Sunshine Hours Research Articles

Solar Irradiance Prediction Method for PV Power Supply System of Mobile Sprinkler Machine Using WOA-XGBoost Model

Solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to estimate the solar irradiance of typical irrigation areas. The relation between meteorological parameters and solar irradiance is studied, and four different parameter combinations are formed and considered as inputs to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as input parameters. In the model testing, the RMSE and MAE of WOA-XGBoost are 2.142 MJ·m−2·d−1 and 1.531 MJ·m−2·d−1, respectively, while those of XGBoost are 2.298 MJ·m−2·d−1 and 1.598 MJ·m−2·d−1. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model. The model developed in this study can be applied to forecast solar irradiance in different regions. By inputting the meteorological parameter data specific to a given area, this model can effectively produce accurate solar irradiance predictions for that region. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines.

Seasonal Incidence of Sucking Pests and Their Natural Enemies on Moth Bean [Vigna aconitifolia(Jacq.) Marechal

A field experiment was conducted at the College of Agriculture, NAU, Bharuch (Gujarat) to study the seasonal incidence of sucking pests and their natural enemies and their correlation with weather parameters on moth bean during kharif -2023. The studies on seasonal incidence indicated that jassid infestation began in the 1st week of August (31st SMW) and peaked during the 1st week of September (35th SMW). Whitefly infestation also began in the 1st week of August (31st SMW) achieved its peak during 2nd week of September (36th SMW). The population of thripscommenced from 1st week of August (31st SMW) reached its peak during2nd week of September (36th SMW). The population of ladybird beetle appeared from 2nd week of August (32th SMW) and reached its peak during 2nd week of September (36th SMW). The population of chrysoperla appeared from 2nd week of August(32nd SMW) and reached its peak population during 2nd week of September (36th SMW). Among the different environmental factors, morning relative humidity had a significant positive impact on the jassid and whitefly population. Bright sunshine hours showed significant positive influence on thrips and whitefly population. However no significant correlation was observed between ladybird beetle and Chrysoperla population with weather parameters.

Extended Failure Mode and Effects Analysis for Development of Hot Desert Test Cycle Proposal

ABSTRACTA growing number of gigawatt‐scale photovoltaic (PV) power plants are being established in hot desert regions worldwide, which are favored for their vast available land, high solar irradiance, long sunshine hours, and relatively low maintenance needs. This study combines insights from global PV experts on degradation rates, failure mode and effects analysis (FMEA), and desert weather conditions to develop a hot desert test cycle (HDTC). The average degradation rate for PV modules installed in hot desert regions over the past 10 years is estimated to be around 1.63% per year. Eighteen failure modes were identified and analyzed using FMEA. According to the results, the main degradation mechanisms include UV light‐induced degradation (UVLID), thermomechanical failures in interconnects and fingers, light‐elevated temperature‐induced degradation (LeTID), and abrasion of the glass and antireflection coatings. A radar map comparison shows that desert environments experience UV exposure, ambient, and module temperatures that are more than twice as high as those in moderate climates. The HDTC protocol was developed based on FMEA results and desert‐specific weather conditions. It includes tests for desert UV exposure, temperature cycles, mechanical loads, and sand/brush abrasions. To ensure consistency across countries, there is a plan to establish an internationally recognized standard that complements existing IEC standards. As the industry grows, desert regions are expected to place greater emphasis on adopting desert‐specific testing standards for the qualification and evaluation of PV modules.

Effects of Temperature, Precipitation, and Sunshine on Cold-Tolerant Wheat Yield Under Warming Trends: A 20-Year Study in Hokkaido, Japan

To clarify the adaptation strategies of cold-tolerant wheat against global warming, this study examined the effects of daily temperature, precipitation, and sunshine duration on wheat yield in Hokkaido, Japan, over 13 years (2011–2023). Yield components were also analyzed over 20 years (2004–2023). The number of snow-cover days decreased by about 24 days over the 20-year period. As a result, the growth of overwintered wheat accelerated, with the heading and maturity of plants advancing by about 8 and 5 days, respectively, and the grain-filling period extending from about 44 to about 48 days. Multiple regression analysis was conducted using wheat yield as the objective variable and weather conditions as explanatory variables. Three weather conditions were selected: precipitation for 8 days from 27 March, sunshine hours for 8 days from 21 March, and sunshine hours for 12 days from 13 June, which yielded a coefficient of determination of 0.953. Despite the highest mean summer temperatures on record being registered in 2023, high yields were ensured by the number of sunshine hours, which were approximately 1.5 times the normally recorded hours. This highlights the importance of this parameter in mitigating the impact of high summer temperatures.

High prevalence and seasonal Patterns of vitamin D deficiency in children and adolescents in central China: A Three-Year Single-Center study

ObjectiveThis study aimed to determine the prevalence and associated factors of vitamin D deficiency and insufficiency in children and adolescents in Central China. MethodsIn total, 8,248 children and adolescents aged 0–18 years at a children’s hospital from January 2019 to February 2022, were recruited. Their serum vitamin D levels were measured, and monthly meteorological and air pollution data were collected. ResultsThe overall mean serum vitamin D level was 37.7 ± 17.7 ng/mL, and the prevalence of vitamin D deficiency and insufficiency was 17.7 % and 23.4 %, respectively. Children aged 13–18 years had the highest vitamin D deficiency rate (64.1 %) and the lowest sufficiency rate (4.8 %). The incidence of vitamin D deficiency in girls, especially those aged 6–13 years and 13–18 years, was higher compared to boys. The highest prevalence of vitamin D deficiency was observed in winter (23.2 %), whereas the lowest was found in autumn (12.0 %). Vitamin D insufficiency was most prevalent in summer (27.0 %), significantly higher than in other seasons. Girls were more prone than boys to vitamin D deficiency in spring and summer. Stepwise multiple linear regression analysis showed a positive correlation between vitamin D levels, nitrogen dioxide concentrations, and sunshine hours and a negative correlation with particulate matter 2.5 (PM2.5). ConclusionOur study found high vitamin D deficiency among children in central China, especially girls aged 13–18. Strategies should include promoting sunlight, reducing air pollution, and considering supplementation, particularly in spring and summer.

Central-European sunshine hours, relationship with the Atlantic Multidecadal Oscillation, and forecast

Sunshine hours (SSH) is an important meteorological parameter, loosely linked to temperature and precipitation, and highly relevant for various sectors such as agriculture or solar energy. Previous studies have already identified a correlation of European SSH with the thermal state of the North Atlantic. This paper investigates this relationship further by studying annual and monthly SSH of seven long-term Central European SSH series and comparing them to the Atlantic Multidecadal Oscillation (AMO) using Fourier Transformation, Monte Carlo simulation and non-linear optimization. The Fourier spectra of our annual SSH series have their strongest and highly significant peaks in the known AMO period of ~ 50 to ~ 80 years, supporting the hypothesis that European SSH and the AMO are linked. The optimized sinusoids of the seven SSH and the AMO series with these periods show substantial correlations with the corresponding data (r = 0.42–0.55 for SSH and 0.71 for the AMO). Extrapolating the sinusoids, we project a gradual decline in SSH across Central Europe by 9–16% from its current maximum over the next three decades, particularly pronounced in northern regions.

Impacts of nitrogen (N), phosphorus (P), and potassium (K) fertilizers on maize yields, nutrient use efficiency, and soil nutrient balance: Insights from a long-term diverse NPK omission experiment in the North China Plain

Context or problemSoil nutrient deficiency is one of the significant challenges in grain production, particularly nitrogen (N), phosphorus (P), and potassium (K). These deficiencies not only reduce crop yields but also cause associated environmental issues, such as soil structure deterioration and ecosystem services diminution. ObjectivesThis research aimed to investigate the long-term effects of NPK fertilizers on soil nutrient properties and maize phenology, further on the grain yield, and to evaluate the nutrient use efficiency and soil nutrient balance under different fertilization managements. MethodsA long-term field experiment was initiated in 1990 in a summer maize field in the North China Plain, including five fertilizer treatments: CK (control), NP, NK, PK, and NPK. The soil nutrient properties, maize yields, crop nutrient uptake amount, nutrient recovery efficiency (NRE), nutrient harvest index (NHI), and soil nutrient balance were annually evaluated from 2005 to 2022. ResultsSignificant improvements in maize yields were found under NPK (9081 kg ha−1), NP (6426 kg ha−1), and PK (2668 kg ha−1) compared with CK (1809 kg ha−1) and NK (1656 kg ha−1). The yield increase was mainly attributed to: (1) enhancing in soil nutrient properties, such as soil organic carbon, soil total N (TN), available N (AN), total P (TP), available P (AP), and available K (AK), and (2) the shortened vegetative period, leading to greater sunshine hours (SH) and accumulative growing degree days (GDD) during the reproductive period. Furthermore, a random forest analysis quantified their importance to grain yield, showing that the edaphic factors (mainly SOC, TN, AK, AN, TP, AP, C:N, and N:P) explained a much greater proportion of yield variation compared with phenological factors (mainly GDD during tasseling and physiological maturity stages, and SH during tasseling stage). Additionally, the significantly higher response ratio of both N and P to NRE and NHI implied that N and P fertilizers having a more pronounced impact on improving nutrient use efficiency than K fertilizer. In terms of soil nutrient balance, a most relative soil nutrient balance was detected under NPK treatment, avoiding either substantial nutrient depletion or accumulation under any nutrient deficiency conditions. ConclusionsSoil deficiencies in N and P had more severe impacts on maize yields and nutrient use efficiency compared with K deficiency. Additionally, a balanced NPK fertilizer regime effectively managed soil nutrient balance. Implications or significanceThese findings elucidate the roles of N, P, and K fertilizers in maize production and soil nutrient conditions from a long-term field experiment, which could provide valuable insights for optimizing fertilization management strategies.

Construction of a comprehensive meteorological risk index for wheat Fusarium head blight prediction based on more than a half-century of monitoring data.

Fusarium head blight (FHB) represents a critical threat to wheat production globally, not only reducing yields but also contaminating crops with harmful mycotoxins. This study aimed to elucidate new spatiotemporal patterns of FHB incidence and to develop a comprehensive meteorological risk index to enhance scientific prevention and control of the disease. Through the analysis of annual and decadal variations from 1965 to 2023, the study assessed FHB trends across four agricultural regions (I, II, III, and IV) in Jiangsu Province, located in the middle and lower reaches of the Yangtze River-a hotspot for FHB in China. Key findings include: Since 1965, Regions I and III consistently exhibited higher FHB incidence rates compared to Regions II and IV. Post-2000, there was a notable increase in years with high incidence rates, with Region III overtaking Region I as the region with the highest incidence. Since 2010, occurrences of FHB reaching the most severe grade (Grade 5) have surpassed those in previous decades across all regions. The study also revealed a stronger correlation between meteorological factors (cumulative precipitation, number of days with rainfall ≥ 0.1 mm, total rainy days with ≥ 2 and ≥3 consecutive days of rain, total rainy days with both average daily air temperature ≥ 15 °C and daily rainfall ≥ 0.1 mm, days with average daily relative humidity ≥ 85%, cumulative sunshine hours, and cumulative cloudy days) and the FHB incidence rates during the heading-flowering-grain filling period in Regions I, II, and III, compared to the heading-flowering period alone. This indicates that optimal temperature and high humidity during the grain filling stage significantly contribute to the final FHB incidence rates. Despite the less apparent correlation between temperature changes and disease rates, the significant warming trend observed since 2000 has likely fostered conditions conducive to the proliferation of FHB. The comprehensive meteorological risk index, constructed to incorporate key meteorological factors during the heading-flowering-filling period, showed a strong correlation with actual disease incidences. The index demonstrated fitting accuracy rates of 84.7% for Region I, 72.9% for Region II, 83.1% for Region III, and 90.9% for Region IV, underscoring its effectiveness in predicting FHB occurrences. This tool offers both convenience and practicality, providing valuable insights for strategically managing FHB risks based on local weather conditions.

Application of multi-criteria decision making (MCDM) model for solar plant location selection

This study aims to systematically evaluate and identify the most suitable locations for establishing solar farms in the United Kingdom. It employs a comprehensive Multi-Criteria Decision-Making (MCDM) model that incorporates the Fuzzy Analytic Hierarchy Process (FAHP) method. Eight potential locations have been identified and selected for their climatic conditions and other pertinent parameters. These potential locations underwent additional assessment considering several factors including temperature, annual hours of sunshine, absolute humidity, proximity to major roads, distance from the power network, and potential demand. The data was normalized to eliminate scale effects and improve comparability. A MATLAB program has been developed with universality and user-friendliness in mind. Its purpose is to establish location selection factors graphs according to application-specific criteria and generate the matrix representation of these graphs for each potential candidate location. The permanent matrix, a composite metric synthesizing six criteria, identifies Torquay as the optimal location with a permanent value of 18.16. This quantitative approach, intersected with qualitative assessments, presents a clear hierarchy of site suitability. The model's simplicity, scalability, and proven accuracy make it a valuable tool for assessing renewable energy project viability in diverse regions.

Effects of environmental factors on host-parasite interaction patterns in backyard-tethered goats of Kerala, India

The environment is the most important stratum in the epidemiological triad of a parasitic disease and any variations in the environmental factors may decide the dynamic occurrence and existence of different lifecycle stages of these parasites. The present study investigated the correlations between key biometeorological and demographical parameters with the incidence of different gastrointestinal parasites and hemoparasites among goats. Four hundred and thirty-two goats were screened for parasitic infection in a yearlong survey conducted from July 2022 to June 2023 in the Teaching Veterinary Clinical Complex, Mannuthy, Kerala, India. The weather parameters (Tmax, Tmin, RH, THI, and bright sunshine hours), air quality parameters [AQI, PM2.5, and PM10], and demographic parameters (gender and age) were recorded along with the test positivity of different categories of gastrointestinal parasites and hemoparasites in goats by routine fecal sample examination and blood smear examination, respectively. The infection level was ranked based on the severity of the infection. The mean and daily variations in biometeorological parameters were calculated and the data were statistically analyzed to figure out the pertinent correlations in host-parasite-environment interaction patterns. High levels of parasitic infections with significant month-wise variations and climate-correlated peak infection patterns were noticed. The incidence of parasites was negatively correlated to all parameters except humidity, indicating more severe parasitism during monsoon months. The significant variations in the host-parasite interaction dynamics point towards the need for detailed explorations concerning the lifecycle of each specific parasite with a focus on the possible environment-favourable and resistant lifecycle stages. Future studies may be designed from a biometeorological perspective to develop a crucial understanding of host-parasite-environment interactions in goats ensuring sustainable goat farming.

Inter- and intra-annual carbon isotope fluctuations in Pinus sylvestris L. tree rings whole wood and cellulose in north-eastern Lithuania

In temperate regions trees typically exhibit growth sensitivity to climatic conditions during the growth season. Annual tree ring growth increments correlate with a variety of environmental factors. As an index of water use efficiency, δ13C is a preferred proxy to allow accurate interpretation of environmental factors critical for the tree growth, including changes in climate patterns, variation in the ambient temperature and precipitation. We assumed that isotopic differences within individual tree rings are likely to produce seasonal isotope fluctuations in the chronology that might be interpreted as response to environmental impacts. To verify the assumption, we measured δ13C in annual tree rings of Pinus Sylvestris L. split into 13 intra-annual segments each and checked δ13C correlations with temperature, precipitation, the number of sunshine hours and relative air humidity. For the investigation, we chose a site in north-eastern Lithuania, Zarasai, located in boreal latitude and remote from industrial pollution sources. The methodology of the research was based on high coherence of δ13C chronologies measured in the whole wood and α-cellulose extracted by means of two different methods. The experiment produced strong δ13C correlations with hydrometeorological parameters, especially in the earlywood formed in June

Long- and short-run asymmetric impacts of climate variation on tuberculosis based on a time series study

Distinguishing between long-term and short-term effects allows for the identification of different response mechanisms. This study investigated the long- and short-run asymmetric impacts of climate variation on tuberculosis (TB) and constructed forecasting models using the autoregressive distributed lag (ARDL) and nonlinear ARDL (NARDL). TB showed a downward trend, peaking in March-May per year. A 1 h increment or decrement in aggregate sunshine hours resulted in an increase of 32 TB cases. A 1 m/s increment and decrement in average wind velocity contributed to a decrement of 3600 and 5021 TB cases, respectively (Wald long-run asymmetry test [WLR] = 13.275, P < 0.001). A 1% increment and decrement in average relative humidity contributed to an increase of 115 and 153 TB cases, respectively. A 1 hPa increment and decrement in average air pressure contributed to a decrease of 318 and 91 TB cases, respectively (WLR = 7.966, P = 0.005). ∆temperature(−), ∆(sunshine hours)( −), ∆(wind velocity)(+) and ∆(wind velocity)(−) at different lags had a meaningful short-run effect on TB. The NARDL outperformed the ARDL in forecasting. Climate variation has significant long- and short-run asymmetric impacts on TB. By incorporating both dimensions of effects into the NARDL, the accuracy of the forecasts and policy recommendations for TB can be enhanced.

Exploring perceived relationships between weather, climate and mental health: biometeorological perspectives of healthcare practitioners.

Over the last decade, there has been an increase in research examining the influence of weather and climate in mental health caseloads. Variations in temperature, sunshine hours, cloud cover, precipitation and extreme weather events have been statistically linked to diagnoses and increases in hospital admissions for several mental health conditions. This study aimed to explore whether mental health practitioners perceive there to be a link between mental health and daily, seasonal, or inter-annual shifts in various climate variables in South Africa, and the timing and causal mechanisms thereof. Semi-structured interviews were conducted with 50 practicing healthcare practitioners, and the data was analysed using thematic analysis. The findings of this research show that all 50 participants were aware of the link between weather, climate and mental health, primarily through their awareness of seasonal affective disorder. Of the 50 participants, 38 participants could explain the aetiology of seasonal affective disorder. Participants perceived sunlight and temperature to exert an influence on mental health. All 50 participants perceived exposure to sunlight to exert a positive influence on several mental health conditions. Of the 50 participants, 36 participants perceived increases in temperature to exert an adverse effect on mental health symptomology. A minority of 11 participants perceived precipitation to influence mental health conditions such as seasonal affective disorder, bipolar disorder, and substance abuse disorder. Participants' perceptions of the influence of precipitation on mental health provided a unique potential explanation of this relationship, which, at the time of writing, has not been discussed in formal research.

Combining tree-ring growth and carbon isotope data enhances the understanding of climate sensitivity and physiological responses for Chinese fir in a common garden

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is one of China's most important tree species, and possible adverse factors affecting its growth and physiology is of particular concern for climate change adaptation. In this context, growth performance (BAI: basal area increment and MAXD: maximum density), climate sensitivity, and the relative contributions of climatic and physiological determinants to growth were evaluated across the 30 Chinese fir provenances using a combination of dendroclimatology and carbon isotope analysis (δ13C). Over the past 27 years, intrinsic water-use efficiency (iWUE) increased significantly by 12.71–33.56 %, while radial growth decreased (−63.38 % to −88.93 %). Strong growth decreases reflected increasing water stress due to climate warming, which was not offset by greater iWUE. A similar trend was observed in the theoretical gas exchange scenario as a response to increasing Ca as stomata opened and Ci increased proportionally to Ca. This study identified temperature and relative humidity as determinants of growth and physiology. However, meteorological factors (temperature, relative humidity, and sunshine hours) contributed much less to growth than physiological factors (iWUE). Variation in performance and climate sensitivity among populations significantly correlated with the mean annual temperature of the seed source origin. In general, seed sources from warmer and more humid climates in the center region grew faster and had higher iWUE. Provenances from drier climates had slower growth, higher wood density, and higher carbon isotope discrimination (Δ13C) compared to those from wetter climate conditions. Compared to provenances from cooler regions, the seed sources from warmer climates were less sensitive to temperature but more sensitive to sunshine hours for BAI and MAXD. These results contribute to a better understanding of the climate sensitivity and physiological responses of the Chinese fir provenances to long-term changing climate.

Promoting the Renewable Energy Zones by implementing the photovoltaic panels in an industrial building

Abstract Environmental protection depends on energy production and use, which are responsible for ∼94% of carbon emissions. The lack of sufficient energy resources has led EU countries to alternatives for Green Energy production. Albania’s national response to climate change has been limited to some small changes mainly in the sector of the integrated water and environmental management legislation. However, in terms of changing the energy law, no effort has been made to prioritize green energy production. Doing so it is expected to contribute to the overall goal of reducing greenhouse gas emissions through the integration of clean energy solutions. The paper is referred to a specific case study focused on renewable energy using photovoltaic panels in an industrial building in Saranda, as the city with the most hours of sunshine per year in Albania. To support renewable energy initiatives, it is being emphasized with the help of statistical methods that Saranda has strong potential to invest in energy production through solar panels, which give rise to long-term renewable energy solutions. In summary, there are being identified three main factors that seemed to contribute to the results of national renewable energy solutions: 1) Creating renewable energy zones, 2) Installing solar panels for electricity generation 3) Enforcing regulations. In such conditions when energy of any kind is the most demanded product, green energy is the best way to manage it. It is being used in any country, but especially in Albania, which has a high average of sunny days, compared to other European countries, is an immediate requirement and, as such it should be stripped of it all useless bureaucracies to enable a higher production of it, even with state subsidies. But development will also have to overcome the above issue by adapting to energy production in small units where bureaucratic hurdles are even smaller.

Spatiotemporal variation and GeoDetector analysis of NDVI at the northern foothills of the Yinshan Mountains in Inner Mongolia over the past 40 years

The study of spatiotemporal variation and driving forces of the normalized difference vegetation index (NDVI) is conducive to regional ecosystem protection and natural resource management. Based on the 1982–2022 GIMMS NDVI data and 26 influencing variables, by using the Theil-Sen median slope analysis, Mann-Kendall (M-K) test method and GeoDetector model, we analyzed the spatial and temporal characteristics of vegetation cover and the driving factors of its spatial differentiation in the northern foothills of the Yinshan Mountains in Inner Mongolia. The NDVI showed a significantly increasing trend during 1982–2022, with a growth rate of 0.0091 per decade. It is further predicted that future change in NDVI will continue the 1982–2022 trend, and sustainable improvement will dominate in the future; however, 17.69% of vegetation will degrade, that is, NDVI will degrade instead of improvement.. The spatial distribution of the NDVI in the northern foothills of the study area was generally characterized by high in the east and low in the west. Annual precipitation (Pre), evapotranspiration (Evp), relative humidity (Rhu) and sunshine hours (Ssd) had > 70% explanatory power (73.5, 79.9, 79.0, and 74.9%, respectively). The explanatory power of edaphic factors was > 30%, whereas anthropogenic and topographic factors had little influence on the spatial variation of NDVI, with an explanatory power of < 30%. Thus, climatic factors were the dominant factors influencing the spatial variability of NDVI in the study area. The results of the interaction detector analysis showed nonlinear strengthening for any two factors, and the interaction between Rhu and barometric pressure had the highest explanatory power. There were optimal ranges or characteristics of each factor that promoted vegetation growth. This study investigated the differences in the explanatory power of different factors on the NDVI and the optimal range of individual factors to promote vegetation growth, which can provide a basis for the development of vegetation resource management programs.

Experimental Investigation of Two-Pass Solar Dryer with V-Corrugated Absorber for Potato Slice Drying

Reducing the moisture level of food items can help prevent bacterial development and deterioration, extend shelf life, reduce packaging, and improve storage for convenient transportation. In this paper, a two-pass solar dryer with V-Corrugated absorber plate is developed. Its experimental performance evaluation in forced convection is carried out for potato chip drying. Various parameters like Hourly Variation of Solar Radiation Intensity, Temperature Distribution Curves inside Solar Dryer, Collector Efficiency Curve, Hourly Mass Loss of Potato Slices and Moisture Removal Comparison with Conventional Open Sun Drying Method are calculated and presented graphically. The peak temperature of the absorber plate reached 69.30C, and the air temperature at the collector outlet recorded the highest value at 57.50C. The average temperature difference of 28.580C is obtained for heat transfer by convection between the modified corrugated absorber plate and the air. An important finding in this experimental investigation was that there is an average 6.50C difference in temperature between the hot air exiting the collector and the air available at the bottom of the lower tray of the drying chamber, which should be reduced by applying means of avoiding heat loss. The highest collector efficiency is calculated as 88.9 % at 2 PM. The lowest efficiency is calculated at 9 AM as 66.8 %. The thermal inertia of the system adds to the collector efficiency in the last 2 hours of the experimentation and hence collector performs better than in the morning hours, though the insolation is nearly the same for the first and last two hours of sunshine. The percentage reduction in drying time was found to be 38.9 % for 50 % moisture removal from potato slices as compared to open sun drying.

The interaction between water quality and meteorological factors on chlorophyll-a concentration in Honghu Lake: based on PiecewiseSEM-generalized additive model coupling model.

In order to explore the interactive effects of environmental factors on the chlorophyll-a (Chl-a) concentration variation in Honghu Lake, this study was based on the monitoring data of Chl-a mass concentration and water quality factors (water temperature, pH, dissolved oxygen, permanganate index, total nitrogen, total phosphorus) and meteorological factors (evaporation, precipitation, sunshine hours, average wind speed) at three research sites (Dakou, Chatan Island, Lantian) in Honghu Lake from January 2010 to December 2019. Time series analysis, piecewise structural equation model (PiecewiseSEM), and generalized additive model (GAM) were used to quantitatively study the spatial and temporal changes of different environmental factors and their interaction with chlorophyll-a concentration in Honghu Lake. The results showed that the effects of TN and DO on Chl-a at Dakou and Chatan Island were more significant than other environmental meteorological factors, while the effects of DO and CODMn on Chl-a at Lantian were more obvious. At the same time, it was found that Chl-a had a non-linear relationship with TN and DO at Dakou and Chatan Island, a non-linear relationship with DO at Lantian, and a linear relationship with CODMn. The interaction effect of dominant environmental meteorological factors on Chl-a was significantly higher than that of a single factor, and the explanation rates were 80.6%, 72.8%, and 64.6%, respectively. In conclusion, based on the Piecewise SEM and GAM model, it not only can reveal the influence of the interaction of influencing factors on the change of Chl-a concentration, but also has important significance for the early warning and control of lake eutrophication.

Prediction of Maize Crop Yield Using Principal Component Analysis of Weather Parameters

The use of principal component analysis in the development of statistical models for crop yield forecasting has been demonstrated. Maize crop yield data for a period of 21 years (2001-2021) were drawn from the Dacnet website and the weather data were collected from the Meteorological Observatory, Department of Agrometeorology, College of Agriculture, G.B. Pant University of Agriculture and Technology Pantnagar, Uttarakhand. Maximum temperature, Minimum temperature, Relative Humidity A.M, Relative Humidity P.M, Total rainfall, Sunshine hours, Wind velocity and Evapotranspiration were the weather parameters considered for the study. Out of the 21-year data, 17-year data were used for training the model while remaining 4 years data were used for testing the model. Weekly data on weather variables was used to create weather indices [1]. This work involves developing forecasting models using Principal Component Analysis (PCA) and Multiple Linear Regression (MLR). Applied to extract principal components (PCs) from the correlation matrix of predictors. Five models (Model 1 to Model 5) are developed using MLR, with varying numbers of PCs as regressors which also include time trend and maize yield as dependent variable. The model performance was measured using Adjusted R-squared (adj R2) and Root Mean Square Error (RMSE) as goodness of fit criteria. On the basis of adj R2 and RMSE, model 1 which includes all the calculated weather indices, was found to be best suited model with high adj R2 (74.18 %) and least RMSE (276.36). Hence, this model can be used to forecast maize yield for the studied region.

Are Water Use Efficiency and Effectiveness Relatively Lower in Arid Zones? Comparative Analyses of the Water Productivity of Typical Crops

Agriculture is the largest water user of all sectors. In arid regions in particular, achieving efficient water use in agriculture is an important way to solve water scarcity. However, the difference in water use efficiency between arid and humid regions has long been a focus of academic debate. Many studies consider water use efficiency to be higher in humid areas due to the abundance of water resources. This view is based on the fact that less irrigation in humid areas may lead to higher crop yields and better conditions for agricultural production; however, it ignores the efforts of researchers and agricultural workers in arid zones who have attempted to develop efficient water-saving technologies, as well as the effect of natural conditions on agricultural production. Correctly evaluating the efficiency of agricultural water use in arid zones is important for achieving efficient use of water resources, as well as for water management decisions. This study calculates the yield structure and water productivity of typical crops in both arid and humid regions in China based on the footprint theory and other methodologies. This approach allows for an accurate assessment of irrigation water benefits in various regions, providing a scientific basis for improving agricultural water use efficiency under different climatic conditions. The study results indicate that the average reliance on blue water for wheat and cotton gradually increases from 49.9% to 93.6% as regional aridity intensifies, ranging from the Central China Humid Region to the Northwest China Arid Region. Similarly, the average contribution of blue water to crop yield rises from 31.0% to 100%, while irrigation water productivity increases from 0.27 kg·m−3 to 0.53 kg·m−3. Finally, this study concludes that, in arid zones with lower precipitation and more hours of sunshine, a higher dependence on blue water for crop growth and development leads to a higher productivity of irrigation water. In addition, in arid zones, the focus should be on optimizing the use of irrigation water and improving irrigation technology and efficiency, while, in humid zones, there should be more use of natural precipitation to efficiently reduce dependence on irrigation water.