bluuebunny/crossref_metadata_2025 huggingface dataset:
Potential gradient as a predictor of fog
Authors: Miller Caleb , Nicoll Keri , Westbrook Chris , Harrison R. Giles
Published: March 2024

Although fog is an important weather phenomenon, it remains difficult to predict using traditional methods. This could be improved by new observations-based nowcasting systems. It has long been understood that fog affects measurements of atmospheric electricity. However, there has been disagreement in the literature on whether these changes contain information which is valuable for fog prediction beyond other commonly used methods. Here, results are presented which show that the potential gradient (PG), a measure of atmospheric electricity, could be used as an additional diagnostic in predicting fog for timescales of several hours. A much larger dataset of fog and PG is examined than has been previously possible, which allows for a more robust understanding of the behaviour of the PG during radiation fog. It is found to increase by a median of 58 V/m by the start of the event. In addition, this increase is found to begin over two hours in advance of the fog, 30% of the time. This shows that PG may contain useful fog nowcasting information. A number of individual fog case studies are presented and the applicability of the general results to these specific cases is discussed. 
Actionable human-water systems modeling under uncertainty
Authors: Gil-García Laura , Montilla-López Nazaret M. , Gutiérrez-Martín Carlos , Sánchez-Daniel Ángel , Saiz-Santiago Pablo , Polanco-Martínez Josué M. , Pindado Julio , Pérez-Blanco C. Dionisio
Published: March 2024

Abstract. This paper develops an actionable interdisciplinary model that thoroughly quantifies and assesses uncertainties in water resources allocation under climate change. To achieve this objective, we develop an innovative socio-ecological grand ensemble that combines climate, hydrological, and microeconomic ensemble experiments with a widely used Decision Support System for water resources planning and management. Each system is populated with multiple models (multi-model), which we use to evaluate the impacts of multiple climatic scenarios and policies (multi-scenario, multi-forcing) across systems, so as to identify plausible futures where water management policies meet or miss their objectives, and explore potential tipping points. The application of methods is exemplified through a study conducted in the Douro River Basin (DRB), an agricultural basin located in central Spain. Our results show how marginal climate changes can trigger nonlinear water allocation changes in the Decision Support Systems (DSS); which can be further aggravated by the nonlinear adaptive responses of irrigators to water shortages. For example, while some irrigators barely experience economic losses (average profit and employment fall by <0.5 %) under mild water allocation reductions of 5 % or lower, profit and employment fall up to 12 % (~24x more) where water allocation is reduced by 10 % or less (~2x more). This substantiates the relevance of informing on the potential natural and socioeconomic impacts of adaptation strategies, and related uncertainties, towards identifying robust decisions.
SPATIAL INVENTORY OF SOLAR PHOTOVOLTAIC (PV) INSTALLATIONS USING REMOTE SENSING AND MACHINE LEARNING: CASE OF PAMPANGA PROVINCE, PHILIPPINES
Authors: Dalagan A. G. , Principe J. A.
Published: March 2024

Abstract. In recent years, the cost of photovoltaic (PV) technologies significantly declined, boosting the expansion of solar PV installations in the country. This rapid development in solar PV utilization necessitates an effective detection method capable of delineating both utility-scale and distributed PV installations to generate a complete inventory of solar PV installations for status monitoring and implementation of appropriate programs of stakeholders and decision-makers. This study aims to detect and delineate solar PV installations in Pampanga, Philippines using different band combinations of Sentinel-2, Sentinel-1, and indices (NDVI, NDWI, and PVSI) through machine learning with the aid of open-source geographic information system and remote sensing software. Moreover, an alternative approach to identifying solar PVs using the combination of pixel-based classification (PBC) and object-based classification (OBC) was introduced. Training and validation data were acquired from the satellite images. The accuracy of each approach in PV detection was then compared using three classifiers: Support Vector Machine (SVM), Random Forest, and Naive Bayes. Results showed that SVM has the best performance for PBC while Random Forest demonstrated the highest accuracy for OBC. A post-processing procedure was also implemented using a set of spectral rules to further refine the results of image classification. The delineation accuracies of the post-processed data over the ground-truth data showed that the methodology is effective in delineating utility-scale installations for both Sentinel-2 and Planetscope. However, the detection of distributed PV systems showed limitations particularly when dealing with small solar PV installations (less than 45 pixels) due to Sentinel-2’s coarse spatial resolution.
METHODS FOR SATELLITE DERIVED BATHYMETRY FROM SENTINEL-2 IMAGES: A COMPARISON
Authors: Figliomeni F. G. , Parente C.
Published: March 2024

Abstract. In recent decades, research has been developed to estimate near-shore bathymetry depth values using satellite imagery. Visible and infrared bands are used to derive elevation profile estimates, so to obtain bathymetric in rapid way without mobilisation of persons or equipment and saving the costs. For consequence, Satellite Derived Bathymetry (SDB) is seen as a valid approach for shallow waters survey: strongly supported by the activity of scholars and researchers, multiple methods are available in the literature. This article aims to investigate and compare different SDB methods for sea depth extraction from Sentinel-2 satellite multispectral images, with particular attention to the accuracy of the results. The experiments are conducted on imagery including Blue, Green, Red and Near Infrared bands, with 10 m resolution, concerning the Bay of Pozzuoli (Italy). After removing the glint, the effects caused by the reflection of sunlight through single scattering from sea surface, three methods are applied: Band Ratio method (BRM), 3rd-degree polynomial regression line method (3DPM), and principal component analysis method (PCAM). 3DPM can be seen as a variant of the BRM where the linear law that interprets the correlation between the band ratio values and the depth values is replaced by the third order function. Models are trained using depth data extracted from an Electronic Navigational Chart (ENC) at 1:7,500 scale, which is also used to verify result accuracy. The experiments demonstrate that the 3DPM is better able to obtain a more precise bathymetric model, confirming the greater adaptability of the 3rd order function to interpretate the variability of the interaction of light with water along the water column.
USING OPTICAL SATELLITE IMAGES AND SATELLITE ALTIMETRY DATA TO ESTIMATE VOLUME VARIATIONS IN DAMS
Authors: Ghanbari R. , Tayfehrostami A. , Forouzanfar M. , Tashakori M.
Published: March 2024

Abstract. This study focused on monitoring the water volume variations of the Doroudzan dam reservoir in Shiraz, Iran, using satellite observations. In particular, Sentinel-3 altimetry mission (SRAL) Level-1B and Level-2 data were employed to calculate water level changes, addressing the limitations in accuracy for inland and shallow waters. Re-tracking of returned waveforms was applied to improve the accuracy of Level-2 altimetry results. Additionally, Sentinel-2 optical images were utilized to monitor the water surface area of the dam reservoir. The results demonstrated that re-tracking the returned waveforms significantly improved the water level observations compared to Level-2 data. The analysis extended to comparing the time series of water surface area estimated from Sentinel-2 images with in-situ data, revealing a high accuracy of 5.39%. Combining optimum water level and surface area data in Heron's equation facilitated the calculation of water volume variations. A remarkable correlation of 95.27% was found when comparing the time series of estimated water volume variations and in-situ data. This study underscores the effectiveness of Copernicus satellites, particularly Sentinel-3 and Sentinel-2 missions, in monitoring inland water bodies and demonstrates the reliability of the techniques employed for tracking dam reservoir volume variations.
3D MONITORING OF COASTAL EROSION CONTROL STRUCTURES USING UAV
Authors: Sakamoto N. , Nishiyama S.
Published: March 2024

Abstract. Coastal erosion has increasingly become a problem in recent years due to rising sea levels caused by global warming. To prevent further coastal erosion and damage, control structures like seawalls and breakwaters have been installed along vulnerable coastlines. However, it is crucial that these structures are regularly and thoroughly inspected for any abnormalities or deformations. At present, inspections are done manually by visual surveys which are time-consuming and inefficient. There is great potential to optimize this process using drone technology equipped with 3D laser scanners. In this study, we utilized a drone with a green laser scanner to inspect and diagnose control structures along the coast. We conducted surveys to determine the basic performance of this approach and used ICP algorithms to extract any deformations in vanishing wave blocks over two time periods. Our results showed high variability in basic performance due to the influence of waves during the surveys. However, we were still able to detect strain of around 50 cm in a submerged breakwater located 3 meters below the water's surface. Furthermore, an overall settlement of approximately 34 cm was observed in the vanishing wave blocks along with some localized movements. This demonstrates that drones can be successfully implemented for efficient inspection, diagnosis and detection of abnormalities and deformations in coastal structures that are extremely difficult to identify through visual surveys alone. The use of this advanced technology will allow for quicker identification of at-risk structures, enabling timely maintenance and prevention of further coastal erosion.
ESTIMATION OF SUGARCANE YIELD USING MULTI-TEMPORAL SENTINEL 2 SATELLITE IMAGERY AND RANDOM FOREST REGRESSION
Authors: Taravat A. , Abebe G. , Gessesse B. , Tadesse T.
Published: March 2024

Abstract. Advancements in remote sensing techniques have greatly enhanced crop monitoring and yield estimation, with spectral vegetation indices (VIs) serving as a key component. Our study investigates the use of Sentinel-2 data, notable for its red-edge bands, in estimating sugarcane yield in Ethiopia's Awash Basin. Utilizing 22 VIs from S2 imagery, our approach combines Random Forest (RF) regression with the Recursive Feature Elimination (RFE) algorithm to improve the accuracy of sugarcane yield predictions. The results demonstrate the superior performance of the RF-RFE method over traditional RF with full datasets and Stepwise Multiple Regression (SMR). Particularly, VIs focusing on the red-edge spectral bands of S2 - such as NDVIre1n, NDVIre2n, NDVIre3n, NDRE1 and NDRE2 - were crucial in enhancing prediction precision. These indices from the red-edge and NIR narrow bands consistently influenced yield estimations in both the Wonji-Shoa and Metehara estates. The study underscores the critical role of the RFE algorithm in optimal variable selection, reinforcing earlier findings that precise variable choice can substantially boost model accuracy. The enhanced performance of the RF model when paired with the RFE algorithm was evident, emphasizing the importance of variable selection in accurate yield predictions. Employing the Out-of-Bag RMSE (OOB_RMSE) error estimate for evaluation, we observed variations in OOB_RMSE performance with different RF parameters, identifying the ntree value of 500 as optimal for the studied regions. The RF-RFE model’s estimations showed lower errors and higher correlation coefficients, proving its efficacy over a full dataset approach, which faced challenges with traditional VIs' saturation. Our findings align with earlier studies, highlighting the efficiency of S2’s red-edge bands in diverse estimation tasks and a shift towards using freely available broadband images like S2, over hyperspectral imagery, due to reduced data redundancy and processing costs. In conclusion, our findings reveal that RF regression, particularly when integrated with the RFE algorithm, is a powerful tool in remote sensing applications. The S2 imagery is optimal VIs, predominantly from the red-edge bands, exhibit significant potential for sugarcane yield estimations. The impressive results of the RF-RFE method, evident in metrics like MAE, MAPE, RMSE, Mean percentage, and R2, advocate its invaluable role in sugarcane yield prediction, highlighting its potential for optimizing irrigation management strategies and broad-spectrum agricultural planning.
THE EFFECT OF SEASONAL VARIATION ON GNSS ZENITH TROPOSPHERIC DELAY
Authors: Tekin Ünlütürk N. , Doğan U.
Published: March 2024

Abstract. The Global Navigation Satellite System (GNSS) signal experiences delays caused by the atmosphere, leading to the lengthening of the geometric path of the ray, commonly referred to as tropospheric delay. This delay is a significant source of error in GNSS positioning, contributing to a bias in the height component of several centimeters, even when meteorological data are simultaneously recorded and used in tropospheric models. In this study, considering seasonal variations, we investigated the impact of tropospheric delay on the GNSS height component. GNSS stations, part of the Turkish RTK CORS Network known as TUSAGA-Active (Turkish National Permanent GNSS Network Active), covered different heights over the 2014–2019 period. Daily coordinates of GNSS stations and tropospheric zenith delay were obtained through the GAMIT/GLOBK software solution.In the study, temperature, pressure, and relative humidity data of meteorological stations at different heights were converted to mean sea level. By using these values, interpolation estimates were made for the continuous GNSS stations in the same region with the IDW method. The most significant delay in GNSS signals occurs in July and August. This effect, which causes periodic changes in the zenith delay, varies inversely with the station's height. With the increase in the amount of water vapor in the atmosphere in parallel with the rise in the temperature in the summer months, it is seen that the stations at a low height are more exposed to the tropospheric effect than the stations at higher heights. In addition, GNSS stations' reduced meteorological values (temperature, pressure and relative humidity) show that the zenith delay values changed directly proportional to the temperature and inversely proportional to the pressure and relative humidity.
BIM-LADM AMALGAMATION — A REVIEW
Authors: Zamzuri A. , Abdul Rahman A. , Hassan M. I. , van Oosterom P.
Published: March 2024

Abstract. This paper discussed two International Organization for Standardization (ISO) standards, namely, ISO 19152 – Land Administration Domain Model (LADM) and ISO 16739 – Industry Foundation Classes (IFC), to identify three-dimensional (3D) multi-floor building rights. These days, it is challenging to characterize all multifunctional structures due to the increase in complex buildings. High-rise building land and property information management is recommended through building information modeling (BIM). Countries like the Netherlands, Australia, and Turkey have considered adopting BIM for their land administration. A land administration standard, such as LADM, offers better legal and physical representation in identifying the rights, restrictions, and responsibilities (RRRs) of the spatial units and stakeholders. However, LADM falls short in representing all building elements, such as semantic information and invisible functional spaces. Hence, this paper reviews incorporating additional information from BIM to create a comprehensive three-dimensional building representation including legal information from LADM. Issues and challenges also being highlighted with some recommendations for possible future works.
EXPERIMENTING TIN DATA STRUCTURE FOR REPRESENTING PLANE SURFACE AND SUBSURFACE SPATIAL OBJECTS - PRELIMINARY WORK
Authors: Apeh M. M. , Musliman I. A. , Abdul Rahman A.
Published: March 2024

Abstract. Understanding and analyzing complex spatial objects involves the integration of surface, terrain, and subsurface data into 3D spatial models. However, describing and efficiently analyzing the connections between these data model is particularly challenging. This study aims to generate TIN data structure that enable the 3D representation of surface terrain subsurface integration. Furthermore, to ensure accurate representation within a unified 3D model, spatial relationships between the TIN data model could be obtained. Consequently, three – dimensional Triangular Irregular Networks (3D TIN) mesh of spatial objects representations and indexing structures were created. The integration of spatial objects, encompassing surface, terrain, and subsurface elements, is realized through a unified model. This synergy is achieved by combining the distinct 2D and 3D topology structures of each component. The resulting comprehensive model captures the intricate relationships and interactions within the spatial environment. This study provides additional insight into the representation and analysis of surface, terrain, and subsurface management in 3D spatial models. Hence, better decision making, resource management, underground utility installations, and evaluation of spatial objects will be made possible in our future work.
FIRE WEATHER INDEX AND FOREST FIRE DANGER MAPPING: INSIGHTS FROM A CASE STUDY IN ANTALYA - MANAVGAT FOREST, TURKIYE
Authors: Atalay H. , Dervisoglu A. , Sunar F.
Published: March 2024

Abstract. Forest fires in Türkiye, like in other regions, have detrimental effects on wildlife habitats, water quality, air pollution, climate change, and the economy. These fires become particularly concerning during the dry summer months. In 2021, forest fires affected over 150 thousand hectares of land across the country, with the Manavgat district in Antalya province alone witnessing the burning of approximately 60 thousand hectares of forest area. This study aims to assess the applicability and suitability of Fire Weather Index (FWI) data derived from meteorological station data in the Antalya region, as well as EFFIS FWI data generated using satellite-based meteorological information, for fire danger mapping during the Manavgat forest fire that occurred between 28 July and 6 August 2021. Additionally, correlation analyses were performed between the two FWI datasets and other relevant variables, including the difference in Normalized Burn Ratio (dNBR), the difference in Land Surface Temperature (dLST), and Fire Radiative Power (FRP) data detected from MODIS and VIIRS satellites. The results of the correlation analysis indicated that the FWI values obtained using in-situ meteorology station data showed much higher correlations than FWI values obtained from EFFIS, with the highest correlation (73%) observed with dLST data. Consequently, the fire danger map was created using the in-situ meteorological data, given its stronger correlation. The results prominently revealed a widespread high-risk level across the entire Antalya province, with the Manavgat district classified into the "Extreme" and "Very Extreme" FWI classes, emphasizing the critical importance of utilizing in-situ meteorological data for precise fire danger assessments and proactive fire management strategies.
60-YEAR REMOTE SENSING OBSERVATIONS REVEALED CROSS-CYCLE EVOLUTION OF THE BRUNT ICE SHELF IN THE CONTEXT OF GLOBAL WARMING
Authors: Cheng Y. , Xue J. , Yu H. , Hai G.
Published: March 2024

Abstract. The Antarctic Ice Sheet (AIS) holds the potential to raise global sea levels by a staggering 57 m. Ice shelves, extensions of these ice sheets into the ocean, play a crucial role in stabilizing the upstream ice sheet. The Brunt Ice Shelf (BIS), located in the Southern Weddell Sea region and proximal to the continental shelf break, stands as a vital indicator for the region's response to global climate warming. Hence, this study systematically employs a range of remote sensing and field data, including remote sensing data from 1963 to 2023 (ARGON images, Landsat1-9 images, Sentinel-1 images, ICESat-2 altimetry data, etc.) and in-situ ice flow velocity data since 1956, to conduct a comprehensive analysis of the BIS's calving cycle and evolution over nearly six decades. The results reveal a significant exacerbation of both dynamical and structural instabilities in the BIS compared to the calving cycle in the 1970s. Combining analyses of air temperature from meteorological station, water temperature from ocean models and in-situ measurements such as Conductivity-Temperature-Depth profiles, the study suggests that the increased instability of the BIS is likely linked to the intrusion of warmer currents over the continental shelf. This research provides valuable insights into the evolving behavior of the BIS in response to changing climate conditions, underscoring the critical role of remote sensing data in advancing our understanding of these processes on a global scale.
Effect of Subsurface Drip System in Nitrate Leaching
Authors: Neelam Patel  , T.B.S. Rajput
Published: March 2024

Fertigation enables the application of soluble fertilizers and other chemicals along with irrigation water, uniformly and more efficiently. Improved water efficiency under drip irrigation, by reducing percolation and evaporation losses, provides for environmentally safer fertilizer application through the irrigation water. The overall problem is to identify economically viable practices that offer a significant reduction of NO3-N losses through leaching, which also fit in the farming systems practiced under a particular soil type and set of climate conditions. An experiment was conducted at Precision Farming Development Centre, Water Technology Centre, Indian Agricultural Research Institute, New Delhi to study the leaching of nitrate from the root zone of potato under surface and subsurface drip irrigation system. The study consisted of 2 types of drip system (surface and surface drip) as main treatments and 3 levels of irrigation including 100% crop evapotranspiration, 80% of crop evapotranspiration and 60 % of crop evapotranspiration as sub-treatments. Direct correlation was found between the amount of irrigation water and nitrate leaching. Reduction of amount of irrigation water to the tune of 40% decreased the nitrate leaching from 30% to 10 per cent. It was observed that by changing the position of water source from surface to subsurface, the nitrate leaching decreased by 12-20%, and thus subsurface drip (10 cm depth of drip tape) was recommended in potato crop to get higher yield with minimum leaching of soil nitrate-nitrogen.
Effect of Operating Speed and Cob Size on Performance of a Rotary Maize Sheller
Authors: P.S. Tiwari  , M. M. Pandey  , L. P. Gite  , A. K. Shrivastava
Published: March 2024

The operating speed of rotary maize sheller was optimised for its operation at higher operating speeds in pedalling mode, by conducting a simulation study for three sizes of maize cobs at seven operating speeds. The shelling capacity and shelling efficiency of maize sheller for all categories of maize cobs increased curvilinearly with increase in operating speed up to about 70 rpm. The shelling capacity at a particular operating speed decreased with increase in the maximum diameter of cobs. Operating torque of rotary maize sheller for a given size of maize cobs decreased with increase in operating speed. On the other hand, the torque decreased with decrease in maximum diameter of maize cobs at a given operating speed. It was concluded that the operating speed of maize sheller should be 70 to 80 rpm for higher shelling capacity, shelling efficiency and lower operating torque.
Studies on Nitrate-nitrogen Movement under Sub-surface Drip Irrigation in Potato
Authors: N. Tiwari  , M. K. Maji  , U. Biswas  , P. K. Mal
Published: March 2024

Among various inputs, the modern agriculture is heavily dependent on the use of fertilizers and pesticides to meet the food requirements of ever-increasing population. Nitrate form of nitrogen is one of the major plant nutrients, and is mainly responsible for the pollution of soil and water resources. The movement of nitrate-nitrogen (NO3-N) in the soil is a complex, but largely affected by water movement. An attempt was made to study the dynamics of NO3-N under sub-surface drip irrigation in potato (Kufri-jyoti) crop. Four levels of fertilizer-N were applied at two depths of application with subsurface drip. The nitrogen fertigation levels were 40 %, 60 %, 80 % and 100 % of the recommended dose and replicated three times. Irrigation water requirement of the crop was estimated using cumulative pan evaporation data. The soil samples from three depths (0-15 cm, 15-30 cm and 30-45 cm) of the crop field were collected for chemical analysis. The maximum concentration of nitrate content was at 100 % fertigaton levels, followed by 80 % N level. The biometric observations showed that application of 100 % N fertigation through subsurface drip irrigation buried at 10 cm depth exhibited highest vegetative growth as compared to other N fertigation levels. The maximum yield of 23.84 t/ha was obtained under the same treatment, followed by 20.03 t/ha under the treatment 80 % N. The economic analysis indicated highest benefit-cost ratio of 2.11:1 for the treatment 100 % N (F4) followed by 1.64:1 for 80 % N.
Performance Evaluation of Different Seed Cotton Distribution Systems used in Modern Indian Ginneries
Authors: K. Shukla  , V. G. Arude  , Jyoti M. Nath
Published: March 2024

The distribution systems were compared on the basis of productivity of double roller gins and power requirements. The productivity loss of first, central and end DR gins in a row with the distribution system varied between 2.7 to 9.6% as compared to manual feeding. However, the trolley feeding-single side for 6 DR gins / trolley did not cause any productivity loss. Among the systems studied, the trolley feeding-single side for 6 DR gins / trolley was best, followed by trolley distribution system-either side (8 DR gins/trolley) in terms of productivity of DR gins. In case of screw conveyor distribution system, minimum productivity loss was observed for 9 DR gins. Power requirement per DR gin for different kind of distribution systems varied from 373 to 1343 W. Minimum power requirement occured for trolley feeding system-either side with 18 DR gins/trolley, whereas maximum power requirement was for trolley distribution system-single side with 6 DR gins / trolley. The distribution systems should be carefully selected and used for feeding the optimum number of DR gins so as to avoid the shortage of seed cotton while processing.
Computer Vision – A Versatile Technology in Automation of Agricultural Machinery
Authors: Jens Möller
Published: March 2024

The agricultural market in developed countries is evolving from being mechanised in the 20th century, with still larger machines being automated in the 21st century. Development of automation technology for agricultural machinery includes many aspects. As the degree of automation increases, the complexity of automation would rise. The paper focuses on the sensor sub-system, and more specifically, computer vision technology. The emergence of widely available vision technologies has enabled the manufacturers to automate a wide range of tasks. Weed control and auto-guidance systems are two areas in agriculture that have driven the development of vision technology. Applying computer vision technology makes it possible to automate the navigation tasks when the vehicle is driven along crops and other field structures. The operator stress level can be generally reduced and high precision steering in sensitive crops can be maintained through out the day. The driver can concentrate on optimizing the machine settings and ensure a safe operation of the system. Machine settings can be optimised yielding a higher quality in the field operations. The working speed can be increased, thus saving time and money.
Optimal Cropping Pattern for Adoption of Micro-Irrigation Methods in Canal Command Area - A Case Study
Authors: S.B. Gadge  , S.D. Gorantiwar  , Virendra Kumar  , Mahesh Kothari
Published: March 2024

Currently the micro irrigation methods are mainly adopted on farms with irrigation from tube wells or dug wells. However, in view of increasing scarcity of water for irrigation and need to increase food production, it is important to adopt these methods in canal command area. A linear programming model was formulated to suggest the optimal cropping pattern under micro irrigation method in canal command areas. The objective was to achieve the maximum such as net returns. The objective function of the model was subjected to the constraints such as total available water and land during different irrigation periods, crop area restrictions, and system reutilization constraints. The system reutilization constraint facilitated utilization of micro irrigation system among the different short duration seasonal crops having similar system geometry requirement. The model was applied to command area of direct minor no. 3 of the Mula Irrigation Project, Ahmednagar, Maharashtra. The model gave optimal cropping pattern for
Effect of Contour Cultivation on Rainfall-Runoff Relationship and Productivity in Rainfed Agriculture
Authors: S.M. Taley
Published: March 2024

A field experiment was carried out to test the suitability of contour cultivation with vegetative contour hedges (T2, leucaena and T3, vetivar) over cultivation across (T4) and along (T1, traditional) the slope in controlling runoff, soil and nutrient losses. During the study period of 9 years, data pertaining to surface runoff, soil and nutrient losses revealed the superiority of contour cultivations along with the vegetative hedges in controlling runoff and soil nutrient losses over cultivation across and along the slope. The average percentage runoff for the rainfall causing runoff (437.41 mm) was 14.98 (T3), 20.42 (T2), 22.46 (T4) and 28.93 (T1) along with the soil loss of 1.36 (T3), 2.31 (T2), 3.99 (T4) and 7.21 (T1) t.ha-1. Maximum reduction in NPK (55 to 63%) was observed in contour cultivation along with the vetiver hedge (T3). The average yield levels of sorghum enhanced by 14.40 to 19.38% in contour cultivation with vegetative hedges (T2 and T3) and 7.45% in cultivation across the slope (T4) over the traditional practice of cultivation along the slope (T1). It was observed that contour cultivation along with the vetivar hedges (T3) is effective in controlling runoff and soil and nutrient losses. The study further indicated that the best fit equations were 4th degree polynomial for all the treatments having coefficient of determinant (R2) as 0.86, 0.84, 0.72 and 0.84 for T1, T2, T3 and T4 respectively.The developed rainfall-runoff relationships could be successfully used for predicting runoff.
Ergonomic Evaluation of Rotary Power Input by Hand and Leg Muscles to Operate Farm Equipment
Authors: Potdar Rahul Rajaram  , Ramchandra Ram  , Adarsh Kumar  , J.K. Singh  , Indra Mani
Published: March 2024

An ergonomic study was conducted to evaluate common postures to facilitate active combination of body muscles to generate rotational motion in static mode. The study was conducted on five modes of posture, namely handle rotation, hand rocking, single foot pedal, dual foot pedal and foot rotation (cycling) for generating rotary motion. A postural dynamometer was developed for loading and recording power load in above-mentioned modes. The experiments were conducted with six subjects in the age group of 20 to 40 years at five levels of mechanical load. During the experiments, physiological and postural parameters were recorded and data was statistically analyzed. Foot cycling mode was found to be best for mechanical power load up to 60W and dual foot pedal mode for 60 to 75 W. Study established the fact that leg muscles are better suited to provide manual power on sustainable basis as in both modes (cycling and dual foot pedal), leg muscles were primarily used.
Effect of Pre-milling Treatments on Green Gram Dhal Recovery
Authors: S. Kshitija Wani  , S. K. Jha  , Amar Singh  , R. Shrivastava  , G. K. Jha  , J. P. Sinha
Published: March 2024

Effect of oil and thermal treatments on milling quality of green gram was studied at 8 to 12% moisture content (w.b) with 2.40 to 4.00 g.kg-1 oil for treatment and holding time of 5 to 10 h, thermal treatment at temperature of 80 to 120°C and roasting duration of 1 to 5 min. These pretreatments showed dhal recovery of 70.01 to 74.93% in case of oil treatment, and 71.18 to 78.12% in case of thermal treatment as against 61.19 to 65.64% without any pretreatment. Optimum conditions for oil treatment for maximum dhal recovery were 10.26% (w.b), oil quantity of 3.17 g.kg-1 and holding for 7.72 h, roasting for 2.86 min at temperature of 99.24°C and 10.25% moisture content (w.b) for thermal treatment of green gram.
Nitrogen Use Efficiency and Yield of Maize under Deficit Irrigation
Authors: M. Abdenipour  , A. Sarangi  , T.B.S. Rajput  , Man Singh
Published: March 2024

The NUE in maize (hybrid BIO-9681) crop with different levels of nitrogen under varying irrigation levels was estimated through an experiment conducted during 2009 and 2010. The field experiment comprised of four levels of irrigation and four levels of nitrogen application rates replicated thrice in a randomized complete block design. Irrigation water treatments in the main plots were: rainfed (W1); 50 % deficit irrigation (W2), 25 % deficit irrigation (W3) and full irrigation (W4). Nitrogen levels in sub plots were 0 (N1), 75 (N2), 150 (N3) and 225 (N4) kg.ha-1. Application of nitrogen significantly affected the grain yield and NUE for N2 and N3 (75 and 150 kg N.ha”1) treatments at 0.01 and 0.05 probability levels, respectively. However, the difference in yield and NUE were non-significant for N3 and N4 treatments. Maximum grain yield and biomass was observed for W4N4 treatment amounting to 6050 kg.ha-1 and 18650 kg.ha-1, respectively, during 2009. On the other hand, grain yield and biomass during 2010 was highest for W4N4 treatment amounting to 5860 kg.ha-1 and 18010 kg.ha-1, respectively. The highest NUE (19.6 kg grain.kgN-1) was obtained for W4N2 treatment combination during 2009, while it was highest (21.7 kg grain.kgN-1) for W3N2 treatment during 2010. Overall, the NUE decreased with increasing nitrogen level beyond 75 kg N.ha-1 (N2) at all irrigation levels.
Grain Storage for Food Security and Safety: Research at the University of Manitoba, Canada
Authors: Digvir S. Jayas1
Published: March 2024

Globally over 2 billion tonnes of grains, oilseeds, and pulses (hereinafter referred to as grains) are produced annually and stored at different points along the grain distribution chain between the producer and the consumer. The post- harvest losses for grains range from
Detection of Fungal Infection in Canola using Near-Infrared Hyperspectral Imaging
Authors: T. Senthilkumar  , C.B. Singh  , D.S. Jayas  , N.D.G. White
Published: March 2024

Near-infrared (NIR) hyperspectral imaging was used to detect the presence of fungal infection in stored canola. Artificially fungal infected (Aspergillus glaucus group) canola was subjected to single kernel imaging every two weeks after incubation using an NIR imaging system in the wavelength range of 1000 to 1600 nm at 60 evenly distributed wavelengths. Three wavelengths 1100, 1230 and 1300 nm were identified as significant wavelengths and used in the analysis. Statistical discriminant classifiers (Linear and Quadratic) were used to classify healthy, two–, four–, six–, eight–, and ten–week fungal incubated samples. The linear and quadratic statistical classifiers gave maximum accuracy of 99% for healthy samples and 100% for fungal infected samples at later stages of infection levels and 90 to 95% for the first four weeks of A. glaucus infected samples.
Study on the Impact and Adoption of Soil and Water Conservation Technologies in Eastern Ghats of India
Authors: S. Sudhishri  , Anchal Dass
Published: March 2024

Land degradation is a serious problem world-over and need immediate attention. The eastern Ghats of India spreading over 19.8 Mha have suffered severe erosion due to shifting cultivation, deforestation, over grazing and faulty land use. Site specific soil and water conservation measures were implemented in Kokriguda watershed, a representative of the eastern Ghats of India, for monitoring their impact on resource conservation, productivity and income of tribal farmers as well as their adoption by the tribal farmers. Cost effective soil and water conservation (SWC) measures viz., contour and stone bunds, trench-cum-bunds with vegetative barriers and hedge rows, sunken ponds, loose boulder check dams etc. were constructed at suitable locations. Bio-engineering measures were generally preferred. These land treatments resulted in reduction in soil loss and runoff by 82 and 51%, respectively, rise in water table by 0.32 m, and increase in crop yield by 15 to 38% within four-year period. Irrigated area increased from 2 to 35 ha due to water resources developed. Total income from vegetable cultivation using harnessed water for the whole village increased to Rs. 1.4 lakh.year-1. Farmers’ participation in soil and water conservation activities was appreciable, and their contribution to different activities varied from 5 to 10 per cent. However, education and support services to convince the farmers about the problem of soil degradation and training on soil conservation practices is essential for large scale adoption of soil and water conservation measures.
Decision Support Tool for Evaluating Changes in Arid and Tropical Watersheds
Authors: Forood Sharafi  , Jan Adamowski  , Jalal Barkhordari  , Hossein Saadat
Published: March 2024

During the last three decades, many arid and semi-arid watersheds have been affected by major hydrological changes because of human interventions such as deforestation and other agricultural changes, as well as climate fluctuations and/or changes. The primary objective of this study was to investigate whether recent changes are the result of climatologic variability or anthropologically induced transformations over the past years. A secondary objective was to provide a more practical approach to assess actual changes in the hydrological response of a watershed in an arid and tropical region. The methodology used in this study involved combining remotely sensed image data from satellites with in-situ hydrological observations from the Minab catchment in the south of Iran. The results of longterm analysis of historical time series on rainfall, land use/land cover, and stream flow were integrated at the landscape level to identify appropriate options for land and water management. It was found that the destruction of natural vegetation resulted in a decrease in the annual total water yield of 20%, with a decrease of 6.5% in the base flow during the low-flow period (May to November), and an increase in the storm runoff during the high-flow period (December to April). While potential evaporation from periods 1 to 3 showed a decrease of 10%, the actual evaporation increased by 9 per cent. It was concluded that climatic variations and land use change are the most important factors affecting the changes in the hydrologic regime of Minab catchment in Iran.
Runoff Prediction: Use of Muskingum Model for a Small Watershed
Authors: Pravendra Kumar  , J. K. Singh
Published: March 2024

An effort was made to develop a mathematical model using unit-step and transfer functions approach for Karkara watershed of Tilaiya dam catchment in Upper Damodar Valley of Jharkhand State of India for estimating direct runoff hydrographs on storm basis. The model used rainfall data in blocks of finite duration represented by unit step function. The outflow hydrograph ordinates were obtained by taking inverse Laplace transform of product of Laplace transforms of the transfer function (Laplace transform of Instantaneous Unit Hydrograph) and the input (effective rainfall). The direct runoff hydrograph ordinates were computed by lagging outflow hydrograph ordinates. Model parameter was estimated by Sabol method using rainfall and runoff data of the study watershed. The model was calibrated for nine storm events, and validated for three events. Quantitative performance of the model was tested using some of the widely used statistical indices as integral squared error, relative squared error and coefficient of efficiency. The estimated direct runoff hydrographs using the model were in close agreement with the observed direct runoff hydrographs. The developed model can be satisfactorily applied for prediction of storm direct runoff hydrographs from small watersheds in the study region.
Application of Artificial Neural Network in Predicting Farmers’ Response to Water Management Decisions on Wheat Yield
Authors: M.K. Hardaha  , S.S. Chouhan  , S.K. Ambast
Published: March 2024

Water management usually involves decision-making with respect to allocation, scheduling and application of available water to different crops over an irrigation season so as to get maximum economic returns. A study was carried out in the Kaithal irrigation circle for prediction of farmers’ decisions regarding total depth of irrigation water, fraction of groundwater and delay in sowing on yield of wheat crop under varying conditions of groundwater and soil salinity using Artificial Neural Networks (ANN). Three ANN algorithms i.e. gradient-descent back propagation (BP), Levenberg-Marquardt (LM) and radial basis functions (RBF) with various architectures were used. It was found that radial basis function with a spread constant of 0.1 performed better in predicting wheat yield. Also, it was observed that ANN algorithm predicted wheat and rice yields better correlated to observed yields (r2=0.63 and 0.74) in comparison to regression model (r2=0.37 and 0.52)
RS and GIS for Identification of Potential Sites for Water Harvesting Structures in Bandal Watershed
Authors: J.P. Singh  , I. Sekar  , K.H.V. Rao
Published: March 2024

A case study was conducted to identify the suitability of potential sites for groundwater recharge structures in Bandal watershed, Uttaranchal, using Remote Sensing (RS) and Geographical Information System (GIS). Sites for 8 check dams, 86 groundwater recharge structures (percolation tanks) and 15 farm ponds and check dams were identified covering an area of 449,531 m2, 449,531 m2 and 36,448 m2, respectively.
2. NGHIÊN CỨU TỶ LỆ NHIỄM KÝ SINH TRÙNG SỐT RÉT TẠI XÃ IA HDRE, HUYỆN KRÔNG PA, TỈNH GIA LAI NĂM 2020
Authors: Ly Phan Cẩm , Vỹ Trình Hoàng
Published: March 2024

Mục tiêu: Xác định tỷ lệ nhiễm ký sinh trùng sốt rét và tìm hiểu một số yếu tố liên quan nhiễm ký sinh trùng sốt rét tại xã Ia Hdreh, huyện Krông Pa, tỉnh Gia Lai năm 2020.

Đối tượng và phương pháp nghiên cứu: Nghiên cứu cắt ngang mô tả thực hiện trên 406 trường hợp người dân sinh sống trên địa xã Ia Hdreh, huyện Krông Pa, tỉnh Gia Lai, thời gian từ tháng 10/2019 đến tháng 6/2020 với việc xét nghiệm tìm Ký sinh trùng sốt rét bao gồm cả định loài và định thể vô tính-hữu tính, kết hợp điều tra thông tin dịch tễ.

Kết quả: Tỷ lệ nhiễm ký sinh trùng sốt rét trong cộng đồng người dân xã Ia Hdreh là 3,2%, tỷ lệ thể giao bào chiếm 0,74% tổng số 406 người. Có mối liên quan có ý nghĩa thống kê giữa tỷ lệ nhiễm ký sinh trùng sốt rét với nhóm tuổi, trình độ học vấn, và nhất là thói quen ngủ màn (OR 6,24).

Kết luận: Có sự lưu hành sốt rét tại cộng đồng người dân xã Ia Hdreh với tỉ lệ hiện mắc 3,20%; với tỉ lệ giao bào là 0,74%, P.falciparum chiếm 76,90%; P.vivax chiếm 23,10%. Cần theo dõi sát diễn biến tình hình sốt rét tại xã Ia Hdreh, huyện Krông Pa, tỉnh Gia Lai và đánh giá kết quả triển khai các biện pháp can thiệp phòng, chống bệnh sốt rét để kịp thời ngăn chặn dịch xảy ra.
7. GÁNH NẶNG ĐA BỆNH VÀ MỐI LIÊN QUAN VỚI SUY YẾU TRÊN NGƯỜI CAO TUỔI BỊ LOÃNG XƯƠNG
Authors: Khoa Trương Trí , Huân Nguyễn Thanh , Công Nguyễn Đức
Published: March 2024

Mục tiêu: Khảo sát thực trạng đa bệnh và mối liên quan giữa đa bệnh với suy yếu trên người cao tuổi bị loãng xương.

Đối tượng và phương pháp nghiên cứu: Nghiên cứu cắt ngang mô tả trên 296 bệnh nhân cao tuổi loãng xương điều trị tại khoa Nội cơ xương khớp, khoa Ngoại thần kinh, phòng khám Nội cơ xương khớp, Bệnh viện Đại học Y Dược TP. Hồ Chí Minh.

Kết quả: Nghiên cứu đã thu thập được 296 bệnh nhân cao tuổi bị loãng xương. Tỉ lệ đa bệnh trên người cao tuổi bị loãng xương là 43,2% (128/296). Những bệnh đồng mắc thường gặp bao gồm thoái hóa khớp và tăng huyết áp. Nhóm đa bệnh có tuổi trung bình cao hơn, có tỉ lệ tiền căn GXĐS, phụ thuộc ADL, phụ thuộc IADL, suy yếu nhiều hơn nhóm không đa bệnh có ý nghĩa thống kê, nhưng có tỉ lệ hoạt động thể lực ít hơn nhóm không có đa bệnh. Trong mô hình hồi quy logistic đơn biến, đa bệnh có liên quan với suy yếu, nhưng mối liên quan đi này không quan sát thấy khi thực hiện các mô hình hồi quy có hiệu chỉnh với tuổi.

Kết luận: Người cao tuổi bị loãng xương có gánh nặng đa bệnh tương đối cao với tỉ lệ 43,2%. Đa bệnh có liên quan với suy yếu trong mô hình đơn biến nhưng không quan sát thấy khi hiệu chỉnh cho tuổi.
11. NHẬN THỨC VỀ AN TOÀN NGƯỜI BỆNH CỦA ĐIỀU DƯỠNG TẠI BỆNH VIỆN ĐẠI HỌC Y DƯỢC, ĐẠI HỌC QUỐC GIA HÀ NỘI, NĂM 2023
Authors: Hiền Nguyễn Thị Thu , Hằng Lê Thị , Tuyến Nguyễn Thị
Published: March 2024

Đặt vấn đề: An toàn người bệnh (ATNB) đang trở thành một vấn đề nhận được rất nhiều sự quan tâm của cộng đồng và cũng đặt ra thách thức lớn với ngành y tế. ATNB là tránh và phòng ngừa tổn thương hoặc sự kiện bất lợi trong quá trình chăm sóc cho người bệnh [4]. Cơ quan nghiên cứu chăm sóc sức khỏe và chất lượng đã định nghĩa văn hóa ATNB là thái độ, nhận thức, năng lực và mô hình hành vi của mỗi cá nhân nhân viên y tế hay của cơ sở y tế. Những đặc điểm này xác định trách nhiệm và cam kết của tổ chức chăm sóc sức khỏe (CSSK) trong đảm bảo ATNB [5].

Mục tiêu: Mô tả nhận thức về ATNB của điều dưỡng tại Bệnh viện Đại học Y Dược, ĐHQGHN năm 2023.

Phương pháp: Điều tra cắt ngang, nghiên cứu định lượng

Kết quả và kết luận: Nhận thức đúng phản hồi tích cực về ATNB của 150 điều dưỡng tại Bệnh viện Đại học Y Dược là rất tốt, cụ thể: NVYT đánh giá cao công tác quản lý ưu tiên người bệnh của bệnh viện (>90%), phối hợp tốt giữa các khoa phòng (94%), bàn giao ca trực (88%), cấp phát thuốc đúng quy định tại khoa (90%). NVYT lo lắng thiếu sự hỗ trợ khi có sai sót (74,6%), NVYT cảm thấy bị thành kiến khi có sai sót (41,0%), sai sót trong kê đơn thuốc tại khoa (>50%).
15. NGHIÊN CỨU VỀ TÌNH TRẠNG SUY DINH DƯỠNG THẤP CÒI Ở HỌC SINH TIỂU HỌC THUỘC VÙNG VEN BIỂN HUYỆN PHÚ VANG, TỈNH THỪA THIÊN HUẾ
Authors: Thúy Lê Thị Bích , Vy Nguyễn Vũ Thảo , Mai Hồ Võ Thị Như , Ánh Trương Thị Ngọc , Trung Nguyễn Lê Quốc , Nha Phùng Phương
Published: March 2024

Đặt vấn đề: Suy dinh dưỡng thấp còi (SDDTC) là một chỉ số của suy dinh dưỡng (SDD) mãn tính, phản ánh kết quả của một quá trình dài chăm sóc, nuôi dưỡng trẻ thiếu dinh dưỡng.

Mục tiêu: (1) Xác định tỷ lệ suy dinh dưỡng thấp còi của học sinh tiểu học thuộc vùng ven biển huyện Phú Vang, tỉnh Thừa Thiên Huế và (2) Tìm hiểu một số yếu tố liên quan đến tình trạng suy dinh dưỡng thấp còi ở đối tượng nghiên cứu.

Phương pháp nghiên cứu: Nghiên cứu mô tả cắt ngang, thực hiện trên 417 mẹ học sinh và học sinh tại các trường tiểu học không bán trú.

Kết quả: 7,0% học sinh mắc SDDTC, trong đó tỷ lệ học sinh SDDTC mức độ vừa là 6,0% và mức độ nặng là 1,0%. Có mối liên quan có ý nghĩa thống kê giữa tình trạng SDDTC với các yếu tố loại nhà ở, sử dụng sữa ở học sinh, chẩn đoán SDD trong một năm qua và chiều cao cha (p<0,05).

Kết luận: Tỷ lệ SDDTC ở học sinh tiểu học còn cao. Ngành y tế cần triển khai những kế hoạch thiết thực và thực hiện nhiều nhóm biện pháp nhằm cải thiện tình trạng dinh dưỡng học sinh.