scholarly journals   Environment and weather influence on quality and market value of hops

2012 ◽  
Vol 58 (No. 4) ◽  
pp. 155-160 ◽  
Author(s):  
V. Pavlovic ◽  
M. Pavlovic ◽  
A. Cerenak ◽  
I.J. Kosir ◽  
B. Ceh ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Acid Content ◽  
Correlation Coefficients ◽  
Market Value ◽  
Weather Conditions ◽  
Growing Season ◽  
Time Period ◽  
Weather Parameters ◽  
Time Periods ◽  
Sum Of Active Temperatures

The paper analyses the influence of four main weather parameters on alpha-acid contents for the main hop variety Aurora (Super Styrian Aurora) in Slovenian production for the time period 1994&ndash;2009. Through inspection of correlation coefficients, it tries to find specific times of the year when the weather conditions affect the alpha-acid content with a view to prediction in Slovenia. The most significant time periods of weather that influenced the alpha-acid contents of the Aurora variety during the growing season are identified as attributes of temperatures calculated from the interval from 25<sup>th</sup> to 30<sup>th</sup> week (T<sub>2530</sub>, r = &ndash;0.88, P &lt; 0.01), as attributes of rainfall and sunshine from the interval from 25<sup>th</sup> to 29<sup>th</sup> week (R<sub>2529</sub>, r = 0.85, P &lt; 0.01 and S<sub>2529</sub>, r = &ndash;0.75, P &lt; 0.01) and attributes of relative humidity from the interval from 27<sup>th</sup> to 32<sup>nd</sup> week (RH<sub>2732</sub>, r = 0.71, P &lt; 0.01). The attribute T<sub>2530</sub> represents the sum of active temperatures from June 18 to July 29 of that year. Similarly, the attribute R<sub>2529</sub> corresponds to the rainfall (in mm or L/m<sup>2</sup>) that fell during the June 18 to July 22 etc. &nbsp;

scholarly journals The impact of weather conditions on alpha-acid content in hop (Humulus lupulus L.) cv. Aurora

2020 ◽  
Vol 66 (No. 10) ◽  
pp. 519-525
Author(s):  
Douglas MacKinnon ◽  
Viljem Pavlovič ◽  
Barbara Čeh ◽  
Boštjan Naglič ◽  
Martin Pavlovič
Keyword(s):  
Relative Humidity ◽  
Acid Content ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Humulus Lupulus ◽  
Forecasting Model ◽  
Time Period ◽  
Humulus Lupulus L ◽  
Time Of Year ◽  
The Impact

The influence of four main weather attributes on the content of alpha-acids of the hop cv. Aurora for the period 1994–2019 was studied. By analysing correlation coefficients, specific times of the year when the weather conditions affect the alpha-acid content with the goal of creating a forecasting model in Slovenia were identified. The most significant periods of weather that impacted the alpha-acid contents throughout the growing time of year are recognised as attributes of temperatures (T), rainfall (R) and sunshine (S) calculated from the 25<sup>th</sup> to 30<sup>th</sup> week (T<sub>2530</sub>, r = –0.78, P &lt; 0.01; R<sub>2529</sub>, r = 0.72, P &lt; 0.01 and S<sub>2529</sub>, r = –0.81, P &lt; 0.01) and attributes of relative humidity (RH) from the 27<sup>th</sup> to 32<sup>nd</sup> week (RH<sub>2732</sub>, r = 0.82, P &lt; 0.01). T<sub>2530</sub> stands for the amount of active temperatures from June 18 to July 29. Likewise, R<sub>2530</sub> matches to the precipitation (in mm or L/m<sup>2</sup>) during the same time period.  

scholarly journals Market value assessment of hops by modeling of weather attributes

2013 ◽  
Vol 59 (No. 6) ◽  
pp. 267-272 ◽  
Author(s):  
M. Pavlovic ◽  
V. Pavlovic ◽  
C. Rozman ◽  
A. Udovc ◽  
D. Stajnko ◽  
...  
Keyword(s):  
Sunshine Duration ◽  
Correlation Coefficients ◽  
Market Value ◽  
Weather Conditions ◽  
Growing Season ◽  
Value Assessment ◽  
Air Humidity ◽  
Weather Factors ◽  
Air Temperatures

The effect of major weather factors on the quality of hops in Slovenia from 1994 to 2009 is analyzed and discussed. For this purpose, the three main varieties, namely Savinjski golding, Aurora and Bobek were merged into a model variety which we called Virtual. Through assessment of correlation coefficients, we tried to find specific times of the year when the weather conditions affect the alpha-acid content with a view toward prediction. The most significant time periods of weather that influenced the alpha-acid contents of hops during the growing season are identified as attributes of air temperatures calculated during the interval from the 24<sup>th</sup> to the 31<sup>st</sup> week (T<sub>2431</sub>; r = &ndash;0.92;P &lt; 0.01), as attributes of rainfall and sunshine duration calculated during the interval from the 25<sup>th</sup> to the 29<sup>th</sup> week (R<sub>2529</sub>; r = 0.83; P &lt; 0.01 and S<sub>2529</sub>, r = &ndash;0.76; P &lt; 0.01), and as attributes of air humidity calculated during the interval from the 28<sup>th</sup> to the 33<sup>rd</sup> week (RH<sub>2833</sub>; r = 0.77; P &lt; 0.01).

scholarly journals Temperature-related Variables Associated with Yield of ‘Kerman’ Pistachio in the San Joaquin Valley of California

HortScience ◽  
2017 ◽  
Vol 52 (4) ◽  
pp. 598-605 ◽  
Author(s):  
Craig E. Kallsen
Keyword(s):  
Crop Yield ◽  
Air Temperature ◽  
Growing Season ◽  
San Joaquin Valley ◽  
Efficient Allocation ◽  
Time Period ◽  
Processing Facility ◽  
Time Periods ◽  
Advance Knowledge ◽  
Facility Capacity

Information on how annual pistachio yield is affected by air temperature (Ta) during the winter and growing season is lacking. Timely advance knowledge of the magnitude of the yield of the California pistachio harvest would be beneficial for the pistachio industry for efficient allocation of harvest and postharvest resources, such as personnel, harvesting machinery, trucks, processing facility capacity, crop storage facilities, and for making marketing decisions. The objective of this study was to identify parameters, especially Ta variables and time periods, calculated from Ta data during the previous fall, winter, spring, and summer, that were associated most closely with fall nut-crop yield. The premise of this study was that sequential, historical yield records could be regressed against a number of Ta-derived variables to identify Ta thresholds and accumulations that have value in explaining past and predicting subsequent nut yield. Of the 27 regression variables examined in this study, the following, which were all negatively correlated with subsequent yield, explained the greatest proportion of the variability present in predicting yield of ‘Kerman’ pistachio: yield of the previous-year harvest, hourly Ta accumulations above 26.7 or 29.4 °C from the time period between 20 Mar. and 25 Apr., hourly Ta accumulations below 7.2 °C from 15 Nov. to 15 Feb., and hourly Ta accumulations above 18.3 °C from 15 Nov. to 15 Feb.

scholarly journals Spatial and temporal variation in weather events critical for boreal agriculture: II Precipitation

2016 ◽  
Vol 25 (1) ◽  
Author(s):  
Pirjo Peltonen-Sainio ◽  
Pentti Pirinen ◽  
Hanna M. Mäkelä ◽  
Hannu Ojanen ◽  
Ari Venäläinen
Keyword(s):  
Temporal Variation ◽  
Crop Protection ◽  
Growth Yield ◽  
Weather Conditions ◽  
Growing Season ◽  
Spatial And Temporal Variation ◽  
Finnish Meteorological Institute ◽  
High Soil Moisture ◽  
Weather Events ◽  
Time Period

There is great temporal and spatial variation in precipitation in Finland. Both drought episodes and repeated, abundant rains may interfere with crop growth, yield and quality formation, and many agricultural operations (such as tillage, sowing, crop protection and harvesting). The windows for optimal operations are often narrow due to the short growing season and variable weather conditions. Field traffic at high soil moisture may e.g. cause soil compaction. Also, the high environmental footprint on agriculture under high latitude conditions is often attributable to fluctuations in precipitation. The station-wise precipitation observations from the Finnish Meteorological Institute for the time period of 54 years (1961‒2014) were interpolated to a regular 10 km × 10 km grid covering the whole country. Several successive time slices were used to calculate the likelihood of: 1) drought periods and 2) periods with repeated rains with above normal precipitation sum so that both of these lasted for at least a) two weeks or b) three weeks. We demonstrated substantial spatial and temporal variation in the likelihood of drought and repeated rains: drought episodes were common during the early half of the growing season, while again repeated rains with high accumulated precipitation (lasting for two weeks) became common in the latter part of the growing season. Though, we highlighted in this paper some examples of how these events may affect agriculture and their environmental impacts, the datasets published here may be applied for many other assessments.

scholarly journals Prediction model for deoxynivalenol in wheat grain based on weather conditions

2010 ◽  
Vol 45 (Special Issue) ◽  
pp. S33-S37 ◽  
Author(s):  
M. Váňová ◽  
K. Klem ◽  
P. Matušinský ◽  
M. Trnka
Keyword(s):  
Relative Humidity ◽  
Environmental Factors ◽  
Winter Wheat ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Weather Data ◽  
Wheat Grain ◽  
Average Temperature ◽  
Preceding Crop ◽  
Beginning Of Flowering

Environmental factors influence the growth, survival, dissemination and hence the incidence of <i>Fusarium</i> fungi and the disease severity. The knowledge of the quantitative and qualitative effects of environmental factors and growing practices on initial infection, disease development and mycotoxin production is important for prediction of disease severity, yield impact and grain contamination with mycotoxins. The objective of this study was to design a model for prediction of deoxynivalenol (DON) content in winter wheat grain based on weather conditions, preceding crop and soil cultivation. The grain samples from winter wheat field experiments conducted in 2002–2005 to determine the effect of preceding crop in combination with soil cultivation on Fusarium head blight infection were analysed for the DON content. Average daily weather data (temperature, rainfall, relative humidity) were collected using an automated meteorological station and analysed separately for April, May and a 5 days period prior to the beginning of flowering and 5 days after the beginning of flowering. The correlation coefficients of DON content to weather data were calculated for monthly data prior to heading and 5 days data prior to and after the beginning of anthesis. Highest positive correlation coefficients were found for sum of precipitation in April, average temperature in April, and sum of precipitation 5 days prior to anthesis. Significant negative correlation was found for average temperature in May and average relative humidity 5 days prior to anthesis. Using the data from this experiment, we trained neural networks for prediction of deoxynivalenol content on the basis of weather data and preceding crop. The most appropriate neural network model was then coupled with AgriClim model to simulate spatial and temporal variation of DON content in wheat samples for south Moravia and north-east Austria area.

scholarly journals Coronavirus Seasonality, Respiratory Infections and Weather

2020 ◽  
Author(s):  
Gordon L. Nichols ◽  
Emma Gillingham ◽  
Helen Macintyre ◽  
Sotiris Vardoulakis ◽  
Shakoor Hajat ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Influenza A ◽  
Respiratory Infections ◽  
Global Radiation ◽  
Weather Conditions ◽  
Seasonal Distribution ◽  
England And Wales ◽  
Daily Average ◽  
Weather Parameters ◽  
Coronavirus Infections

Abstract Background: The survival of coronaviruses are influenced by weather conditions and seasonal coronaviruses are more common in winter months. We examine the seasonality of respiratory infections in England and Wales and the associations between weather parameters and seasonal coronavirus cases.Results: The seasonal distribution of 985,524 respiratory infections in England and Wales (1989-2019) showed coronavirus infections had a similar seasonal distribution to influenza A and bocavirus, with a winter peak between weeks 2-8. Seasonal coronaviruses from 2012 to 2019 were compared to weather parameters for the 28-day average before the patient’s specimen date. Ninety percent of infections occurred where the daily mean ambient temperatures were below 10oC; where daily average global radiation exceeded 500kJ/m2/hour; where sunshine was less than 5 hours per day; or where relative humidity was above 80%. Coronavirus infections were significantly more common where daily average global radiation was under 300 kJ/m2/hour (OR 4.3; CI 3.9-4.6; p<0.001); where average relative humidity was over 84% (OR 1.9; CI 3.9-4.6; p<0.001); where average air temperature was below 10oC (OR 6.7; CI 6.1-7.3; p<0.001) or where sunshine was below 4 hours (OR 2.4; CI 2.2-2.6; p<0.001) when compared to the distribution of weather values for the same time period. Seasonal coronavirus infections in children under three years old were more frequent at the start of an annual epidemic than at the end, suggesting that the size of the susceptible child population may be important in the annual cycle. Conclusions: The dynamics of seasonal coronaviruses reflect immunological, weather, social and travel drivers of infection. Evidence from studies on different coronaviruses suggest that low temperature and low radiation/sunlight favour survival. This implies a seasonal increase in SARS-CoV-2 may occur in the UK and countries with a similar climate as a result of an increase in the R0 associated with reduced temperatures and solar radiation. Increased measures to reduce transmission will need to be introduced in winter months for COVID-19.

Variation of morphological indicators of three-line hybrids sunflower and their parental forms

2021 ◽  
pp. 43-54
Keyword(s):  
Plant Growth ◽  
Plant Height ◽  
Correlation Coefficient ◽  
Pollen Fertility ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Growing Season ◽  
Hydrothermal Coefficient ◽  
Average Plant ◽  
Fertility Restorers

The article presents the results of three-year (2016–2018) studies of five three-line hybrids of the IMC selection - Agent, Agronomichny, Marshal, Kamenyar, Zaporozhskij 28 and their parent components - simple unreduced hybrids - ZL22A/102B, ZL42A/46B, ZL42A/58B and pollen fertility restorers – ZL512V, ZL678V and ZL7034V. It was found that individual indicators do not change synchronously. The Agent, Marshal and Kamenyar hybrids had the highest plant height in 2016, one each in 2017 – Agronomichny and in 2018 – Zaporozhskij 28. At the same time, three hybrids (Agent, Agronomical, Marshal) had the largest basket diameter in 2018 and two (Zaporozhskij 28, Kamenyar) in 2017. The shortest growing season hybrids Marshal, Zaporozhskij 28 and Kamenyar had in 2016 (90, 105 and 105 days), and two – Agent and Agronomichny in 2018 – 100 and 103 days, respectively. Among the simple unrecovered hybrids, two – ZL42A/46B and ZL42A/58B had high indicators of plant height, basket diameter and duration of the growing season in 2016. In the ZL22A/102B hybrid, the diameter of the basket was also the largest in 2016 (18.5 cm), the average plant height in 2016 – 124.5 cm was slightly lower than in 2018 (125.4 cm), also in these years in it almost coincided with the duration of the growing season – 97 days in 2016 and 96 in 2018 Fertility restorers had the highest indicators of plant height and basket diameter in 2017, also this year they had the shortest growing season, in 2016, on the contrary, they had the lowest height and the diameter of the basket, and the long growing season. The size of the baskets in the Marshal and Kamenyar hybrids correlates with the moisture supply of plants and the hydrothermal coefficient – the correlation coefficients are 0.997, 0.902 and 0.990, 0.973, respectively. The phases of organogenesis of plants of hybrids Kamenyar and Zaporozhskij 28 are greatly influenced by temperature, the correlation coefficient of this indicator with plant height and with the duration of the growing season is 0.996 for Kamenyar and 0.946 for Zaporozhskij 28, and with a hydrothermal coefficient – 0.939 and 0.753. In the Agent hybrid, the temperatures in June have the greatest influence on plant growth - the correlation coefficient is 0.997 and precipitation in May is 0.968, and the temperatures in May - 0.999 and June - 0.998 on the size of the basket. For the height of plants and the duration of the growing season at Agronomichny, moisture availability at the beginning of the growing season is very important, the correlation coefficients are 0.918 and 0.994, and in August during the filling of seeds 0.996 and 0.927, as well as July precipitation is 0.995. Of the simple unrecovered hybrids, the most demanding for heat is ZL22A/102B - the correlation coefficients are 0.941 with plant height and vegetation duration, 0.843 with the basket size. For ZL42A/58B, the most important are the May precipitation, their correlation with the vegetation duration of 1,000 and the basket diameter of 0.987, and the July temperatures - 0.999 and 0.993, respectively. Among the pollen fertility restorers, the line ZL512V turned out to be the most demanding to weather conditions. For plant growth, the temperatures of April (0.906), May (0.995) and June (1.000) are very important, for the duration of the growing season respectively – 0.958, 0.971 and 0.991, and for the size of the basket, precipitation in May (0.956) and July temperatures (0.943). The correlation coefficient with the sum of active temperatures is – 0.829 for plant height – 0.851 for basket diameter – 0.902 for the growing season.

scholarly journals The association between COVID-19 data and meteorological factors in Indonesia

2020 ◽  
Author(s):  
Supari ◽  
Danang Eko Nuryanto ◽  
Amsari Muzakir Setiawan ◽  
Ardhasena Sopaheluwakan ◽  
Furqon AlFahmi ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Relative Humidity ◽  
Meteorological Factors ◽  
Correlation Coefficients ◽  
Weather Conditions ◽  
Weather Data ◽  
Data Series ◽  
Distribution Analysis ◽  
Cumulative Number ◽  
Daily Data

Abstract On March 2, 2020, the first Coronavirus Disease (COVID-19) case was reported in Jakarta, Indonesia. One and half month later (15/05/2020), the cumulative number of infection cases was 16496 with a total of 1076 mortalities. This study is aimed to investigate the possible role of weather in the early cases of COVID-19 incidence in six selected cities in Indonesia. Daily data of temperature and relative humidity from weather stations nearby each city were collected during the period 3 March - 30 April 2020, together with data of COVID-19 cases. Correlation tests and regression analysis were performed to examine the association of those two data series. In addition, we analysed the distribution of COVID-19 with respect to weather data to estimate the effective range of weather data supporting COVID-19 incidence. Our results reveal that weather data is generally associated with COVID-19 incidence. The daily average temperature (T-ave) and relative humidity (RH) presents significant positive and negative correlation with COVID-19 data, respectively. However, the correlation coefficients are weak with the strongest correlations found at 5 day lag time i.e. 0.37 (-0.41) for T-ave (RH). The regression analysis consistently confirmed this relation. The distribution analysis reveals that the majority of COVID-19 cases in Indonesia occurred in the daily temperature range of 25-31oC and relative humidity of 74-92%. Our findings suggest that COVID-19 incidence in Indonesia has a weak association with weather conditions. Therefore, non-meteorological factors seem to play a larger role and should be given greater consideration in preventing the spread of COVID-19.

Influence of limiting factors of the growing season on the yield of early-maturing soybean varieties

2020 ◽  
Author(s):  
M.Е. Belyshkina ◽  
◽  
E.V. Gureyeva
Keyword(s):  
Growth And Development ◽  
Weather Conditions ◽  
Growing Season ◽  
Limiting Factors ◽  
Critical Periods ◽  
Ecological Adaptability ◽  
Early Maturing ◽  
Stable Yield ◽  
Heat And Moisture ◽  
Sum Of Active Temperatures

Soybean has an ecological adaptability due to the deep selectivity of this crop in relation to the specific features of the growing zone. At the same time, it makes increased demands on heat and moisture, especially during certain "critical" periods of growth and development. The lower threshold of active average daily temperatures is 15–17oC, and for full maturation of ultra-ripe and early-maturing varieties, the sum of active temperatures of 1700–2100oС is required. Assessment of the agro-climatic resources of the Ryazan region indicates the possibility of growing precocious soybean varieties here. The limiting indicator in some critical periods may be insufficient moisture. As a result of the conducted research, it was found that soybean varieties of the Northern ecotype are able to form a stable yield in the conditions of the Ryazan region. At the same time, the lesser response to changes in agroclimatic conditions was shown by the Kasatka variety, which showed the shortest growing season and yield at the level of 1.00 t / ha. The Georgiya variety reacted more than any other to changes in weather conditions, its yield was from 1.24 to 1.72 t/ha over the years of research.

scholarly journals Criteria for Abnormality Evaluation of Selected Weather Parameters in the Slovak Republic

2017 ◽  
Vol 63 (2) ◽  
pp. 86-91
Author(s):  
Martin Danilovič ◽  
Helena Hlavatá ◽  
Božena Šoltysová
Keyword(s):  
Air Temperature ◽  
Slovak Republic ◽  
Weather Conditions ◽  
Growing Season ◽  
Cultivated Plants ◽  
Limit Values ◽  
Temperature And Precipitation ◽  
Weather Parameters

Abstract The paper describes the procedure of calculation and assessment of deviations of the average air temperature from the normal (in relation to the normal 1961‒1990) or long-term average and the percentage of normal precipitation or long-term sum of precipitation, valid for the Slovak Republic. Three evaluation tables clearly indicate both threshold limit values, which facilitate the classification of the calculated indices for air temperature and precipitation. Criteria presented in this work are fully applicable for weather conditions evaluation during the growing season of cultivated plants in the Slovak Republic.

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