ISCAN Multi Sensor Multi Parameter Soil Physical and Chemical Property Mapping System

Preface

Precision agriculture has been a hot topic in international agricultural scientific research in recent years, and it is also a new trend in the development of agriculture in the world today. Researchers hope to reduce production costs through the use of precision agriculture technology systems,Improve and stabilize the yield and quality of agricultural products,Increase economic income,Reduce environmental pollution.

The salt content, moisture content, organic matter content, soil compaction, texture structure, etc. in the soil all affect the changes in soil conductivity to varying degrees. By measuring soil conductivity, it can provide important basis for analyzing yield, evaluating soil production capacity, and formulating precise fertilization prescriptions. Traditional sample sampling surveys are not only time-consuming and labor-intensive, but also cannot truly reflect the spatiotemporal changes in soil characteristics of the plot due to low sampling density. For large-scale surveys, a towed soil conductivity measurement system combined with motor vehicles is undoubtedly the best choice.

iSCANUsed for large-scale soil conductivity（EC）Soil organic matter（OM）Soil temperature and moisture survey can be carried out by tractor or pickup truck for towing operations (with optional brackets), or installed on agricultural machinery such as seeders - completing the survey of agricultural land while farming operations, flexible and convenient; Among them, the upgraded versioniSCAN+Additional soil temperature and humidity sensors (temperature and humidity are important influencing factors for seed germination and emergence).

By conducting in-situ measurements of soil conductivity on siteECTheOMValue, temperature, and humidity values, utilizingGPSThe positioning and data processing surveying software (paid data processing service) can draw a distribution map of soil physical and chemical properties, comprehensively analyze and reflect soil texture, salinity, water holding capacity, cation exchange capacity, root depth, etc. Suitable for research demonstrations in precision agriculture, soil investigation, and carbon sequestration agriculture (estimation of soil carbon storage), as well as land management and land use planning.

2017-2018Year in the United States4Total of states15Block of land, utilizationiSCANThe system conducted a survey and compared it with handheld device data, obtaining very good linear correlation results.

The above picture shows Kansas40Exploration map of hectares of land parcels

Main Features

1. iSCANCan simultaneously survey soilECValueOMValue,iSCAN+Then there are additional soil surface temperature and humidity values

2. Field surveying: With the airborne system moving forward in the field, real-time conductivity and geographic coordinates (latitude and longitude) can be obtained, and each hectare can be measured120-240Sample point data

3. Direct contact measurement methodEC（Electrical Conductivity）The measurement is basically not affected by the surrounding electromagnetic field and does not require calibration, reflecting the characteristics of soil texture and salinity

4. VIS-NIRDual band spectral sensor, which can provide soil organic matter for data processing through a data processing centerOM（Organic Matter）Value, reflecting soil nitrogen mineralization, soil water infiltration, root growth, and soil water holding capacity

technical indicators

1. Dual bandVIS-NIRSensor, in situ mapping of spectral reflectance of lower soil layer under plant litter

2. Visible light wavelength:660nmNear infrared wavelength:940nm; Light source:LED

3. Spectral detector:5.76mmphotodiode

4. Except through dual bandVIS-NIRSpectral sensor high-density in-situ mapping and analysis of soilOMIn addition to the values and their distribution maps, they can be measured and plotted simultaneously at onceEC，iSCAN+Can be equipped with soil temperature and humidity sensors, and can record and display measurement data and distribution maps in real time

5. Garmin GPS 15X: DifferentialGPSPositioning accuracy, superior to3rice

6. electronic device:NMEA 4XSealed, military grade waterproof interface

7. Data collection:80 pin PICmicroprocessor,1HzAcquisition rate, backlit display, power supply12VDC，5A

8. Real time display of surveying softwareECValue and spectral reflection, and download geographic location information (latitude and longitude) and measurement values to the computer to automatically create a two-dimensional distribution map (spectral reflection needs to be processed and analyzed by the company's data processing center to form)SOMValue)

9. ECSurveying and mapping can form0－60cmSurface Soil Conductivity Mapping Map

10. OMMeasurement depth:38－76mm

11. Length: Agricultural Machinery Edition145cm; Dragged version259cm

12. Width: Agricultural Machinery Edition31cm;Dragged version127cm

13. Height:110cm

14. Weight:147 kg

15. Measurement speed: up to24km/hr

16. Operating Temperature-20－70°C

software interface

Place of Origin

the United States

Optional technical solutions

1) Optional crop phenotype analysis module, synchronously analyzing crop chlorophyll index, anthocyanin index, flavonoid index, andNElemental state, etc

2) Optional infrared thermal imaging for studying the effects of soil moisture and temperature changes on respiration

3) OptionalECODRONE®Unmanned aerial vehicle platform equipped with hyperspectral and infrared thermal imaging sensors for spatiotemporal pattern investigation and research

Partial references

1. Adamchuk, V.I., J.W. Hummel, M.T. Morgan, S.K. Upadhyaya. 2004. On-the-go soil sensors for precision agriculture. Comput. Electron. Agric. 44:71–91.

2. Christy, C.D. 2008. Real-Time Measurement of Soil Attributes Using On-the-go Near Infrared Reflectance Spectroscopy. Computers and Electronics in Agriculture. 61:1. pp.10-19

3. Kitchen, N.R., S.T. Drummond, E.D. Lund, K.A. Sudduth, G.W. Buchleiter. 2003. Soil electrical conductivity and other soil and landscape properties related to yield for three contrasting soil and crop systems. Agron. J. 95:483–495.

4. Kweon, G., E.D. Lund, and C.R. Maxton. 2013. Soil organic matter and cation-exchange capacity sensing with on-the-go electrical conductivity and optical sensors. Geoderma 199:80–89.

5. Lund, E.D. 2008. Soil electrical conductivity. p.137-146. In: S. Logsdon et al. (ed.) Soil Science Step by Step Field Analysis. SSSA, Madison, WI.

6. Lund, E.D., C.R. Maxton, T.J. Lund. 2015. Assuring data quality and providing actionable maps using a multi-sensor system. Proceedings of Global Workshop on Proximal Soil Sensing. Hangzhou China. 266-278.

7. Eric Lund, Chase Maxton. 2019. Comparing Organic Matter Estimations Using Two Farm Implement Mounted Proximal Sensing Technologies. 5TH GLOBAL WORKSHOP ON PROXIMAL SOIL SENSING. P35-40.

8. IfisPaulo Molin, Tiago Rodrigues Tavares. 2019. SENSOR SYSTEMS FOR MAPPING SOIL FERTILITY ATTRIBUTES: CHALLENGES, ADVANCES, AND PERSPECTIVES IN BRAZILIAN TROPICAL SOILS. Eng. Agryc. vol.39.