Smart Agriculture

Soil and plant sensing and Monitoring Maximize Agricultural Productivity, also,  enables farmers, producers and advisors to analyze nutrients in soil and plants. The in a fast, affordable and reliable way.  Our compact handheld pXRF and pNIR are fast and affordable reliable mobile sensors to test for moisture and nutrients. The handheld pXRF pNIR, p can test in the field and in real time soil moisture, micro nutrients and macro nutrients.

Point Shoot and test for nutrients content and moisture 

 The portable technology of the pXRF and pNIR contains a light source. The source for the pXRF is a gamma ray and for pNIR or near infrared wavelengths are commonly generated by lasers and LEDs (light-emitting diodes) spectrometer on a chip. The real game changer is however the combination of the device and the database in the cloud. The scans from the Scanner are compared with the data in the cloud and  recommendations are given via your smartphone.  

Onsite Plant and Soil Analysis

The ease of testing (both solids and liquids), rapidity, accuracy of results, and non-destructive nature of x-ray fluorescence (XRF) near infrared (NIR) has made it an important analytical tool for diverse matrices – food, soil, and plant. The XRF and NIR has been coupled with global-positioning system (GPS) for mapping of soil pollution. Although XRF has been used in research, this promising technology for practical agricultural applications on a simple-to-use platform for producers and their crop consultants and when integrated with a Decision Support System (DSS) to provide information for farming decisions of nutrients and management of the crops. 

The available NOx, NH3, and orthophosphate ions (H2PO4–, HPO42-) is measured via a colorimetric spectroscopic sensor on a microplate platform to facilitate easy and simultaneous multi-sample analyses. While the N speciation for soil samples as determined using vibrational spectroscopy methods may not be reliable, the disaggregation of total N into total Kjedahl N, nitrite-N, and nitrate-N. The importance of the quantification of nitrate-N fraction, is directly related to the availability for crop uptake, Also, this fraction is highly susceptible to leach to groundwater. These determination of the available NOx, NH3 will r be pursued using the microplate spectrophotometer system. 

 Decision Support System (DSS) facilitate data management incorporating an optimization model, accounting for local meteorological and economic parameters, to provide a cost-effective and actionable set of recommendations. This DSS will mimic the decision-making of a farmer, who would want to maximize their profit, allowing for any constraints, including crop needs, short-term resource limitations for farm activities, environmental restrictions etc. It will be available on a smartphone/tablet or similar user interface with internet access. The DSS can be used in an iterative manner to afford precise farm management. The DSS include a farmer/server system  (i.e., topology, area, tilling practices, nutrient management plan) with 1) a dynamic soil-plant-environment database to store and organize collected data, 2) a dynamic economic and logistic farm-specific database, 3) an optimization system based on large-scale mixed integer programming, and 4) an intuitive interface. 

 Raw field data will be extracted from the sensing devices via standard connections. This data, along with model results, raw spectral data, and any intermediate data processing results will be stored on a remote server. Both raw data and post-processed data will be stored in the database to enable any future algorithm improvements. These multiple models with multiple runs each can provide a sense of the model and climate uncertainty present.  Large production fields from farmers will be used over two cropping seasons to test the proposed sensing and monitoring approach. These locations represent a wide range of soil types and cropping conditions that reflect a significant portion of the private agricultural production regions. Collected soil and biomass samples will completely analyze. Farmers use these analyses to determine the availability of nutrients in soils to their crops and the uptake by the biomass.  Crop response will be assessed by collecting yield information with harvesting equipment mounted with yield monitors and scales. The location of each soil and crop-sampling site will be georeferenced. In-field data will be integrated with the DSS to evaluate the overall performance of our system. 

  Raw field data will be extracted from the sensing devices via standard connections. Once extracted from the devices, the data will be processed into a JSON file, which can be easily imported into the PostgreSQL database.