Progress 09/01/21 to 08/31/24
Outputs
Target Audience:The addressable market for our product is the broader agricultural testing market, which will be worth $6.29 Billion by 2022. In the US, 2 million farms cover an area of 922 million acres (i.e., an average of 420 acres per farm). Using the range (1 sample/acre to 40 samples/acre (in precision agriculture)), and a once in 3 years soil assessment assumption, we estimate that the number of soil tests required to reach 10% of the US farms ranges from 30 million to 1.2 billion per year. Our market audiences include several large food & beverage companies, experts at the Rutgers University soil-testing laboratory, the experts at the Northeast Organic Farming Association (NOFA) of NJ, etc. Our customers are independent growers, soil consultants, precision agriculture (PA) equipment manufacturers, and food & beverage companies. Our primary go-to-market strategy is to tap into the resources of organizations like NOFA and regional soil-testing laboratories to market directly to our prospective customers. Organizations like NOFA interact closely with growers and are advocates of proactive soil management. Regional soil testing laboratories will be a source of region-specific ground-truth data for our product, and we will forge win-win relationships with them. As our product primarily supports precision agriculture and intense spatiotemporal soil analysis, it is not a substitute for the highly accurate soil analyses conducted at the regional soil laboratories. Hence, the regional soil testing laboratories and organizations like NOFA and NJ Farm Bureau can be great channel partners for our product. Given the emergence of many new technology startups in precision agriculture, organizations like NOFA are ready to collaborate with budding companies (see support letter). We will leverage such opportunities to educate a larger pool of end users for our product. Changes/Problems:Our progress has been severely hampered by supply chain issues surrounding the availability of sensor hardware, spare parts, and electronic chips. This is due to the post-COVID supply chain problems. We worked with several sensor vendors to address this problem What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Up-to-date information on soil properties and the ability to track changes in soil properties over time are critical for improving multiple decisions on soil security at various scales, ranging from global climate change modeling and policy to national-level environmental and development planning to farm and field-level resource management. Diffuse reflectance infrared spectroscopy has become an indispensable laboratory tool for the rapid estimation of numerous soil properties to support various soil mapping, soil monitoring, and soil testing applications. Recent advances in hardware technology have enabled the development of handheld sensors with similar performance specifications as laboratory-grade near-infrared (NIR) spectrometers. We compiled a hand-held NIR spectral library (1350-2550 nm) using the NeoSpectra Handheld NIR Analyzer developed by Si-Ware. Each scanner is fitted with Fourier-Transform technology based on the semiconductor Micro Electromechanical Systems (MEMS) manufacturing technique, promising accuracy and consistency between devices. This library includes 2,106 distinct mineral soil samples scanned across 9 of these portable low-cost NIR spectrometers (indicated by serial no). 2,016 of these soil samples were selected to represent the diversity of mineral soils found in the United States, and 90 samples were selected across Ghana, Kenya, and Nigeria. 519 of the US samples were selected and scanned by Woodwell Climate Research Center. These samples were queried from the USDA NRCS NSSC-KSSL Soil Archives as having a complete set of eight measured properties (TC, OC, TN, CEC, pH, clay, sand, and silt). They were stratified based on the major horizon and taxonomic order, omitting the categories with less than 500 samples. Three percent of each stratum (i.e., a combination of major horizon and taxonomic order) was then randomly selected as the final subset retrieved from KSSL's physical soil archive as 2-mm sieved samples. The remaining 1,604 US samples were queried from the USDA NRCS NSSC-KSSL Soil Archives by the University of Nebraska - Lincoln to meet the following criteria: Lower depth <= 30 cm, pH range 4.0 to 9.5, Organic carbon <10%, Greater than lower detection limits, Actual physical samples available in the archive, Samples collected and analyzed from 2001 onwards, Samples having complete analyses for high-priority properties (Sand, Silt, Clay, CEC, Exchangeable Ca, Exchangeable Mg, Exchangeable K, Exchangeable Na, CaCO3, OC, TN), & MIR scanned. All samples were scanned dry 2mm sieved. ~20g of sample was added to a plastic weighing boat where the NeoSpectra scanner would be placed down to make direct contact with the soil surface. The scanner was gently moved across the surface of the sample as 6 replicate scans were taken. These replicates were then averaged so that there was one spectra per sample per scanner in the resulting database. Calibration models were developed using the spectral data collected. On the hardware side, we designed and developed electronic boards to interface with the portable NIR sensors to enable automated data gathering on demand. We also developed the back-end software and user interface to enable end users to operate the sensors remotely (via a browser-based application). Our work lays the foundation for a robust prototype for an insitu soil samples testing sensor.
Publications
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Progress 09/01/22 to 08/31/23
Outputs
Target Audience:The addressable market for our product is the broader agricultural testing market, which will be worth $6.29 Billion by 2022.In the US, 2 million farms cover an area of 922 million acres (i.e., an average of 420 acres per farm). Using the range (1 sample/acre to 40 samples/acre (in precision agriculture)), and a once in 3 years soil assessment assumption, we estimate that the number of soil tests required to reach 10% of the US farms ranges from 30 million to 1.2 billion per year. Our market audiences include several large food & beverage companies, experts at the Rutgers University soil-testing laboratory, the experts at the Northeast Organic Farming Association (NOFA) of NJ, etc. Our customers are independent growers, soil consultants, precision agriculture (PA) equipment manufacturers, and food & beverage companies. Our primary go-to-market strategy is to tap into the resources of organizations like NOFA and regional soil-testing laboratories to market directly to our prospective customers. Organizations like NOFA interact closely with growers and are advocates of proactive soil management. Regional soil testing laboratories will be a source of region-specific ground-truth data for our product, and we will forge win-win relationships with them. As our product primarily supports precision agriculture and intense spatiotemporal soil analysis, it is not a substitute for the highly accurate soil analyses conducted at the regional soil laboratories. Hence the regional soil testing laboratories and organizations like NOFA and NJ Farm Bureau can be great channel partners for our product. Given the emergence of many new technology startups in precision agriculture, organizations like NOFA are ready to collaborate with budding companies (see support letter). We will leverage such opportunities to educate a larger pool of end users for our product. Changes/Problems:Our progress has been severely hampered by supply chain issues surrounding the availability of sensor hardware, spare parts, and electronic chips. This is due to the post-COVID supply chain problems. We are working with several sensor vendors to address this problem. What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?1. We will build models to predict plant extractable nutrients using portable NIR and VIS sensors; 2. We will integrate the portable NIR and VIS sensors into our penetrometer prototype and demonstrate the measurement of soil properties in the field; 3. We will develop the in-situ soil sampling and measurement hardware which requires no sample prep, and demonstrate insitu soil properties measurement capabilities.
Impacts
What was accomplished under these goals?
Up-to-date information on soil properties and the ability to track changes in soil properties over time are critical for improving multiple decisions on soil security at various scales, ranging from global climate change modeling and policy to national-level environmental and development planning to farm and field-level resource management. Diffuse reflectance infrared spectroscopy has become an indispensable laboratory tool for the rapid estimation of numerous soil properties to support various soil mapping, soil monitoring, and soil testing applications. Recent advances in hardware technology have enabled the development of handheld sensors with similar performance specifications as laboratory-grade near-infrared (NIR) spectrometers. Wecompiled a hand-held NIR spectral library (1350-2550 nm) using the NeoSpectra Handheld NIR Analyzer developed bySi-Ware. Each scanner is fitted with Fourier-Transform technology based on the semiconductor Micro Electromechanical Systems (MEMS) manufacturing technique, promising accuracy and consistency between devices. This library includes 2,106 distinct mineral soil samples scanned across 9 of these portable low-cost NIR spectrometers (indicated by serial no). 2,016 of these soil samples were selected to represent the diversity of mineral soils found in the United States, and 90 samples were selected across Ghana, Kenya, and Nigeria. 519 of the US samples were selected and scanned byWoodwell Climate Research Center. These samples were queried from theUSDA NRCS NSSC-KSSL Soil Archivesas having a complete set of eight measured properties (TC, OC, TN, CEC, pH, clay, sand, and silt). They were stratified based on the major horizon and taxonomic order, omitting the categories with less than 500 samples. Three percent of each stratum (i.e., a combination of major horizon and taxonomic order) was then randomly selected as the final subset retrieved from KSSL's physical soil archive as 2-mm sieved samples. The remaining 1,604 US samples were queried from the USDA NRCS NSSC-KSSL Soil Archives by theUniversity of Nebraska - Lincolnto meet the following criteria: Lower depth <= 30 cm, pH range 4.0 to 9.5, Organic carbon <10%, Greater than lower detection limits, Actual physical samples available in the archive, Samples collected and analyzed from 2001 onwards, Samples having complete analyses for high-priority properties (Sand, Silt, Clay, CEC, Exchangeable Ca, Exchangeable Mg, Exchangeable K, Exchangeable Na, CaCO3, OC, TN), & MIR scanned. All samples were scanned dry 2mm sieved. ~20g of sample was added to a plastic weighing boat where the NeoSpectra scanner would be placed down to make direct contact with the soil surface. The scanner was gently moved across the surface of the sample as 6 replicate scans were taken. These replicates were then averaged so that there was one spectra per sample per scanner in the resulting database. Calibration models were developed using the spectral data collected. On the hardware side, we designed and developed electronic boards to interface with the portable NIR sensors to enable automated data gathering on demand. We also developed the back-end software and user interface to enable end users to operate the sensors remotely (via a browser-based application). Our worklays the foundation for a robust prototype for an in-situ soil samples testing sensor.
Publications
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Progress 09/01/21 to 08/31/22
Outputs
Target Audience:The addressable market for our product is the broader agricultural testing market which will be worth $6.29 Billion by 2022 (15). In the US, 2 million farms cover an area of 922 million acres (i.e., an average of 420 acres per farm). Using the range (1 sample/acre to 40 samples/acre (in precision agriculture)), and a once in 3 years soil assessment assumption, we estimate that the number of soil tests required to reach 10% of the US farms ranges from 30 million to 1.2 billion per year. Our market audiences include several large food & beverage companies, experts at the Rutgers University soil-testing laboratory, the experts at the Northeast Organic Farming Association (NOFA) of NJ, etc. Our customers are independent growers, soil consultants, precision agriculture (PA) equipment manufacturers, and food & beverage companies. Our primary go-to-market strategy is to tap into the resources of organizations like NOFA and regional soil-testing laboratories to market directly to our prospective customers. Organizations like NOFA interact closely with growers and are advocates of proactive soil management. Regional soil testing laboratories will be a source of region-specific ground-truth data for our product, and we will forge win-win relationships with them. As our product primarily supports precision agriculture and intense spatiotemporal soil analysis, it is not a substitute for the highly accurate soil analyses conducted at the regional soil laboratories. Hence the regional soil testing laboratories and organizations like NOFA and NJ Farm Bureau can be great channel partners for our product. Given the emergence of many new technology startups in precision agriculture, organizations like NOFA are ready to collaborate with budding companies (see support letter). We will leverage such opportunities to educate a larger pool of end users for our product. Changes/Problems:Our progress has been severely hampered by supply chain issues surrounding the availability of sensor hardware, spare parts, and electronic chips. This is due to the post-COVID supply chain problems. These problems will likely result in our application for a no-cost extension for this project. What opportunities for training and professional development has the project provided?
Nothing Reported
How have the results been disseminated to communities of interest?
Nothing Reported
What do you plan to do during the next reporting period to accomplish the goals?1. We will build models to predict plant extractable nutrients using portable NIR and VIS sensors; 2. We will integrate the portable NIR and VIS sensors into our penetrometer prototype and demonstrate the measurement of soil properties in the field; 3. We will develop the in-situ soil sampling and measurement hardware which requires no sample prep, and demonstrate in-situ soil properties measurement capabilities.
Impacts
What was accomplished under these goals?
First, we accessed the USDA soil archive and selected ~350 soil samples from the archive. These samples were scanned by a NeoSpectra handheld scanner. Each sample was scanned three times and the spectra were averaged. Data analysis is ongoing to model soil nutrient data with the spectral data from the NeoSpectra scanner. The modeling results would help us to answer two key questions: (1) how successful the soil nutrients can be estimated from the NeoSpectra data in the lab setting, and (2) how the performance of soil nutrient estimation from NeoSpectra is compared to that from the ASD. Second, we conducted two sampling campaigns with our VisNIR penetrometer system for in-situ soil measurement. Both of the sampling campaigns happened on a research farm (~300 acres with mixed soil types, topography, and crop management practices) at UNL. In the first campaign, testing was done at nine locations; and the second campaign, testing was done at 12 locations. At each location, we used the VisNIR penetrometer system to collect in-situ soil spectral data to a depth of 80 cm every 5 cm. We then collected a validation soil core from each location. The validation cores were cut in the field to 10-cm segments (0-10, 10-20 cm...). The samples were dried and ground in our lab, and then sent to a local soil testing laboratory for soil nutrient analysis. We are awaiting the results to be returned, and then we will conduct analysis to estimate the soil nutrient from the in-situ spectral data by the VisNIR penetrometer. We developed electronics and data gathering software required for our NIRONE NIR sensor and the Ocean STS sensor.
Publications
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