Variable Rate Irrigation technology (VRI) has the potential to reduce water use in agriculture and increase overall efficiency in water management. Nonetheless, in order to fully leverage its potential, the end-users must have access to irrigation scheduling maps.

Using a Pivot-mounted microwave radiometers, Volumetric Water Content (VWC) maps can be created instead of point dataset. While the pivot is moving, the radiometers interpret the microwave emissivity of the top 50 cm of the soil to produce Brightness Temperature (TB) maps.

Three microwave radiometers have been mounted on a 70 acres irrigation pivot equipped with a VRI system at the Lethbridge College Demo Farm. The accuracy of the microwave radiometers has been tested under two irrigation treatments (100% and 50% applications) and on three different crops (potato, wheat, and sugar beet).

A linear regression model was used to describe the empirical relationship between the TB and the VWC profile at different depths 15, 30 and 50 cm. The VWC profiles were obtained from monitoring stations equipped with fixed moisture sensors and weekly surveys with portable VWC probes.

According to the findings, the Radiometer can differentiate between dry and wet plots. However, the estimating the absolute values of VWC requires enhancement. there exists a linear correlation between the TB and VWC with a coefficient of determination of 0.59.

The potential of this project is to develop a practical method to create field-scale maps of plant available water by combining observations of VWC with the soil and water retention characteristics of the field.

Plant growth and development mainly depend on the soil's mineral nutrient composition and concentration. Due to their immobility, plants may not obtain adequate supply of specific nutrients. As such, foliar application of certain nutrients such as boron is done during the growing season to compensate for any possible deficiency and enhance potato production. Currently, analyzing plant tissue is done at external laboratories based on petiole chemical testing whose results take nearly two weeks to reach the grower, hence the decision to spray is based solely on the grower’s experience. Therefore, this research aims to develop a machine learning model to determine the levels of sufficiency and deficiency of boron based on its contents in petioles and relating them to leaf reflectance. We collected samples from three locations in New Brunswick to create a dataset of 98data points, each of which, consists of 50-70 petioles and their tip leaves. The leaves were scanned using a Vis-NIR spectrophotometer that covers the range of 400-2500 nm, whereas the chemical analysis is done at the laboratory, whose guidelines divide the boron status into 3 categories, excessive, sufficient, and deficient. The datasets for machine learning were arranged based on this categorization. Next, neural networking classification will be conducted to find out the possibility of sensing the boron status using spectral reflectance. The ability to get this information using a sensor will provide the nutrient status in a timely manner so that foliar application of boron is decided on the basis of data instead of guessing.

Autonomous agriculture is a subset of the broader precision agriculture movement, the practice of utilizing technology and equipment to farm more efficiently. Autonomous and precision advancements can save producers time, energy, costs, and provide valuable detailed data. Since 2020, Olds College of Agriculture & Technology has operated the OMNiPOWER autonomous platform with three implements (Seedmaster 30 ft Air Seeder, Pattison 120 ft Sprayer, New Leader 90 ft Fertilizer Spreader) as part of a 3.5 year study of the technical, economic, environmental, and logistical factors associated with operating autonomous farm equipment on the Canadian Prairies. OMNiPOWER was digitally monitored using an on-board data acquisition system (somat e-DAQ) providing CANBUS and geographic data at a rate of 2 Hz. This amounted to a robust dataset allowing users to trace progress (tracking fuel consumption and field efficiency), identify temporal/spatial points of interest, provide reasoning for downtime, calculate hands-off operational time, among other insights. 2022 OMNiPOWER operational outcomes were seeding (7.6 ac/hour), spraying (44.3 ac/hour), and spreading (31.4 ac/hour), covering 7000 acres, achieving a maximum uninterrupted autonomous operating time of 5 hours, and totalling 155 autonomous hours over the season. During the 2022 season, autonomous operation was compared to conventional operations to determine and compare economic and environmental differences. Furthermore, building upon the concept of field efficiency, other coverage planning characteristics were assessed for autonomous and conventional operations in 2022: route efficiency (based on theoretical field capacity), route planning for irregularly shaped terrains, and isoperimetric quotient.

Various published data show the amount of crop residue available in India may range from a low of 90 to a high of 180 million tonnes. One immediate short term use of the residue is to replace 5-7% of the 670 million tonnes of coal India currently consumes to generate power. The estimated biomass tonnage would range from 33.5 million to 47.5 million tonnes annually. The resulting reduction in GHG would exceed 100 million tonnes. The farmers will benefit from the sale of their excess crop residue to power plants while reducing pollution due to crop burning. The challenge is to mobilize the crop residue collection and delivery to ensure a robust and sustainable supply chain. The data and calculations in this monogram show that it is economical for the famer to remove the crop residue from the field quickly by using modern balers, to pelletize the biomass in small scale distributed pellet plants, to store pellets in the modern steel bins and to de-liver the pellets to coal plants using rail transport. The delivered cost is estimated around Rp 6.78/kg. The Government of India encourages the power plants to pay at least Rp 10/kg for the de-livered biomass. The critical components of the proposed supply chain are discussed in this monogram.