Unit 6 Proximal Soil and Crop Sensing - PDF

29/10/2024 AGRIC 108 UNIT 6 Proximal Soil & Crop Sensing and Soil Variability Measurements & Management Topic Outline: A.Introduction to proximal sensing systems B.Emerging techniques in soil a...

29/10/2024 AGRIC 108 UNIT 6 Proximal Soil & Crop Sensing and Soil Variability Measurements & Management Topic Outline: A.Introduction to proximal sensing systems B.Emerging techniques in soil and plant sensing C.Sources of soil variability D.Soil sampling strategies for SSNM E.Zone mapping tools 1  29/10/2024 A. Introduction to proximal sensing systems  Proximal sensing involves the use of sensors in close proximity to the plants, such as on a tractor or harvester or ground-based robot. A. Introduction to proximal sensing systems Types of Sensor Deployment: On-the-Go Moved across the field using tractor, ATV, pick-up, planter, sprayer, or combine These systems can record yields, crop and soil properties as well as field elevation, when using high- accuracy GNSS receivers 2  29/10/2024 A. Introduction to proximal sensing systems Types of Sensor Deployment: Stop-and-Go A sensor platform to remain stationary while the measurements are collected. Provide detailed information of specific field locations defined by the user and typically have lower mapping density as compared to on-the-go systems. Soil cone pentometer A. Introduction to proximal sensing systems Types Proximal Sensing System: In Situ The sensor measures soil or crop properties in place. A good example is a soil moisture or temperature sensor that is buried in the soil. e.g., Soil sensors buried in the soil 3  29/10/2024 A. Introduction to proximal sensing systems Types Proximal Sensing System: Ex Situ Sensors require placement of soil or plant material in contact with the sensing element while moving to the next sampling location. e.g., soil core field scanners A. Introduction to proximal sensing systems Proximal Sensors Energy Source: Active A proximal soil sensor that produces its own energy from an artificial source for its measurements Passive It is passive if it uses naturally occurring radiation from the sun or earth. 4  29/10/2024 A. Introduction to proximal sensing systems I. Proximal Soil Sensing System: The physical principles used to measure soil properties in field conditions can be separated into several categories including: 1. electrical and electromagnetic sensors that include most geophysical tools, 2. optical and radiometric sensors that cover different parts of the electromagnetic spectrum, 3. Mechanical sensors - sensors that rely on mechanical interactions between sensors and soil, and 4. Electrochemical sensors that directly measure the activity of specific ions or molecules A. Introduction to proximal sensing systems Electrical Resistivity/Conductivity Sensing:  Soil ECa can be a strong indicator of soil media composition. First, this is an excellent tool to delineate field areas containing relatively high salinity levels.  In many instances, soil EC a maps have been used to accurately define soil series boundaries and indirectly predict the physical, as well as some chemical, soil attributes using site-specific relationships. 5  29/10/2024 A. Introduction to proximal sensing systems How does soil EC relate to soil properties? A. Introduction to proximal sensing systems Ground Penetrating Radar:  Ground penetrating radar (GPR) uses the transmission and reflection of very high and ultra-high frequency (30 MHz to 1.2 GHz) electromagnetic waves to measure variations in the soil properties as well as subsurface objects, and voids and cracks.  Ground penetrating measurements are also non-invasive, and the sensors can measure the soil water content of relatively large volumes of soil. 6  29/10/2024 A. Introduction to proximal sensing systems Visible, Near-infrared, and Mid-infrared Spectrometry  There is widespread use of diffuse reflectance spectroscopy with visible (390 to 700 nm), NIR (700 to 2500 nm) and MIR (2500 to 25,000 nm) ranges to measure soil properties.  Because the technique is rapid, nondestructive, less labor- intensive, and cost-effective when compared to routine chemistry measurements. A. Introduction to proximal sensing systems Sensing Mechanical Impedance  Proximal soil sensors measures the mechanical interaction between the sensor and the soil. 7  29/10/2024 A. Introduction to proximal sensing systems Sensing Mechanical Impedance  Two basic approaches o The first approach measures the amount of energy required to pull an implement through the soil. o The second approach measures the resistance of the soil to insertion of a probe (penetration resistance)  Measures several soil properties (compressibility, shear strength) A. Introduction to proximal sensing systems Ion-selective Electrodes and Ion-selective Field Effect Transistors  Ion-selective potentiometric sensors (most popular electrochemical sensors) use a modified traditional laboratory method to determine chemical soil properties, such as pH, or nutrient content.  The real-time chemical extraction of the ions mimics conventional soil analysis procedures. 8  29/10/2024 A. Introduction to proximal sensing systems Families of proximal soil sensing: A. Introduction to proximal sensing systems II. Proximal Plant Sensing System: The grown crop is another indicator of soil characteristics, which interact with agro-climatic conditions and management. Plant sensing is essential for early detection and alleviation of crop stress. Crop canopy sensing system that utilizes crop canopy reflectance, ultrasonic and infrared thermal sensors. 9  29/10/2024 A. Introduction to proximal sensing systems Crop Canopy Reflectance and Fluorescence  As the canopy develops, reflectance in the visible spectrum is reduced while NIR reflectance increases.  Therefore, measurement of crop canopy reflectance in visible and near-infrared parts of the spectrum can be associated with a number of physiological plant properties. A. Introduction to proximal sensing systems Crop Canopy Reflectance and Fluorescence Chlorophyll florescence and meter instruments 10  29/10/2024 A. Introduction to proximal sensing systems How do crop canopy sensors works? ` A. Introduction to proximal sensing systems III. Other sensors 1. Mechanical sensor - Must be in direct contact with the plant to measure mechanical changes within the sensor caused by plants. 2. Thermal Sensors - measuring absolute temperature or relative temperature (differences). 3. Acoustic Sensors - the reflection of sound is captured by microphones to determine the distance and the direction of a reflector. 11  29/10/2024 B. Emerging Techniques in Soil and Plant Sensing I. Laser light backscattering image analysis  Evaluates the spatial distribution of scattered laser light after passing through tissue. These transflective images provide information about fruit quality (Ji and Zude, 2007) and fungal infection (Lorente et al., 2015). laser-light backscattering imaging and computer vision for rapid determination of oil palm fresh fruit bunches maturity B. Emerging Techniques in Soil and Plant Sensing II. Laser induced breakdown spectroscopy (LIBS)  It is used to assess elemental composition of a sample by analyzing optical spectra of a plasma, created by a high energy laser impulse.  LIBS was used to detect relevant elements like K, P, Mg and Ca in plants and soils (Pouzar et al., 2009). 12  29/10/2024 B. Emerging Techniques in Soil and Plant Sensing III. X-ray fluorescence (XRF) spectroscopy  Analytical technique that uses x-rays to determine the elemental composition- major and minor elements and some trace elements  Portable XRF spectrometers are commercially available that can be used for in situ analysis of soils and crops.  If applied directly to fresh leaves, adjustment for leaf thickness and water content is required. B. Emerging Techniques in Soil and Plant Sensing IV. Raman spectroscopy  Able to discriminate many complex molecules, including primary and secondary plant metabolites, like proteins, lipids, carbohydrates, flavonoids, and alkaloids, (Schulz and Baranska, 2007) as well as phosphate and other molecules in soils. 13  29/10/2024 B. Emerging Techniques in Soil and Plant Sensing V. Capillary electrophoresis  Based on the separation of dissolved ions in an electric field applied to a liquid soil extract filled in a capillary. Separated based on charge and size  Capillary electrophoresis is a common method in the lab. However, portable systems are relatively recent development (Smolka et al., 2016). B. Emerging Techniques in Soil and Plant Sensing VI. Nuclear magnetic resonance spectroscopy (NMR)  It is based on the magnetic resonance between the nucleus of an atom and an external magnetic field. It identifies, and in many cases quantifies the chemical forms of the target nuclei (Kizewski et al., 2011).  A mobile NMR spectrometer was developed for analyzing nitrogen phosphorus, and potassium content of animal slurry on a manure applicator (Sørensen et al., 2015). 14  29/10/2024 B. Emerging Techniques in Soil and Plant Sensing VI. Gas sensors  It gained some interest for detecting acetylene, which is emitted by plants under unfavorable conditions such as drought or fungal infections.  While acetylene is an unspecific stress indicator, it is known that plants and infecting fungi emit a number of other molecules. B. Emerging Techniques in Soil and Plant Sensing VI. Gas sensors CO2 Controller Gas Meter, NDIR CO2 Sensor for Grow Room Greenhouse  It gained some interest for detecting acetylene, which is emitted by plants under unfavorable conditions such as drought or fungal infections.  While acetylene is an unspecific stress indicator, it is known that plants and infecting fungi emit a number of other molecules.  NDIR - nondispersive infrared, the most common type of sensor used to measure CO2  NDIR sensors work by using an infrared (IR) lamp to direct waves of light through a tube filled with a sample of air that moves toward an optical filter in front of an IR light detector, that measures the amount of IR light that passes through the optical filter. 15  29/10/2024 C. Sources of Soil Variability Variability can result from many factors: 1. Inherent differences produced during soil development 2. The result of erosion following tillage, and 3. Errors from uneven application of fertilizers and manures (Franzen, 2011). C. Sources of Soil Variability Original Soil Development  The live soil forming factors (Jenny, 1941) are parent material, vegetation, climate, topography and time.  Parent material differences are often the reason for crop productivity differences 16  29/10/2024 C. Sources of Soil Variability Salinity  Salinity is a worldwide problem. It has been estimated that by 2150, 50% of arable lands will have salt limitations for crop production (Jamil et al., 2011). C. Sources of Soil Variability Salinity  Excessive salinity reduces crop productivity due to its effect on water uptake and nutrient utilization. Large areas of salinity have prevented crop production in some regions.  Sometimes, salinity develops along the edge of drainage ditches, whereas in other fields it occurs along the margins of wet areas, or from seeps. 17  29/10/2024 C. Sources of Soil Variability Erosion  With the loss of topsoil, crops often have a greater reliance on fertilizers and tillage to maintain and increase production.  Problems such as crusting and susceptibility to drought and adverse weather fluctuations have increased these problems C. Sources of Soil Variability Systematic Variability  Systematic variability is non-natural soil variability due to the activities of human.  Application of fertilizers and manures can result in systematic variability 18  29/10/2024 C. Sources of Soil Variability Systematic Variability  Examples: o application of fertilizer and/ or manure either too close, resulting in increased nutrient content in strips in the direction of travel o application of fertilizer and/or manure too far between passes, leaving untreated strips of soil between wider strips of applied nutrients. o hydraulic oil pressure problems on the fertilizer and/or manure applicator that reduces the ability of the fertilizer applicator to fling fertilizer and/or manure the usual distance from the center of the applicator D. Soil Sampling Strategies for Site-Specific Nutrient Management Grid Sampling  Soil sampling strategies for site- specific nutrient management are based on grid sampling or zone sampling.  The grid sampling philosophy is based on the assumption that nutrient levels are random, unrelated to anything in nature, and should be sampled without any sampler bias toward where to place the sample locations. 19  29/10/2024 C. Sources of Soil Variability Grid Sampling  Grid sampling strategies: 1. Random sampling Random sampling might be appropriate in a field with no recent history of fertilization or manure C. Sources of Soil Variability Grid Sampling  Grid sampling strategies: 2. Random clustered sampling Might help compensate for small- scale variability and larger-scale variability by grouping two to three sample core composites around random points. 20  29/10/2024 C. Sources of Soil Variability Grid Sampling  Grid sampling strategies: 3. Regular systematic grid sampling Regular systematic was a common grid sampling approach in the era before GPS (global positioning system) receivers. C. Sources of Soil Variability Grid Sampling  Grid sampling strategies: 4. Staggered start (or triangular, or diamond) Recognized that systematic errors in one direction are possible, and the start and end of each sampling rank was off set to try to compensate for these errors in one direction. 21  29/10/2024 C. Sources of Soil Variability Grid Sampling  Grid sampling strategies: 5. Systematic unaligned grid sampling This approach minimizes the effects of systematic errors in two directions. The systematic unaligned grid is probably the method most used by commercial grid samplers today. C. Sources of Soil Variability Zone Sampling  Zone sampling philosophy assumes that nutrient levels and the patterns in which they appear in a field are the result of some logical reason. 22  29/10/2024 C. Sources of Soil Variability Zone Sampling vs Grid Sampling D. Zone Mapping Tools 1. Topography  Topography influences crop productivity and nutrient availability to crops.  The obvious affect is the thickness of A-horizon (the organic rich layer at the soil surface). 23  29/10/2024 D. Zone Mapping Tools 1. Topography  Topography is difficult to define within a GIS program. Use of watershed definition tools can be used as a proxy.  Relative elevation may be acquired with a high-resolution GPS receiver, although altitude contains three times the amount of error as latitude and longitude in these instruments.  Some regions have access to LIDAR data, which is highly useful in zone development using topography D. Zone Mapping Tools 2. Satellite Imagery  Satellite imagery has the advantage of obtaining large tracts in a single image.  However, satellite imagery always has the disadvantage of cloud interference (Bu et al., 2017).  As a nutrient management zone delineation tool, an archived image may be acceptable. The image should come from a vegetative season of crop development 24  29/10/2024 D. Zone Mapping Tools 3. Aerial Imagery  Aircraft and UAV’s use in zone delineation and aerial imagery  The technology of UAV’s is rapidly developing and it is possible that the use of imagery from these devices will become easier to manage in the near future. D. Zone Mapping Tools 4. Electrical Conductivity  Soil clay content, moisture content, nutrient levels and soluble salts contribute to different electrical conductivity (EC) readings. 25  29/10/2024 D. Zone Mapping Tools 5. Electromagnetic Sensors  Electromagnetic (EM) sensors measure the capacity to measure changes in the soils ability to conduct and accumulate electrical charge (Chapter 9; Adamchuk et al., 2018).  Electromagnetic sensors have been used to map the depth of a clay limiting layer An electromagnetic (EM) map showing the apparent electrical conductivity (ECa) of a saline field trial site D. Zone Mapping Tools 6. Multiyear Yield Maps  To be most useful, several years of yield maps should be integrated into a multiyear yield map (Franzen et al., 2008; Chapter 5, Fulton et al., 2018) 26  29/10/2024 D. Zone Mapping Tools How can yield maps aid with soil sampling? 27