INVESTIGATIONS ON TRACTOR MOUNTED N-SENSOR FOR WHEAT CROP IN INDIA

Similar documents
Remote sensing: A suitable technology for crop insurance?

Precision Agriculture. John Nowatzki Extension Ag Machine Systems Specialist

HARI RAM*, GURJOT SINGH, G S MAVI and V S SOHU

Use of Chlorophyll Meters to Assess Nitrogen Fertilization Requirements for Optimum Wheat Grain and Silage Yield and Quality

Quantification of microclimate of cotton hybrids under different sowing environments

QUANTIFYING CORN N DEFICIENCY WITH ACTIVE CANOPY SENSORS. John E. Sawyer and Daniel W. Barker 1

The Evaluation of Ground Based Remote Sensing Systems for Canopy Nitrogen Management in Winter Wheat Economic Efficiency

P.L. Patil, H.B.P. Pulakeshi and G.S. Dasog

Swedish Farmers' Experiences of the Yara N-Sensor ABSTRACT

Improving Nutrient Management in Agriculture. Industry Perspective

FACILITATING AGRICULTURE AUTOMATION USING STANDARDS

Estimating the Nitrogen Nutrition Index of Winter Wheat Using an Active Canopy Sensor in the North China Plain

Osamu Shigetomi 2 Saga Prefectural Agricultural Research Institute

Modeling fuel use for specific farm machinery and operations of wheat production

Nitrogen Use Efficiency as an Agro- Environmental Indicator

Strategies for Site Specific Fertilization in a Highly Productive Agricultural Region

ASSESSING BIOMASS YIELD OF KALE (BRASSICA OLERACEA VAR. ACEPHALA L.) FIELDS USING MULTI-SPECTRAL AERIAL PHOTOGRAPHY

Elliott Hildebrand and Jeff Schoenau. ASA, CSSA and SSSA Long Beach, CA November, Dept. Soil Science University of Saskatchewan

Growth Stage, Development, and Spatial Variability in Corn Evaluated Using Optical Sensor Readings

Use of Sentinel 2 for agricultural operational applications at farm level - Talking Fields

Linking GIS and Mobile GIS. in Precision Agriculture

EASY Efficient Agriculture Systems ISARIA CROP SENSOR

AGRICULTURAL MACHINES MANAGEMENT AND ASSIGNMENT SYSTEM OF HEILONGJIANG RECLAMATION AREA

Biogeochemistry of nitrogen in agricultural systems The International Fertiliser Society, Reprints from Society Proceedings, Editor C. J.

CALIBRATION OF FERTILIZER APPLICATION EQUIPMENT ON-FARM

"Depanment of Agricultural Economics INTRODUCTION

Evaluation of a Power Driven Residue Manager for No-till Drills

Analysis of straw bruising and sieving system on performance of modified wheat straw combine for better straw quality

REAL-TIME VARIABLE RATE TECHNOLOGIES (VRT) PRECISION AGRICULTURE TECHNOLOGY ARCHITECTURE OUTLINE

Nitrogen Management Guidelines for Corn in Indiana

Crop Nutrition Application Technology Industri 4.0 Reduce environmental impact & increase yield

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

GPS/GIS Applications for Farming Systems

EASY Efficient Agriculture Systems. Precision farming

Wheat Yield Prediction using Weather based Statistical Model in Central Punjab

Precise Application of Fertiliser

Variable-Rate Application FACT SHEET

Application of Remote Sensing On the Environment, Agriculture and Other Uses in Nepal

Dynamic Image Processing for Landuse Analysis & Precision Agriculture. Hari Yeruva, GISP

Integrated Controls, Distributed Sensors and Decision Support Systems for Wireless Site-specific Sprinkler Irrigation

Biomass Accumulation and Nutrient Uptake of Oilseeds at Different Growth Stages in the Parkland Region of Saskatchewan

K. S. SOMASHEKAR*, B. G. SHEKARA 1, K. N. KALYANA MURTHY AND L. HARISH 2 SUMMARY

GIS based decision support system for precision farming of cassava in India

Site-specific crop management (SSCM) for Australian grains: how to begin

CCA 4R Nutrient Management Specialist Exam

RESPONSE OF MAIZE TO PLANTING METHODS AND FERTILIZER N

CORN NITROGEN RATE RESPONSE AND CROP YIELD IN A RYE COVER CROP SYSTEM. Introduction

BT COTTON PRODUCTIVITY AND PROFITABILITY AS INFLUENCED BY NUTRIENT LEVELS AND NITROGEN SPLIT APPLICATION UNDER IRRIGATION

EFFECT OF PLANT POPULATION ON MAIZE HYBRIDS

Unmanned Aerial Vehicle (UAV)-Based Remote Sensing for Crop Phenotyping

North West Geography

Fig1: Melt pool size of LAMP vs. µlamp. The LAMP process s melt pool is x the area of the LAMP s melt pool.

Crop Growth Monitor System with Coupling of AVHRR and VGT Data 1

Can satellite data beat common sense of farmers? The agricultural sector, a high tech market, many opportunities for the space sector.

Phosphorous management based on an on-line visible and near infrared (vis-nir) spectroscopy sensor

OECD/BIAC Workshop: Green Growth in the Agro-Food Chain: Nutrient use efficiency for crops. Koen Van Keer & Joachim Lammel Yara International ASA

A Study on Wear Characteristics of ADI Rotavator Blades

Environmental assessment of N fertilizer management practices

Transferability of Models for Estimating Paddy Rice Biomass from Spatial Plant Height Data

The Monitoring System of Marine Refrigerated Containers Based on RFID Temperature Tags

» Software in Tractors: Aspects of Development, Maintenance and Support «

Dynamics of Labour Demand and its Determinants in Punjab Agriculture

Estimating Field Loss of a Developed Rice Stripper Harvester in Nigeria

Attribute based coding, review and gap analysis of cotton harvesting processes and machines

FORMA: Forest Monitoring for Action

Precision farming: The most scientific and modern approach to sustainable agriculture

Measuring canopy nitrogen nutrition in tobacco plants using hyper spectrum parameters

RESPONSE OF INTEGRATED NUTRIENT MANAGEMENT ON WHEAT ( TRITICUM AESTIVUM L.) AND ITS RESIDUAL EFFECT ON SUCCEEDING CROP

PLEASE SCROLL DOWN FOR ARTICLE

Impellers of low specific speed centrifugal pump based on the draughting technology

Agricultural Aerial Services

Remote Sensing (C) Team Name: Student Name(s):

Effect of Wheat Residue Management and Fertilizer Levels on Growth and Yield of Fodder Maize (Zea mays L.)

Crop Information Portal Agriculture Information System Building Provincial Capacity for Crop Forecasting and Estimation

25 years Precision Agriculture in Germany a retrospective

Field Loss Estimation Of A Developed Rice Stripper Harvester In Nigeria

Fuel Leak Simulation

Development of Pull Type Inclined Plate Planter

EFFECT OF PLANTING METHODS AND NITROGEN LEVELS ON THE YIELD AND YIELD COMPONENTS OF MAIZE

Recommended Resources: The following resources may be useful in teaching this lesson:

WATER AWARENESS PROGRAM (WAP) FOR FARMERS (Moga, Punjab)

History and Global Perspective of Soil Sampling and Analysis

Indian Res. J. Ext. Edu. 13 (2), May, Custom Hiring Services of Farm Machinery in Punjab: Impact and Policies ABSTRACT

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

Agriculture Information System. Crop Information Portal of Pakistan: version 2 Database Administration

SAR forest canopy penetration depth as an indicator for forest health monitoring based on leaf area index (LAI)

Agricultural drought index and monitoring on national scale. LU Houquan National Meteorological Center, CMA

Design of an Agricultural Runoff Monitoring & Incentive System for Maryland

Monitoring Crop Leaf Area Index (LAI) and Biomass Using Synthetic Aperture Radar (SAR)

Agricultural Innovation

Int.J.Curr.Microbiol.App.Sci (2017) 6(8):

Evaluation of mid-season sensor based nitrogen fertilizer recommendations for winter wheat using different estimates of yield potential

Agro-meteorological Indices to Predict Plant Stages and Yield of Wheat for Foot Hills of Western Himalayas

Agronomic performance of mash bean as an intercrop in sesame under different planting patterns

Second stage cooling from a Cryomech PT415 cooler at second stage temperatures up to 300 K with cooling on the first-stage from 0 to 250 W

Crop Monitoring System in Bangladesh, Main Challenges, Recent Initiatives and Prospects

KEYNOTE LECTURES REGULAR SESSIONS. Special Sessions AND mini-symposia. SESSION index

Climate Sensitivity of Winter Cropping in India

PRECISION PIVOT IRRIGATION CONTROLS TO OPTIMIZE WATER APPLICATION. Biological & Agricultural Engineering and NESPAL ABSTRACT INTRODUCTION

An Architecture for the Agricultural Machinery Intelligent Scheduling in Cross-Regional Work Based on Cloud Computing and Internet of Things

Transcription:

Investigations on Tractor Mounted N-Sensor for Wheat Crop in India Proceedings of AIPA 2012, INDIA 137 INVESTIGATIONS ON TRACTOR MOUNTED N-SENSOR FOR WHEAT CROP IN INDIA Ankit Sharma 1, Manjeet Singh 2 and J. Jasper 3 1,2 Department of Farm Machinery and Power Engineering, Punjab Agricultural University, Ludhiana 3 Research Centre Hanninghof Yara International ASA, Duelmen, Germany ABSTRACT Sensor technology, which benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations, has the potential to provide added value for crop production. The tractor-mounted N-sensor is a remote sensing system which processes the real-time measurements using an onboard computer to produce sensor biomass data. The N-sensor installed on the tractor at 2.74 m height, based upon its geometry, it scanned the cropped area of 46.72 m 2. It consists of two diode spectrometers, fiber optics and microprocessor in a hard shell, built on the roof of the tractor. The viewing angles of two spectrometers of N-sensor are 58 and 70 on each side. The N-sensor was operated in the five wheat crop plot having different nitrogen levels (0, 40, 80, 120 and 160 kgn/ha) and it was observed that the N-sensor data gave good correlations with nitrogen uptake at 35 growth stage (approximately 90 DS) on wheat crop. Keywords: N-sensor, Wheat, Biomass, N-uptake. 1. INTRODUCTION Precision agriculture is such a new emerging, highly promising technology, spreading rapidly in the developed countries. Precision agriculture is a scientific endeavor to improve the agricultural management by application of sensor technology, satellite based technology (e.g. global positioning system, remote sensing, etc.) and Information Technology (IT) to identify, analyze and manage the spatial and temporal variability of agronomic parameters within field by timely application of only required amount of input to optimize profitability, sustainability with a minimized impact on environment. Sensor technology has the potential to provide added value for agriculture e.g., for improving yield quality or for decreasing costs or risks in production. Today, low-cost powerful computers, real-time controllers, variable rate application hardware, accurate location systems, and advances in sensor technology have combined to provide the technology to make precision farming a reality. Currently sensor technology has been most commonly applied in real-time weather monitoring for support of management practices, and in precision agriculture (Pierce and Elliott 2008; Wang et al., 2006). Agriculture benefits from high temporal measuring resolution, real-time data transfer and high spatial resolution of sensor data that shows in-field variations (Hart and Martinez 2006; Butler 2006). Advancement in sensor technology changed Indian environment as well as created new scopes for farm sectors. So under this changed condition it is necessary to grasp over the new cutting edge technologies in agriculture invented in the developed world and subsequent modification according to the domestic conditions for proper digestion of Indian farm sectors. The tractor mounted N-sensors available in the world is one of the sensor technologies which measures the level of light reflectance by crop canopies using spectrometers (Link et al., 2002; Wiltshire et al., 2002). It is a remote sensing system which processes real-time scanner measurements using an onboard computer to produce sensor biomass readings which are combined with GPS technology to produce biomass maps. But in developing countries like India, the uses of such type of sensor technology are in very nascent stage. Investigation of such type of technology in Indian agriculture concern is a dire need of present time. So the objectives of this paper are to investigate the tractor mounted N-sensor. 2. MATERIALS AND METHODS 2.1 Description of N-sensor N-sensor (make Yara) consists of two diode spectrometers, fiber optics and microprocessor in a hard shell, built on the roof of the 55 hp tractor (make New Holland model 5500). A spectrometer collects reflectivity at wavelengths from 620 to 1000 nm with four points, which are around the tractor. Correction radiation occurs through the second spectrometer recognizing area sky at the same wavelength. Crop is scanned by the N-sensor with viewing angle of two spectrometers 58 and 70 on each side. A fifth sensor positioned skywards measures the intensity of light allowing the

138 Agro-Informatics and Precision Agriculture 2012 (AIPA 2012) sensor system to compensate for different light conditions while operating. The N-sensor having 2 m width of rig, installed on the tractor at 2.74 m height, based upon its geometry, it scanned the cropped area of 46.72 m 2. The whole process of determining the crop s Nitrogen requirement and application of the correct fertilizer rate happens instantaneously, with no time delay. This enables real time agronomy to be possible. The N-sensor system was connected to a Differential Global Positioning System (DGPS) signal to allow Location, sensor and application information to be plotted enabling the production of biomass and Nitrogen application maps for the field. The N-sensor was also connected to the computer screen which is installed on the tractor cabin in front of driver seat. All the sensing operations command was given through the computer screen. The N-sensor can also be further connected to the variable rate controller for variable rate application of the fertilizer. A system view of N-sensor and technical setup shown in Figures 1 and 2 showed the view of N-sensor viewing angle, DGPS and computer screen. Fig. 1: N-sensor System View and Technical Setup Fig. 2: View of N-sensor Viewing Angle, DGPS and Computer Screen 2.2 Calculation of Area Sensed by N-Sensor From Figure 3, equations (i) and (ii) ((Source: YARA (Hydro Agri), tec5hellma) can be obtained through which area sensed by the N-sensor can be calculated as follows: X1 = d/2 + h tan58 /(2) 1/2 = 0.5d + 1.13 h (i) X2 = d/2 + h tan70 /(2) 1/2 = 0.5d + 1.94 h (ii) Where: d width of the sensor rig, h: height of sensor rig, X1: inner point of sensor area, X2 = outer point of sensor area, y: width of sensed area, m and n = major and minor axis of ellipse, H = 2.74 m, from equation (i) and (ii), X1 = 4.22 m and X2 = 6.44 m y = X2 X1 = 2.2 m, a = X2 d/2 y = 3.12, b = a+y = 5.32, p = b tan 45, q = p 2 = 10.64 m, L = b/cos45 = 10.13 L1 = a/cos45 = 5.9, m = L L1 = 4.23, Area of Ellipse = πmn,

Investigations on Tractor Mounted N-Sensor for Wheat Crop in India 139 Area of one ellipse = πmn 1/4 = 11.68 m 2, Total area scanned by the 4 sensors = 4 11.68 = 46.72 m 2 Fig. 3: Top and Front View of Geometry of N-Sensor (all dimensions are in meter) 2.3 Operation of N-sensor in the Field The N-sensor installed on the tractor was operated in the five plots of wheat crop (variety PBW 621) of size 20 m 20 m each (Figure 4) having inceasing nitrogen level rate (0, 40, 80, 120 and 160 kgn/ha (Figure 5). Before N-sensor is used in selected plots, a simple agronomic calibration procedure is required for each field. This process involves scanning a small area of crop to measure the average sensor reading. A plot of 40 m 20 m size was selected for the agronomic calibration of N-sensor. An optimum nitrogen rate is then calculated, for that area, using either farm practice, N-tester or N-plan. This optimum Nitrogen rate is then keyed into the computer in the tractor cab and assigned to the average sensor reading. As the tractor passes over the field where it is to be operated, the N-sensor will vary the rate around this average optimum, according to the crop s requirements. If required, the range of application rates can be restricted by setting maximum and minimum levels. Fig. 4: View of Installed N-sensor on the Tractor Roof in the Field Fig. 5: Experimental Layout of Operation of N-Sensor in the Field 3. RESULTS AND DISCUSSION The N-sensor gives the data in the form of log file which can be converted into the CSV file format with the help of log converter software or with N-sensor card writer software. This CSV file can be opened in excel format which contains the real time information of the crop. The N-sensor installed on the tractor roof was operated in the five wheat crop plot having increasing nitrogen level rate (0, 40, 80, 120 and 160 kgn/ha). The data was taken at 35 growth stage (approximately 90 days after sowing (DS)). The relation between N-sensor data and crop N-uptake was studied (Figure 6) and it was

140 Agro-Informatics and Precision Agriculture 2012 (AIPA 2012) observed that Crop N-uptake was increased as sensor data increased (equation was also added with trend line). The coefficient of correlation was found to be 0.907. 120 Crop N uptake (kg/ha) 100 80 60 40 20 0 y = 22.27x 2.781 R² = 0.907 9.04 14.01 52.823 41.75 50.56 Sensor data Fig. 6: Relation between Crop N-uptake and Sensor Biomass Data The N-sensor Biomass map was also prepared from the log file after the operation of N-sensor (Figure 7). The log file was processed through the sensor office software available on the YARA company website (www.sensoroffice.com). The map can be downloaded online from the website. The map showed that the minimum and maximum biomass were 0.8 and 5.4 with average value 2.89 having standard deviation 1.71. Also the relation between N-input and Normalized Difference Vegetation Index (NDVI) (Figure 8) was obtained from the study which indicate that as the N-input rate increase the NDVI also increases because with increase in N-input the biomass of crop also get increased. Fig. 7: View N-sensor Biomass Map

Investigations on Tractor Mounted N-Sensor for Wheat Crop in India 141 0.700 0.600 0.500 NDVI 0.400 0.300 0.200 0.100 0.000 1 11 21 31 41 51 61 71 Data location with increasing trend of N inputs Fig. 8: Relation between N-inputs and NDVI Derived from N-sensor 4. CONCLUSIONS This study has shown the N-sensor to be a useful sensor technology which can estimate cereal crop biomass and N-status at different crop growth stages. The N-sensor readings gave good correlations with crop N-uptake (kg/ha), it also indicates the biomass reading at key growth stage. The N-sensor installed on the tractor at 2.74 m height, based upon its geometry, it scanned the cropped area of 46.72 m 2. It consists of two diode spectrometers, fiber optics and microprocessor in a hard shell, built on the roof of the tractor. The viewing angles of two spectrometers of N-sensor are 58 and 70 on each side. The N-sensor was operated in the five wheat crop plot having different nitrogen levels (0, 40, 80, 120 and 160 kgn/ha) and it was observed that the N-sensor data gave good correlations with nitrogen uptake at 35 growth stage (approximately 90 DS) on wheat crop. The biomass map prepared showed that the NDVI increased as the N-input increases due to increase in biomass having average value of 2.89 and standard deviation of 1.71. REFERENCES Butler, D., 2006, Everything, everywhere. Nature, 7083, 402 405. Hart, J. and Martinez, K., 2006, Environmental sensor networks: A revolution in the earth system science? Earth-Sci. Rev., 78, 177 191. Link, A., Panitzki, M. and Reusch, S., 2002, Hydro NSensor: In : Proceedings of the 6th International Conference on Precision Agriculture. July 14 17, Minneapolis. Madison, Wisconsin. Pierce, F. and Elliott, T., 2008, Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington. Comput. Electon. Agric., 61, 32 43. Wang, N.; Zhang, N. and Wang, M., 2006, Wireless sensors in agriculture and food industry-recent development and future perspective. Comput. Electron. Agric., 50, 1 14. Wiltshire, J., Clark, W.S., Riding, A., Steven, M., Holmes, G., and Moore, M., 2002, HGCA project report no. 288. September.