Variability in vegetation indices as a function of unmanned aerial vehicle flight altitudes and other factors during crop monitoring applications

Unmanned aerial vehicles (UAV) integrated with multispectral sensors has been widely used for phenotyping in plant breeding programs and other agricultural applications. However, the extracted vegetation indices can be affected by radiometric correction, altitude of image acquisition, and orthomosaic generation. In this study, we used wheat and pea trials to evaluate the effect of using different reference reflectance panels for the radiometric correction as a function of flight altitude on commonly used vegetation indices. Pea and wheat data were collected at the initial ripening or flowering stages, respectively. In both trials, single multispectral images were collected at 25m, 35m, 45m, 55m, 65m, and 75m flying altitudes. In addition, UAV was used to collect multispectral images at 25m, 4m, and 75m flying altitude and stitched with multiple photogrammetry software (DroneDeploy, ImageBreed, Agisoft, and Pix4D). For radiometric correction, four Lambertian reference panels were used (10%, 18%, 50%, and 99%). The main results indicated that panels with reflectance of 10% and 20% were suitable for radiometric corrections, since the digital number from these panels did not saturate in most cases. In addition, the correction using the 18% reflectance panel demonstrated consistent reflectance response across flight altitudes. Nevertheless, differences in responses were observed as a function of the flight altitudes after orthomosaic generation, especially with DroneDeploy, ImageBreed, and Pix4D. Vegetation index values, such as normalized difference vegetation index, were highly affected by photogrammetry software. Such information is critical to characterize the multispectral data acquired from UAV and other platforms to extract precise and stable data for agricultural applications

Effects of operational factors on the efficiency and thoroughput capacity of African locust bean processing Machine

De-hulling and cleaning of beans remains a major tedious operation in the processing of locust bean. Using a locust bean de-huller that combine de-hulling and cleaning is one approach to reduce drudgery and improve the quality of the seed. The aim of research is to optimise the operating conditions of a locust bean processing machine for de-hulling and cleaning. To measure de-hulling and cleaning efficiency, dried locust beans were boiled at 2, 4 and 6hr boiling time, loaded onto the machine at various feeing rates (15, 20, and 25kg/hr) and shaft speed (7, 8, 9). The Response Surface Methodology (RSM) was utilised to optimize the operating parameter used in de-hulling process. Quadratic models were developed to establish the interaction between the operational parameters and the response factors. The effect of the investigated operational parameters on the de-hulling and cleaning efficiency were significant (p ≤0.01).  The optimal condition of the process for shaft speed, boiling time and feeding rate were 7m/s, 6hr and 25kg/hr, respectively, resulting in quantitative de-hulling efficiency, qualitative de-hulling efficiency, throughput capacity and cleaning efficiency of 98.67%, 25.85%, 21.66kg/hr and 84.62%, respectively.  This indicate that the locust bean processing machine performed efficiently at optimal conditions thus valid the models developed

Comparative evaluation of FAO56-PM ET0 estimates using meteorological parameters retrieved from MERRA-2 satellite and ground dataset for humid Dehradun region of India

In this study conducted with specific objective to compare ET0 estimates obtained at monthly and cropping (kharif, rabi and zaid) season timescales with climatic parameters retrieved from MERRA-2 satellite and ground meteorological dataset with standardized FAO56-PM model for humid Dehradun district of Uttarakhand, it was found that during 29 years study period, about 84.45% months resulted in very good correlation between FAO56-PM ET0 estimates obtained with MERRA-2 satellite parameters and ground meteorological dataset, while about 37.93% and 27.59% kharif seasons were observed under Very Strong Positive and Strong Positive levels, respectively. Similarly, about 93.10% and 6.90% rabi seasons were obtained with Very Strong Positive and Strong Positive correlation coefficient values. For zaid season, about 93.10% seasons showed Very Strong Positive correlation coefficient values. About 99.71% months during study period extended good agreement in terms of Agreement index. On cropping season basis, 55.17% kharif, 62.07%, rabi, and 7.31% zaid seasons respectively showed agreement index values with medium agreement

Classification method of applying types of rice fertilizers using Resnet50 architecture

The Indonesian government has implemented various strategies to increase rice production and productivity. However, until now, the results have not met expectations, and the sustainability of rice farming practices in Indonesia is still poor. One of the important problems that needs to be addressed is the imbalance of fertilizer use, as it can cause various problems in rice cultivation that lead to non-optimal productivity of rice plants, such as reduced yields and decreased quality of rice grains. Various techniques have been developed to determine the appropriate fertilizer for rice plants based on leaf color of their leaves. However, using specific algorithms to solve the illumination problem increases the computational process and still leaves the possibility of inaccurate image representation. In addition, the use of UAVs is very expensive, making their implementation difficult for farmers. Beside that, previous studies generally only classify Nitrogen status into low or high, fertile or infertile classes, whereas each fertilizer has different characteristics. Therefore, this study proposes a classification method of applying types of rice fertilizers based on vegetative microscopic images of rice leaves using the ResNet50 architecture. The proposed method uses Resnet50 architecture of Convolutional Neural Network to analyze microscopic rice leaf images and classify three types of rice fertilizers accurately, quickly and non-destructively

Development and evaluation of an electronic system for measuring the performance of ploughs: a comparative study of three types of ploughs

The aim of this study was to develop a cost-effective, accurate, and easy-to-install electronic system using the Arduino controller for measuring and recording key parameters of a tractor-implement system. The system was field-tested using three different plows (moldboard, chisel, and disc plow) in the silty clay soil of the College of Agriculture - University of Basra, Karma Ali site. The overall design of the system comprised two main components: the transmitter and the receiver. The transmitter system consisted of three sensors: an Encoder Sensor, an Ultrasonic sensor, and a Load Cell. This system wirelessly transmitted signals to the receiving electronic system using the HC-12 module. The receiving system was responsible for receiving the transmitted signals and automatically saving the data to a Micro SD Card. The designer specified a memory card with a capacity of at least 2GB.The results of the experiments demonstrated a high level of agreement between the depth of plowing measured by the ultrasonic sensor and the depth measured using traditional methods (R-Squared = 0.9978). Similarly, the actual and theoretical forward speed values measured by the encoder sensor closely matched those obtained through traditional methods (R-Squared = 0.9941 and 0.9986, respectively). These findings validate the accuracy and reliability of the device. Furthermore, the study revealed that at a forward speed of 0.51 m/sec and a plowing depth of 25 cm, the traction requirements for the moldboard, chisel, and disc plows were 14.3 kN, 11.25 kN, and 10.35 kN, respectively. The traction force increased by 72-75% and 45-50% when the plowing depth and forward speed were increased, respectively. The disc plow exhibited lower slip compared to the moldboard and chisel plows. Additionally, the study indicated that the tillage depth had a greater impact on slip percentage compared to the forward speed

INTER BASIN WATER TRANSFER FOR SUSTAINABLE AGRICULTURAL PRODUCTION SYSTEMS – A CASE STUDY OF PATTISEEMA LIFT IRRIGATION SCHEME OF ANDHRA PRADESH, INDIA: Inter basin water transfer-Pattiseema Lift Irrigation Scheme

Sustainability of agricultural production system in Krishna delta, which is at lower Krishna river basin (94% of utilizable flow), has been under threat post 2000 owing to basin closure, with available surface water fully utilized for human consumption. The Government of Andhra Pradesh contemplated for interlinking of Godavari river which has surplus water to the Krishna river by transferring 2265 Mm3 to alleviate the water scarcity and to stabilize command area under Krishna delta (0.514 M.ha) through Pattiseema Lift Irrigation Scheme (PLIS). The impact of PLIS on sustainability of agricultural production systems in Krishna delta has been studied.  The quantity of water transferred through PLIS were 1591.86, 2996.09, 274.65, 1217.55 and 1177.00 Mm3 that forms 43.92, 67.41, 63.33, 23.90 and 22.77% of the total water utilization through canal releases during the years 2016-17, 2017-18, 2018-19, 2019-20 and 2020-21, respectively with a net production advantage of 59.12, 258.08, 251.02, 93.36 and 93.36 million USD, respectively for the above crop years. Energy intensity per hectare of irrigated area was estimated at 459.81 kWh/ha and energy productivity and water productivity on production advantage was estimated as 3.63 kg/kwh and 345.52 kg/ha- Mm3. Benefit cost ratio of the project was estimated as 1.90

Determination of the physiochemical characteristics of hotel food waste and its biogas fuel potential in Nairobi City County, Kenya.: food waste, hotel, biogas, biomethane potential, Nairobi City County

Hotels are the source of large quantities of food waste, which can potentially be used for the generation of biogas for different applications, including agriculture. Thus, the purpose of this study was to investigate the physiochemical characteristics and biogas potential of the food waste generated by hotels in Nairobi City County, Kenya. To achieve this, a composition and physiochemical analysis of the feedstock were undertaken, which involved collecting and analysing a food waste sample of 130kg, which gives an accuracy the same as that of a 1000kg sample, according to the literature. In addition, the theoretical biomethane potential of food waste was determined using the Buswell and Carbon Balance equations, and the theoretical results were validated using anaerobic digestion experiments. The analysis showed that the fractions of different FW groups were fruits and vegetables (46%), roots and tubers (17%), meat and fish (14%), grains and cereals (9%), others (8%), bakery (4%), and tea and coffee (2%). The hotel food waste total solids, volatile solids, pH, COD, carbohydrates, and protein contents were determined to be 9.6%, 8.81%, 4.65, 142.3 g/L, 70%, and 13%, respectively. The C, H, O, N, and S compositions of the FW were 48.46%, 9.8%, 30.48%, and 2.2%, respectively.The test results showed that, based on these physiochemical characteristics, the hotel food waste had a theoretical methane yield of 643.07 mL/gVS and an experimental methane yield of 518.53 ± 9.69 mL/gVS. The experimental yield was almost equal to an average biomethane potential of food waste (i.e., 525.65 CH4 ml/gVS) based on the results of the other similar studies. Therefore, the hotel food waste can be used as an alternative feedstock for biogas generation if it is properly secured by, among other things, promoting onsite segregation of the hotel food waste

Effect of growth stage based water stress on yield and water use efficiency of tomato at tselemty district, Tigray, Ethiopia

Water availability is a strong challenge especially under water resource scarce areas. In water-scarce regions as is of Ethiopia, optimum yield and enhanced water use efficiency of crops can be obtained if best irrigation water management stategey is adopted .  The deficit irrigation practices become the main adopting policies for water saving. A two year field experiment  carried out at Maitebri Agricultural Research Center, Maitsebri experimental farm during 2020 and 2021 off seasons to find out the effect of growth stage based water stress on yield, yield parameters and water use efficiency of Tomato. Randomized complete block design (RCBD) with three replications used in the field trial. Three irrigation levels (100%, 50%, and 25% crop evapotranspiration) and FAO based four growth stages of tomato (initial,developmental, mid and late seasons) was considered as treatments. Data on marketable yield, other yield parameters  and crop water use efficiency (WUE) were recorded. Results showed us, reducing the full crop water requirement  up to 75% at development growth stage can severely reduce the marketable yield up to 66.5%. On the other hand, the highest in water use efficiency (9.2kgm-3) was obtained with reducing the full crop water requirement by 75% at the end growth stage of tomato. The lowest in water use efficiency (3.5kgm-3) was obtained from treatments that were irrigating 75% below the full crop-evapotranspiration at development growth stage. Generally, reducing irrigation water below 75%ETc during development growth stage of tomato can significantly influence the marketable, water use efficiency and yield parameters. Therefore, tomato crop is very sensitive to water stress beyond 50% of the full crop evapotranspiration (ETc) at its developmental growth stage

Comprehensive Analysis of Soil Physical Properties and their Relationships: Recommendations for Optimized Irrigation Strategies

This study aims to evaluate the soil physical properties in the Zobe Irrigation Area of Katsina State to determine the most suitable irrigation method for enhancing water use efficiency and crop yield. Soil samples were collected from six different locations and analysed for texture, bulk density, porosity, and water holding capacity. The results indicated that the soils are predominantly sandy loam, with an average sand content of 60.17%, silt 24.17%, and clay 15.7%. The mean bulk density was found to be 1.38 g/cm³, while the mean porosity was 47.67%. A strong negative correlation was observed between sand content and field capacity (-0.72), and a strong positive correlation between porosity and field capacity (0.983). Additionally, a strong negative correlation between bulk density and field capacity (-0.962) was identified, indicating that denser soils have lower water retention. Analysis within the soil profile revealed a decrease in sand content and bulk density with depth, and an increase in silt content and porosity. Based on these findings, drip irrigation is recommended as the most effective technique for the study area due to its ability to deliver water directly to the root zone, thus ensuring efficient water use and optimal moisture levels. Supporting studies confirm that drip irrigation maintains consistent soil moisture levels, crucial for maximizing plant available water capacity and promoting healthy plant growth. This research provides essential insights for developing climate-resilient irrigation strategies to support sustainable agriculture in semi-arid regions

A GIS-BASED ANALYTICAL HIERARCHY PROCESS MODELING FOR AGRICULTURAL-LAND SUITABILITY IN AWKA SOUTH LGA

This study aimed at performing a GIS-Based Analytical Hierarchy Process Modeling for agricultural land suitability in Awka South L.G.A. Its objectives of the study are to: establish the factors for agricultural land suitability in Awka South L.G.A; reclassify and standardize the factors for agricultural suitability; calculate the weights and consistency of the classified factors; and determine the most suitable areas for agriculture practices in the Awka South L.G.A. The methodological approach employed the assessment of factors in modelling and mapping agricultural suitability in Awka South L.G.A. This assessment was based on a wide range of criteria, including slope, elevation, soil, temperature, precipitation, drainage network, and landcover/landuse. The Analytic Hierarchy Process (AHP) was used to compare and determine the relative importance of these criteria through matrix comparisons. Subsequently, these criteria were assigned relative weights. To generate the final suitability map, a Weighted Overlay technique was applied, integrating the various suitability criteria maps. The findings revealed three distinct suitability zones for the area under study: high suitability, moderate suitability, and low suitability. High suitability encompassed an area of 33.324 km2, constituting 20.23% of the total coverage. The moderate suitability zone extended over 89.294 km2, representing a substantial 54.23% coverage. The low suitability zone covered 42.032 km2, accounting for 25.52% of the whole area. These delineations provide a comprehensive understanding of the distribution and extent of suitability within the study area. It was recommended that priority should be given to the development and intensification of agricultural activities in areas identified as High suitability zones. This zone represents prime agricultural land, and efforts should be directed towards maximizing productivity while implementing sustainable farming practice