wheat in the Brown soil zone.Key words: Yield, grain protein, N recovery, plant population, kernel weight

scholarly journals The influence of mineral fertilisers, farmyard manure, liming and sowing rate on winter wheat grain yields

2018 ◽  
Vol 64 (No. 1) ◽  
pp. 38-46 ◽  
Author(s):  
Madaras Mikuláš ◽  
Mayerová Markéta ◽  
Kumhálová Jitka ◽  
Lipavský Jan
Keyword(s):  
Winter Wheat ◽  
Farmyard Manure ◽  
Climatic Conditions ◽  
Soil Conditions ◽  
Wheat Grain ◽  
Response Curves ◽  
Grain Yields ◽  
Yield Increase ◽  
Yield Trends

The influence of mineral fertilisers, liming, farmyard manure and sowing rate on the winter wheat grain yields was studied in a long-term field experiment at 4 sites under different soil and climatic conditions in the Czech Republic. A total of 135 partial fraction-factorial experiments were performed between 1980 and 2013 and evaluated using a statistical model with linear and quadratic terms for each factor. Yield trends demonstrated remarkable influence of fertilisation at two sites of lower starting productivity. Here, grain yields increased by 50% and 25% since the trial commencement, while the rate of yield increase was low at more productive sites. Yields were the most frequently influenced by nitrogen (N) fertilisation, uniformly at all sites. N response curves were strongly curvilinear, but these differed between sites and were affected by preceding crops. The relative frequency of statistically significant influences decreased in the following order: N (significant at α &lt; 0.05 in 89% of all partial trials) &gt; sowing rate (29%) &gt; phosphorus (22%) &gt; farmyard manure (15%) &gt; potassium (12%) &gt; liming (8%). This order and the frequencies of these influences are discussed with regard to relevant site and soil conditions.

scholarly journals The effect of soil and weather conditions on yields of winter wheat in multi-environmental trials

2019 ◽  
Vol 56 (2) ◽  
pp. 263-279 ◽  
Author(s):  
Marzena Iwańska ◽  
Michał Stępień
Keyword(s):  
Winter Wheat ◽  
Crop Yields ◽  
Wheat Yield ◽  
Weather Conditions ◽  
Grain Filling ◽  
Growth Stages ◽  
Yield Data ◽  
Winter Wheat Yield ◽  
Crop Growth Stage ◽  
The Impact

SummaryDrought reduces crop yields not only in areas of arid climate. The impact of droughts depends on the crop growth stage and soil properties. The frequency of droughts will increase due to climate change. It is important to determine the environmental variables that have the strongest effect on wheat yields in dry years. The effect of soil and weather on wheat yield was evaluated in 2018, which was considered a very dry year in Europe. The winter wheat yield data from 19 trial locations of the Research Center of Cultivar Testing (COBORU), Poland, were used. Soil data from the trial locations, mean air temperature (T) and precipitation (P) were considered as environmental factors, as well as the climatic water balance (CWB). The hydrothermal coefficient (HTC), which is based on P and T, was also used. The effect of these factors on winter wheat yield was related to the weather conditions at particular growth stages. The soil had a greater effect than the weather conditions. CWB, P, T and HTC showed a clear relationship with winter wheat yield. Soil data and HTC are the factors most recommended for models predicting crop yields. In the selection of drought-tolerant genotypes, the plants should be subjected to stress especially during the heading and grain filling growth stages.

scholarly journals Discriminant analysis in the assessment of crop yields on agribusiness soils

2020 ◽  
Author(s):  
А.В. РУЧКИНА ◽  
Р.Н. Ушаков ◽  
А.О. Елизаров ◽  
Т.Ю. Амелина
Keyword(s):  
Discriminant Analysis ◽  
Crop Rotation ◽  
Life Support ◽  
Crop Yields ◽  
Weather Conditions ◽  
Point Of View ◽  
Soil Conditions ◽  
Yield Data ◽  
Economic Point ◽  
Grey Forest Soil

Цель исследований – методом дискриминантного анализа оценить вклад абиотических (почвенные условия, осадки) и биотических (сорняки) факторов в формировании урожайности зерновых культур. Урожайность является производной множества условий, проявляющихся в двух результирующих факторах – климатических и почвенных с подчинением классическим законам земледелия. Реализация продукционного процесса сельскохозяйственных растений, его гомеостатические возможности зависят не только от наличия ресурсов жизнеобеспечения, но и от их доступности для растения. Материальными носителями, обуславливающими доступность ресурсов в почве, являются различные компоненты, которые генерируют разнообразные связи внутри почвы и в формате почва - растение. Чтобы хоть как-то разобраться со всей сложностью явления формирования урожайности, необходимо применять методы многомерного статистического анализа, в частности, дискриминантный анализ. Минимальное значение продуктивности севооборотов, с экономической точки зрения, не должно составлять ниже 25-30 ц з.ед/га. Массив данных по урожайности зерновых культур был разбит на группу 1 (урожайность ниже 25-30 ц з. ед/га) и группу 2 (больше 25-30 ц з. ед/га). Всего было определено 180 комбинаций. Это стало возможным благодаря многолетнему опыту, заложенному Л.В. Ильиной по комплексному окультуриванию агросерой почвы с внедрением систем удобрений, обработки, севооборотов. Дискриминация между группами была значима. В процедуре дискриминации наиболее желательным является присутствие переменной «Сорняки» (соответствует наибольшее значение Уилкса Лямбда). На данный факт указывает также значение частной лямбды (характеризует единичный вклад), именно переменная «Сорняки» дает наибольший вклад, вторая переменная по значению вклада – «Калий». Скорее всего, ощутимый вклад сорняков обусловлен конкуренцией с их стороны за использование одних и тех же экологических ресурсов, которые необходимы и культурным растениям. За счет более эффективной организации экологической ниши сорная растительность снижает потенциал реализации климатических и погодных условий. The aim of the studies is to assess the contribution of abiotic (soil conditions, precipitation) and biotic (weed) factors in the formation of crop yields by discriminatory analysis. Yield is a derivative of the many conditions evident in the resulting two factors - climatic and soil with submission to the classical laws of farming. The realization of the production process of agricultural plants, its homeostatic capabilities depend not only on the availability of life support resources, but also on their availability for the plant. The material carriers that make resources available in the soil are various components that generate a variety of connections within the soil and in soil-plant format. The methods of multidimensional statistical analysis, in particular discriminant analysis, allow to understand at least all the complexity of the phenomenon of yield formation. From an economic point of view, the minimum productivity of crop rotation should not be lower than 30 c z. piece/hectare. The crop yield data array was divided into group 0 (yield below 25-30 c z. Unit/ha) and group 1 (more than 25-30 c z. piece/hectare). A total of 180 combinations were determined. This was made possible by the long-term experience laid down by L. V. Ilina on the complex culturing of grey forest soil with the introduction of fertilizer systems, treatment, crop rotation. Discrimination between groups was significant. The presence of the Weeds variable in the discrimination procedure is most desirable (corresponding to Wilkes lambda 's greatest value). This is also indicated by the value of the private lambda (characterizes the unit contribution), i.e. the variable "Weeds" gives the contribution more than all, the variable. "Potassium" is the second most important contribution. The significant contribution of weeds seems to be due to competition on their part for the use of the same environmental resources as cultural plants. Due to more efficient organization of ecological niche, weed vegetation reduces the potential for realization of climatic and weather conditions.

scholarly journals Effects of Bias-Corrected Regional Climate Projections and Their Spatial Resolutions on Crop Model Results under Different Climatic and Soil Conditions in Austria

Agriculture ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1029
Author(s):  
Sabina Thaler ◽  
Herbert Formayer ◽  
Gerhard Kubu ◽  
Miroslav Trnka ◽  
Josef Eitzinger
Keyword(s):  
Winter Wheat ◽  
Crop Production ◽  
Crop Yields ◽  
Spatial Scales ◽  
Spring Barley ◽  
Crop Model ◽  
Soil Water Storage ◽  
Soil Conditions ◽  
Climate Projections ◽  
Climate Conditions

The quality, reliability, and uncertainty of Austrian climate projections (ÖKS15) and their impacts on the results of the crop model DSSAT for three different orographic and climatic agricultural regions in Austria were analyzed. Cultivar-specific grain yields of winter wheat, spring barley, and maize were simulated for different soil classes to address three main objectives. First, the uncertainties of simulated crop yields related to the ÖKS15 projections were analyzed under current climate conditions. The climate projections revealed that the case study regions with higher humidity levels generally had lower yield deviations than the drier regions (yield deviations from −19% to +15%). Regarding the simulated crop types, spring barley was found to be less sensitive to the climate projections than rainfed maize, and the response was greater in regions with a low soil water storage capacity. The second objective was to simulate crop yields for the same cultivars using future climate projections. Winter wheat and spring barley tended to show increased yields by the end of the century due to an assumed CO2-fertilization effect in the range of 3–23%, especially under RCP 8.5. However, rainfed and irrigated maize were associated with up to 17% yield reductions in all three study regions due to a shortened growth period caused by warming. The third objective addressed the effects of crop model weather input data with different spatial resolutions (1 vs. 5, 11, and 21 km) on simulated crop yields using the climate projections. Irrigated grain maize and rainfed spring barley had the lowest simulated yield deviations between the spatial scales applied due to their better water supply conditions. The ranges of uncertainty revealed by the different analyses suggest that impact models should be tested with site representative conditions before being applied to develop site-specific adaptation options for Austrian crop production.

scholarly journals Effects of methods and systems of the primary soil tillage on the yields of seed, vegetable oil and protein of soybean and spring rapeseed in the first crop rotation cycle

2021 ◽  
Vol 185 (1) ◽  
pp. 43-51
Author(s):  
V.P. Savenkov ◽  
◽  
A.V. Dedov ◽  
N.N. Khryukin ◽  
◽  
...  
Keyword(s):  
Winter Wheat ◽  
Crop Rotation ◽  
Vegetable Oil ◽  
Seed Yield ◽  
Weather Conditions ◽  
Experimental Period ◽  
Soil Tillage ◽  
Vegetative Period ◽  
Oil Crops

We studied the influence of various methods and systems of the primary soil tillage on the yields of seeds, vegetable oil and protein of soybean and spring rapeseed at the All-Russian Rapeseed Research Institute (Lipetsk, Lipetsk region) in 2015–2018. In the field crop rotation (soybeans, winter wheat, spring rapeseed and barley), four systems of the primary soil tillage have been carried out, these are conventionally referred to as: moldboard-surface tillage, moldboardsurface tillage with deep loosening, moldboardsurface tillage with shallow loosening and minimal treatment (subsurface). The soil at the experimental field was leached, heavy clay loam chernozem. The weather conditions during the vegetative period varied according to the years of the research, which affected the seed yield and quality of soybean and spring rapeseed. We revealed the largest and relatively equal yields of seeds, vegetable oil and protein per a hectare of soybean and spring rapeseed was provided by moldboard-surface tillage (plowing under soybean and rapeseed, surface tillage for winter wheat and barley) and moldboard-surface tillage with deep loosening (deep subsurface loosening under soybean, plowing under spring rapeseed and surface tillage under winter wheat and barley), and the lowest yield was obtained using minimal soil treatment (chisel plowing under spring rapeseed and surface tillage under soybean and cereal crops). The quality of seed yield of oil crops in the studied experimental variants was practically equal. At the same time, in general, during the experimental period, the yield and the total yields of vegetable oil and protein of spring rapeseed were significantly higher than those of soybean.

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