Influence Of Weather Variables Research Articles

Influence of weather variables on the host range and population dynamics of guava spiralling whitefly (Aleurodicus dispersus Russell) in Tiruchirappalli district of Tamil Nadu, India

Influence of weather variables on the host range and population dynamics of guava spiralling whitefly (Aleurodicus dispersus Russell) in Tiruchirappalli district of Tamil Nadu, India

Influence of Weather Variability on the growth and Development of Wheat Crop: A Review

Influence of Weather Variability on the growth and Development of Wheat Crop: A Review

Evaluation of sorghum genotypes and influence of weather variables on anthracnose (Colletotrichum sublineolum) disease development under field conditions at Jimma, southwestern Ethiopia

The severity and temporal dynamics of sorghum anthracnose on six and nine sorghum genotypes were evaluated on field plots during 2014 and 2015 cropping years in Southwestern Ethiopia, respectively. Anthracnose severity was assessed as the proportion of leaf area affected by the disease. 12 consecutive time point anthracnose severity assessments and their mean severity, disease progress rate, AUDPC, grain yield and yield related components were used to evaluate the response of the genotypes. In the year 2014 and 2015, the mean anthracnose severity was varying from 65 to 79 PSI and 54–82 PSI among six and nine sorghum genotypes, respectively. AUDPC varied from 5063 to 6113%-day and 4171 to 6383%-day in the year 2014 and 2015, respectively. BRC-378 and BRC-245 genotypes consistently had the lowest disease levels and highest grain yields during the two experimental years. The disease pressure was reduced, whereas grain yield and 1000-seed weight of the genotypes were increased in 2015 cropping year. Anthracnose severity was strongly correlated with weather variables and showed strong negative associations with grain yield of all tested sorghum genotypes.

Influence of weather variables on cattle diseases in Ranchi, Jharkhand

Influence of weather variables on cattle diseases in Ranchi, Jharkhand

Influence of weather variables on the incidence and development of rice leaf blast (Magnaporthe oryzae)​

Rice is the second largest grown cereal crop in the world and the most consumed main staple meal. The devastating nature of rice blast disease has resulted in large annual losses. Therefore, a pot experiment was conducted at Paddy Breeding Station, Tamil Nadu Agricultural University, Coimbatore, during Rabi seasons of 2018-19, 2019-20, 2020-21, and 2021-22, with the objective to investigate the possible role of weather variables on rice leaf blast. Research analysis performed through correlation and decision tree analysis was carried under R studio to study the relation between weather parameters and per cent disease index (PDI) of leaf blast. The results revealed that, morning dew point temperature (X4, r = 0.69** and 0.67**) and minimum temperature (X2, r = 0.68** and 0.65**) had higher negative correlation both in real time and in one week lead time (LT1W) respectively. Further, the decision tree analysis showed the combination of rainfall of 5.9 mm and minimum temperature less than 22.6 ºC helped achieve disease incidence of greater than 80 per cent. Thus, the occurrence and development of leaf blast are significantly influenced by the minimum temperature and dew point temperature with drizzling rainfall, and these weather variables can be employed for weather-based disease forewarning against rice leaf blast.

Wavelet Decomposition and Machine Learning Technique for Predicting Occurrence of Spiders in Pigeon Pea

Influence of weather variables on occurrence of spiders in pigeon pea across locations of seven agro-climatic zones of India was studied in addition to development of forecast models with their comparisons on performance. Considering the non-normal and nonlinear nature of time series data of spiders, non-parametric techniques were applied with developed algorithm based on combinations of wavelet–regression and wavelet–artificial neural network (ANN) models. Haar wavelet filter decomposed each of the series to extract the actual signal from the noisy data. Prediction accuracy of developed models, viz., multiple regression, wavelet–regression, and wavelet–ANN, tested using root mean square error (RMSE) and mean absolute percentage error (MAPE), indicated better performance of wavelet–ANN model. Diebold Mariano (DM) test also confirmed that the prediction accuracy of wavelet–ANN model, and hence its use to forecast spiders in conjunction with the values of pest–defender ratios, would not only reduce insecticidal sprays, but also add ecological and economic value to the integrated pest management of insects of pigeon pea.

Influence of weather variables on whitefly population build-up and progression of okra yellow vein mosaic virus disease

Influence of weather variables on whitefly population build-up and progression of okra yellow vein mosaic virus disease

Influence of weather variability on nut yield of cashew under Bastar region of Chhattisgarh

Influence of weather variability on nut yield of cashew under Bastar region of Chhattisgarh

Influence of weather variables on the development of pearl millet downy mildew

The present study was undertaken during 2016 to 2018 to find out the effect of different weather variables on the initiation and development of downy mildew in pearl millet in Punjab. The maximum temperature ranged from 32.8ºC to 36.9ºC and minimum temperature ranged from 17.2ºC to 27.8ºC during the crop season. The correlation analysis showed significant negative correlation of maximum temperature (r = -0.665*), minimum temperature (r = -0.776**), wind speed (r = -0.898**), rainfall (r = -0.625**) and non-significant negative correlation of evening relative humidity (r = -0.523) with downy mildew incidence. The positive correlation with morning relative humidity (r = 0.871**) was significant and sunshine hours (r = 0.321) were non-significant with per cent disease incidence. A multiple regression model was developed using two years (2016 and 2017) data to predict the occurrence of downy mildew with R2 = 0.981, indicating that all weather parameters contributed 98.1 per cent towards disease development. The model was validated with 2018 data which shows that equation can be used in the disease forecasting for taking timely actions for control measures.

Influence of weather variables on progression of white rust disease of Indian mustard

Influence of weather variables on progression of white rust disease of Indian mustard

Weather Variables Affecting the Behaviour of Insect Flower Visitors and Main Pollinators of Erythroxylum myrsinites Martius (Erythroxylaceae)

Basic research assessing environmental effects on entire pollinator communities are still uncommon, particularly for rare and commercially unattractive plant-pollinator partners. We investigated the community of flower visitors of Erythroxylum myrsinites to check for potential pollinators and to check the extent of weather influence of visitor behaviour, registered as the number of visitors attending flowers of E. myrsinites. We then calculated species’ dominance and constancy and assessed location of pollen attachment in each visitor’s body. We correlated weather variables with the composition and abundance of visits carried out by the entire community and by most constant and dominant species. The wasps Polybia sericea, P. ignobilis and P. fastidiosuscula showed the highest values of constancy, dominance and attached pollen. There was a community-level effect of atmospheric pressure, solar radiation and wind speed on the number of visits. Atmospheric pressure affected the number of visits of eudominant species P. fastidiosuscula and P. sericea, while solar radiation affected the number of visits of P. ignobilis. Our results demonstrate the influence of weather variables on flower visiting insects and suggest the importance of native wasps in pollen transport and pollination, a relationship that should be further studied under the worldwide bee pollination decline.

Influence of weather variables on spore biology of Corynespora cassiicola, an incitant of target leaf spot disease of tomato

Among the various biotic and abiotic factors limiting production of tomato, target leaf spot disease caused by Corynespora cassiicola has been emerged as a serious problem in vegetable based cropping systems. In the current research work, the influence of varying environmental conditions including temperature, light, and relative humidity on conidial germination (CG), germ tube elongation (GTE) and sporulation (SP) of C. cassiicola was studied under controlled conditions. The temperature of 25 °C was most congenial for CG and GTE both under light and darkness conditions. The temperature range of 25 °C–30 °C was optimum for CG. Conidial germination increased progressively from 15 to 25 °C both under light and dark conditions and decreased with further increase in temperature. High rate of CG was observed under continuous darkness in comparison to continuous light irrespective of temperature. Lesser duration of light had a stimulatory influence on SP of C. cassiicola and 10 h light/14 h dark cycle at 25 °C temperature was most optimum for SP. Relative humidity (RH) at 95% was optimum for CG, GTE and SP and thus, justified the peak occurrence of the target leaf spot disease during 50-4 Standard meteorological week (SMW). Comparatively higher level of CG was obtained at the humidity range of 95%–100% with the best at 100% RH (92.6%). Increasing humidity significantly decreased the time of spore production. Maximum time required for spore production (69.2 h) was observed at 85% RH followed by 95% RH (50.2 h).

Soybean Rust Epidemics as Affected by Weather Conditions in Brazil

The soybean rust (SBR) epidemics are often triggered by weather conditions, which interfere actively on the disease progress. Therefore, weather variables can be used to estimate the risk of occurrence and severity of SBR outbreaks. This research aimed to determine the influence of weather variables on SBR progress in different field trials in Brazil. Field experiments were conducted during 2014-15 and 2015-16 soybean growing seasons in Piracicaba (SP), Ponta Grossa (PR), Campo Verde (MT) and Pedra Preta (MT). For all sites and seasons, a susceptible soybean cultivar was drilled with 0.45 m row spacing and 12 plants per linear meter. No fungicide sprays were applied to ensure natural disease occurrence. In order to create different environmental conditions, sequential sowing dates, of roughly 30-day intervals were carried out. In Piracicaba, Ponta Grossa, Campo Verde, and Pedra Preta the main weather variables influencing SBR were leaf wetness duration - LWD (R = 0.340), air temperature during LWD (R = 0.313), and cumulative rainfall (R = 0.304). The final severity was assessed only at Piracicaba and Ponta Grossa, and it was mainly influenced by LWD (R = 0.643). It is possible to conclude that epidemics of SBR were mainly influenced by leaf wetness duration, accumulated rainfall and air temperature during the LWD. Therefore, future researches aiming to develop a disease warning system for SBR should include the cumulative rainfall, LWD and the air temperature during LWD, together or individually, as inputs.

Comparing the effects of climate and land use on surface water quality using future watershed scenarios.

Eutrophication of freshwaters occurs in watersheds with excessive pollution of phosphorus (P). Factors that affect P cycling and transport, including climate and land use, are changing rapidly and can have legacy effects, making future freshwater quality uncertain. Focusing on the Yahara Watershed (YW) of southern Wisconsin, USA, an intensive agricultural landscape, we explored the relative influence of land use and climate on three indicators of water quality over a span of 57 years (2014-2070). The indicators included watershed-averaged P yield from the land surface, direct drainage P loads to a lake, and average summertime lake P concentration. Using biophysical model simulations of future watershed scenarios, we found that climate exerted a stronger influence than land use on all three indicators, yet land use had an important role in influencing long term outcomes for each. Variations in P yield due to land use exceeded those due to climate in 36 of 57 years, whereas variations in load and lake total P concentration due to climate exceeded those due to land use in 54 of 57 years, and 52 of 57 years, respectively. The effect of land use was thus strongest for P yield off the landscape and attenuated in the stream and lake aquatic systems where the influence of weather variability was greater. Overall these findings underscore the dominant role of climate in driving inter-annual nutrient fluxes within the hydrologic network and suggest a challenge for land use to influence water quality within streams and lakes over timescales less than a decade. Over longer timescales, reducing applications of P throughout the watershed was an effective management strategy under all four climates investigated, even during decades with wetter conditions and more frequent extreme precipitation events.

Influence of weather variables on atmospheric refractivity over Auchi Town, Edo State, Nigeria

In this study, atmospheric variables such as air temperature, relative humidity and atmospheric pressure were evaluated in order to determine the atmospheric refractivity over Auchi town in Edo State, Nigeria using a portable weather monitoring system. The data revealed that, the average atmospheric refractivity was 354.31 N-units. It was observed that air temperature, relative humidity and atmospheric pressure were having significant influence on the atmospheric refractivity during all the months in 2017. This influence was much during the months with higher rainfall (wet season), than the months with lesser rainfall (dry season). The air temperature was having the higher influence compared to that of the relative humidity and the atmospheric pressure. This study will assist the management of radio communication systems for enhancement and improvement purposes.Keywords: Refractivity; Troposphere; Propagation; Variation; Weather Variables

Temporal Abundance of Agave Weevil,Scyphophorus acupunctatus, and Two Species ofHololeptainAgave inaequidens

The influence of weather variables on temporal distribution of Scyphophorus acupunctatus Gyllenhal, 1838, Hololepta sp., and Hololepta yucateca Marseul, 1853 in Agave inaequidens Koch was analyzed. We evaluated the preference of the species for decomposed A. inaequidens or decaying squid. Carrion traps were used to collect and samples directly from agave plants for 7 months. Abundance of Hololepta sp. was conspecific with abundance of agave weevil. Temperature (rho = >-0.41 and <0.15) and humidity (rho = <0.39) were not correlated with phenology of the species.

Vegetation Development in a Tidal Marsh Restoration Project during a Historic Drought: A Remote Sensing Approach

Tidal wetland restoration efforts can be challenging to monitor in the field due to unstable local conditions and poor site access. However, understanding how restored systems evolve over time is essential for future management of their ecological benefits, many of which are related to vegetation dynamics. Physical attributes such as elevation and distance to channel play crucial roles in governing vegetation expansion in developing tidal wetlands. However, in Mediterranean ecosystems, drought years, wet years and their resulting influence on salinity levels may also play a crucial role in determining the trajectory of restoration projects, but the influence of weather variability on restoration outcomes is not well understood. Here, we use object-based image analysis (OBIA) and change analysis of the high-resolution IKONOS and WorldView-2 satellite imagery to explore whether mean annual rates of change from mudflat to vegetation are lower during drought years with higher salinity (2011-2015) compared to years with lower salinity (2009-2011) at a developing restoration site in California’s San Francisco Bay. We found that vegetation increased at a mean rate of 1979 m2/year during California’s historic drought, 10.4 times slower than the rate of 20580 m2/year between 2009 and 2011 when the state was not in drought. Vegetation was significantly concentrated in areas in closer to channel edges, where salinity stress is ameliorated, and the magnitude of the effect increased in the 2015 image. In our image analysis, we found that different distributions of water, mud and algae between years led to different segmentation settings for each set of images, highlighting the need for more robust and reproducible OBIA strategies in complex wetlands. Our results demonstrate that adaptive monitoring efforts in variable climates should take into account the influence of weather on tidal wetland ecosystems, and that high-resolution remote sensing can be an effective means of assessing these dynamics.

Temporal Variations in N2O Emissions in Maize and Wheat Crop Seasons: Impact of N-Fertilization, Crop Growth, and Weather Variables

ABSTRACTNitrous oxide (N2O) emission from agricultural soils is one of the important contributors to global greenhouse gas (GHG) emissions. The impact of crop growth and weather variables on N2O emissions during maize (Zea mays L.) and wheat (Triticumaestivum L.) crop seasons in unfertilized soils (TC) and N (nitrogen) fertilized soils (TN) was studied in a field experiment in Punjab, India. The fluxes were measured via closed chambers and a gas chromatography. In the maize crop season, N2O fluxes in TC ranged from 11.1 to 61.2 N2O-N g ha−1day−1, and in TN ranged from 10.3 to 129.2 N2O-N g ha−1day−1, respectively, whereas in the wheat crop season fluxes were comparatively lower, and they ranged from 3.3 to 21.2 N2O-N g ha−1day−1 in TC and from 4.8 to 44.4 N2O-N g ha−1day−1 in TN. More than 60% of total season emissions occurred during vegetative growth stages of both the crops. N2O fluxes in both crop seasons were mainly controlled by rainfall, but the impact was marked in the maize season. Additionally, the impact of fertilizer-N application on N2O fluxes was also evident as in TN the influence of weather variables on fluxes was less by 40% than in TC. The study suggested that N2O emissions could be large during vegetative growth stages if rainfall or irrigation events coincide with N-fertilization.

The effect of weather variables on the White Stork (Ciconia ciconia) spring migration phenology

The influence of weather variables on bird migration is widely recognised as birds have been found to adjust their migration phenology under the influence of weather conditions. This is of particular interest in relation to global climate change. We investigated the long-term (1961–2000) first arrival dates (FAD) of White Storks at their breeding grounds in Lithuania and their relationship with local and regional weather variables. The return of White Storks to their breeding grounds was advanced by almost 5 days during the study period. We found that the arrival time was most strongly influenced by temperature conditions along the migration route in south-eastern Europe as well as at breeding grounds, as warmer temperatures in these areas resulted in earlier arrival of birds. Interestingly, the return of White Storks was closely associated with the onset of the 3°C thermal season – the date when the mean daily air temperature permanently exceeds 3°C. However, in very warm years birds did not return to their breeding grounds as early as would have been expected from temperature alone, suggesting that other factors limit the further advancement of FADs. We suggest that local weather conditions, particularly the air temperature during the final stages of the spring migration, have a more pronounced effect on the arrival dates of White Storks at their breeding grounds than regional climatic phenomena (North Atlantic Oscillation or Indian Ocean Dipole).

Influence of weather variables on physical activity assessed by accelerometry across age and gender groups

The purpose of this research was to study the effects of weather on physical activity and compliance to minimum physical activity recommendations. Participants included 257 women and 178 men. Time spent in physical activity, average daily steps, and weather variables were gathered and analysed to explore the influence of weather on PA and compliance with the PA recommendations. In result, environmental factors may have a weak influence in an individual will to engage in PA, and individuals highly committed to an active lifestyle (based on the number of steps taken per day) did not seem to be influenced by any of the weather variables. To conclude, considering the known barriers to an active lifestyle, this information is markedly important since engaging in physical activity on a day-to-day basis may be of extreme relevance to the maintenance of a healthy status, especially in the elderly.