Unexpected Rain Research Articles

Aerial dispersal of Venturia inaequalis ascospores with under-canopy sprinkler irrigation for apple scab management

AbstractSprinkler irrigation systems can release ascospores of Venturia inaequalis, the cause of apple scab, from infected leaves on the ground under conditions unsuitable for infection, and thus reducing the primary inoculum. Under-canopy irrigation was carried out for two hours in the middle of the day over overwintered apple leaves heavily infected with scab, either in a wind-protected enclosure or in a wind-exposed orchard. Ascospores were captured with rotating-arm spore traps at heights ranging from 0.3 m to 3.0 m above the ground. Ascospores dispersed above the irrigated layer and were detected at all heights above the sprinklers. Wind played a critical role in spore transport, evident from the set-up where wind interference was minimised by a wind fence, resulting in higher airborne spore numbers across all measured heights compared with the orchard exposed to unrestricted wind conditions. Furthermore, vertical temperature gradients significantly correlated with spore distributions, particularly where negative gradients at heights between 0.3 m and 0.05 m and positive gradients at heights between 1.0 m and 0.3 m led to spore retention within the irrigated zone. The findings highlight that ascospores, dispersed above the irrigated layers, could settle on susceptible tissues. It thus becomes imperative to ensure a rain-free period of at least 24 h post-irrigation and, if a rainfall shortly occurs after irrigation, the application of curative fungicides becomes essential following unexpected rain. Reliable weather forecasts are therefore crucial in determining the effectiveness of under-canopy irrigation to reduce apple scab incidence.

Operational Risk Assessment for the Pollination Service with Apis mellifera Bees in Cashew Crops in Vichada, Colombia

The cashew tree relies heavily on the presence of pollinators during the peak receptivity of its flower to facilitate the transfer of pollen from the stamen to the stigma and ensure successful fruit production. Apis mellifera bees play a crucial role as intermediaries in the pollination process of the fruit, simultaneously extracting nectar and pollen from the flowers. The pollination service (PS) is susceptible to various risk factors that, if realized, could impact both the beekeeping industry and cashew production. This article aims to assess the operational risks associated with pollination service for Anacardium occidentale production in Vichada, Colombia, as a strategic measure to safeguard the business’s value. Drawing on expert opinions and relevant literature, nineteen risks were identified, encompassing threats such as fires, thefts, attacks by wild animals, unexpected rains, etc. Following the application of Failure Mode and Effects Analysis (FMEA), four risks were prioritized based on their severity and occurrence. Subsequently, Value at Risk (VaR) was employed for risk evaluation. The anticipated loss for the pollination service, resulting from these prioritized risks: 1, 9, 12 and 13, was quantified at $226674 ± $19096 per year for an 8000-hectare margin with a confidence level of 95%. The economic loss for 16000 hectares was $453348 ± $38192. This substantial value is of great significance to the beekeeping sector, translating to a loss of $27.3 per hectare per year and directly impacting the estimated $437824 loss in the cashew sector. Such losses have far-reaching consequences, affecting the livelihoods of peasant beekeepers in the region and potentially discouraging the maintenance of bee colonies and forests.

Crop Canopy: Empowering Crop Resilience with IoT-Driven Rain Shed Solution

India is known for its farming, which has been crucial for its economy. But recently, farming hasn't been doing as well because of unpredictable rain. When the monsoon doesn't behave as expected, it can seriously damage crops, causing farmers to lose a lot of their produce. Unseasonal rains can have significant effects on Post-Harvesting Activities and the quality of harvested agricultural products such as fruit and vegetable crops during different stages of growth and harvesting. Post-harvesting steps are crucial to preserving the quality and ensuring the safety of the harvested products before they reach consumers. After harvesting, drying the crops is essential for storing grains. However, around 70% of farmers use the old method of sun-drying, which becomes a problem when unexpected rain falls. Sometimes, farmers even get hurt or lose their crops due to thunderstorms and lightning. To mitigate these challenges and losses, we have proposed a project aimed at providing an innovative, cost-effective solution: a proper Automated Rain Shed System, which opens and closes to protect crops or plants from unwanted rains and enables remote monitoring of Automated Rain Shed Operations.

Clinical and Laboratory Profile of Leptospirosis in a Tertiary Care Hospital at Kolar

Introduction: Leptospirosis is an acute treponemal infection with high mortality and morbidity. Due to varied presentations in different geographical areas and unexpected seasonal patterns, clinical diagnosis is difficult. The present study aims to analyze the varied clinical presentations and epidemiological factors in correlation with laboratory diagnosis. Materials and Methods: A retrospective study was conducted among the clinically suspected cases of leptospirosis at R. L. Jalappa Hospital, Kolar, from January 2023 to December 2023. A total of 750 blood samples were tested for IgM ELISA leptospira test. All patient samples that tested positive for IgM antibodies were considered seropositive for Leptospira. The clinical history, laboratory parameters, management, course, and outcome of these patients were recorded. Results: The majority of the affected population were in the 41-60 year age group. Males were more affected than females. Due to unexpected rains, cases peaked in March. Thrombocytopenia was observed in 32 patients (34%), hyperbilirubinemia in 28 patients (30%), raised transaminases in 27 patients (29%), followed by low hemoglobin levels in 27 patients (28%). Severe acute respiratory illness (SARI) was the most common complication, seen in 24 patients (26%), followed by renal failure in 11 patients (12%). Conclusion: The morbidity and mortality due to leptospirosis can be reduced by better understanding environmental factors, by early detection through rapid tests, and predicting the severity of illness using laboratory parameters.

Development of Web-based Smart Monitoring System using IoT & Mobile Application for Grapes Drying Unit

IoT (Internet of Things) is one of the leading technologies that is used in many fields and departments. This IoT technology has made the working of systems easier and more hassle-free. This IoT is having tremendous usage and application in the agricultural fields making farmers’ life easier. This IoT technology is used for automation in the agricultural fields to monitor various parameters in real time, helping the farmers in yielding good crops. One such smart system used to safeguard raisins from the climatic changes has been proposed in this research. The drying of grapes requires specific temperature and humidity to be maintained to attain good yield. There is always a possibility of sudden unexpected rains, and it would be difficult for the people to close the sheds of such large drying units and also it is a time-consuming process. In such cases, this model is used where the sheds automatically get closed with the help of the motors and input from the rainfall sensor. Also, additional features such as flame alarm and buzzer module, which help in detecting the fire and informing the farmer about the danger to take immediate action, are used. All these controlling and monitoring are done by making use of the IoT technology and the WSN.

IoT-based Sun and Rain Detection System

The field of IoT has made significant advancements by using software and sensors to collect and share data about device usage and the surrounding environment. This data analysis can be used to identify potential problems before they occur and provide solutions. This technology is applicable to various industries, including healthcare, automation, and wearable technology. Our research shows that there is a correlation between atmospheric pressure, humidity, and rain. To address the issue of people getting caught in unexpected rain, we have used the Bosch BMP280 environment monitor to predict rain and high temperatures. By measuring temperature, atmospheric pressure, and altitude and using an IoT interface with a Magnetic switch sensor, we record and transfer the data to Firebase. We notify the user with a beep if they need to carry an umbrella.

Spatio-temporal Variability and Trends in Rainfall and Temperature in Anger watershed, Southwestern Ethiopia

Insights to broadly argued research gap on lack of climate studies at micro-scale considering unique features of an area, this paper intended to examine agro-ecological level spatio-temporal trends and variability in rainfall and temperature in Anger watershed of southwestern Ethiopia. The gridded data managed by the Ethiopia National Meteorological Services Agency (NMSA) for 1983-2018 were used. The Mann-Kendall test for trend analysis and different variability measures were used. Questionnaire and FGD data on community perceptions gathered from 214 households and elders were analysed descriptively and qualitatively. The study reveals the consistent increasing trends in temperature; and high variability and insignificant but increasing rainfall trend. The trends and variability show spatio-temporal differences along agro-ecologies. The watershed is characterized by moderate to high rainfall coefficient of variations, significant years of high rainfall concentration, and considerable negative annual rainfall anomalies; that the variability was severe in woinadega followed by kolla agro-ecology. Although, the perceptions on trends, variability and its implications show difference across agro-ecology, the propensity to increased temperature, unclear rainfall trend and significant inter-annual and seasonal variability were witnessed. Unpredictability of rainfall time, concentrations in kiremt, and unexpected rain during harvesting was major challenges resulting multifaceted impacts on the small-scale farmers’ livelihoods.

Economic Assessment of Climate Adaptation Options in Myanmar Rice-Based Farming System

Agriculture is highly sensitive to climate change and understandings how the adaptation options improve the farming household’s adaptive capacity are critical to the agricultural policies. The study was carried out for the economic assessment of climate adaption options in rice-based farming system of Myanmar. The propensity score matching approach was applied to explore the existing adaptation options and its contribution on the farm income. In addition, the binary probit model was used to analyse the factors influencing those adaptation decisions. The erratic rainfall, especially dry spell period and unexpected rain during the critical crop growth, was the critical challenge of rice-based farming in the study. The timely operation of farm machineries was one of the major adaptation options for the farmers, followed by other options such as use of more agrochemicals and changing rice varieties including early maturity, high yielding and stress tolerant varieties. The combination of those adaptations gave additional 0.86-0.89 ton/ha yield, 152-158 USD/ha total return and 108-124 USD/ha profit to the adapter farmers. The institutional factors such as irrigation access, access to credit, access to weekly weather information and participation to agricultural training were critically important to the adaptation decision. Moreover, the social capital factors like farming experience, farm size and farm income share were also major influencing variables.

A Tensor-Based Low-Rank Model for Single-Image Rain Streaks Removal

Images were taken in rainy weather always contain unexpected rain streaks, which severely affect the subsequent image processing procedures in outdoor vision systems. Removing rain streaks from a single image is a challenging task and recently has been investigated extensively. In this paper, we propose a novel tensor-based low-rank model for removing rain streaks from a single rainy image. Our method fully exploits the similar repeated patterns and directional smoothness of rain streaks. Different from the existing matrix-based methods, we stack the rain patches to construct a three-order tensor and characterize the similarity and repeated patterns by considering the low-rankness in tensor form. We further regularize the low-rankness by the efficient tensor nuclear norm (TNN) so that the intrinsic spatial structures of rain streaks can be preserved. Moreover, two unidirectional total variation terms are employed to depict the directional smoothness of rain streaks and the rain-free image. The sparsity of rain streaks is also enhanced by an l 1 norm. We develop an efficient alternating direction method of multipliers (ADMM) to tackle the proposed model. The experimental results on synthetic and real-world rain images show that our method outperforms the state-of-the-art methods quantitatively and visually.

Growth Behavior of Coleus (Plectranthus scutellarioides L.) Cuttings In Relation To Light Emitting Diodes (LED) Intensities

Background: Coleus is a perennial herbaceous foliage plant belongs to the family Lamiaceae with long history of medicinal and food uses. Coleus plant have reputed medicinal uses, which includes anti-aggregate, anticancer, antidepressant, antidiuretic, antiglaucomic, antimetastatic, antispasmodic, bronchodilator, bronchospasmolytic, cardiotonic. Hypothesis: Harsh environmental conditions including irregular temperature, unexpected rains and natural calamities have made the production of ornamental plants difficult. Therefore, coleus plants were cultivated under LED intensities to make its availability possible under harsh environmental conditions. Study site and dates: The study was carried out during Feb-May (summer) 2017 at Horticulture Garden, Sindh Agriculture University Tandojam, Sindh, Pakistan. Methods: Vegetative as well as chlorophyll contents were measured using different plant observations in plants grown under different light intensities. Some parameters of economic importance were studied which included: Sprouts cutting-1, sprouting index (SI), plant height (cm), branches per plant, leaves per plant, leaf length (cm), leaf width (cm), leaf area (cm2), single leaf weight (g), chlorophyll content (SPAD) and root length (cm). Results: Growth of coleus varieties were significantly (P<0.05) affected by various LED intensities. The two coleus varieties treated with 1204 μmol. m-2 S-1 produced maximum 3.08 sprouts cutting-1, 0.30 sprouting index, 14.60 cm plant height, 5.05 branches plant-1, 10.23 leaves plant-1, 11.39 cm leaf length, 8.88 cm leaf width, 101.20 cm2 leaf area, 1.75 g single leaf weight, 27.51 chlorophyll content (SPAD) and 9.37 cm root length. However, minimum coleus varietal performance was observed under low light intensity (LI1= 301 μmol m-2 s-1) having 1.08 sprouts, 0.10 sprouting index, 6.58 cm plant height, 1.05 branches, 2.27 leaves, 2.99 cm leaf length, 1.83 cm leaf width, 5.55 cm2 leaf area, 0.28 g single leaf weight, 10.41 chlorophyll content (SPAD) and 4.66 cm root length. Conclusions: Growth of coleus plant increased simultaneously with increasing LED light intensities. 1204 μmol m-2 s-1 resulted in maximum growth of coleus. In case of varieties, “Coleus Brown” resulted in significantly maximum vegetative and flowering traits as compared to variety “Coleus Fairway Rose”.

Sequential quadratic programming and analytic hierarchy process for nonlinear multiobjective optimization of a hydropower network

AbstractIn this paper, an optimal annual scheduling for power generation (i.e. rule curves and volume of water releases) in serial or parallel hydropower plants is developed. Multiobjective programming and weighted sum method are used to convert a multiobjective problem to a single objective one. Furthermore, to obtain viable alternatives under existing uncertainty, some random weight vectors in the whole weighting space are generated and for each weight vector an optimal solution is found using sequential quadratic programming (SQP). Then, analytic hierarchy process (AHP) is used to select the best solution according to a given criterion, and determine the most preferred one. Besides, this method does not require choosing a priori preference for the objective function, thus making an ideal tool for handling complicated multiobjective models and easy to use with the aid of computer programs. Combination of multiobjective optimization and multicriteria decision analysis (MCDA) is an integrated methodology that is capable of dealing with complex water management problems. Various scenarios for dry, median, and wet years are assumed based on stochastic flows from external sources (e.g. flooding rivers, unexpected rains, etc.) coming into each reservoir, and turbine power generation is obtained from hill diagrams provided by the manufacturer. The application of this methodology is illustrated in a case study for optimal scheduling of Karoon River Basin, where the decision support system and optimization routines are implemented in MATLAB. The total energy productions for 10 optimized solutions under dry, median, and wet scenarios (generated from forty‐year historical inflow records) are calculated, and specific water consumption for each reservoir is obtained in different months. This can significantly help decision makers to have an optimal and more intelligent management over energy productions in hydropower plants and associated thermal power plants. Copyright © 2009 John Wiley &amp; Sons, Ltd.

Breeding activity patterns, reproductive modes, and habitat use by anurans (Amphibia) in a seasonal environment in the Pantanal, Brazil

AbstractAnnual patterns of breeding activity, reproductive modes, and habitat use are described for a frog community in a seasonal environment, in the southern Pantanal, Mato Grosso do Sul, Brazil. Data were collected monthly between January 1995 and December 1998. A total of 24 species from four families; Bufonidae (3 species), Hylidae (10 species), Leptodactylidae (9 species), and Microhylidae (2 species) were registered. Three reproductive activity patterns are recognized among these species: continuous, explosive, and prolonged; 50% of the species were explosive breeders. Seasonal pattern of reproduction was verified for three analyzed years (1995-1997); most species reproduced during the rainy season (Nov-Jan). The reproduction was aseasonal in 1998; unexpected rains in the dry season lead to an unusual breeding activity. Five reproductive modes were noted — 62.5% of the species have the generalized aquatic mode, and 33.3% deposit eggs embedded in foam nests. Many species used the same sites for reproduction, although temporal partitioning and calling site segregation was observed. The occurrence of many species that exhibit explosive breeding early in the rainy season is common in seasonal and open environments with variable and unpredictable rainfall, as is the case in the Pantanal.