Novel Approach for Estimating Nitrogen Content in Paddy Fields Using Low Altitude Remote Sensing System

Abstract

Commission I, ICWG I/VbKEY WORDS: Low altitude remote sensing, Unmanned aerial vehicle, Rice, Vegetation index, Nitrogen ABSTRACT:Concerns over the use of nitrogen have been increasing due to the high cost of fertilizers and environmental pollutions caused by excess nitrogen application in agricultural fields. Several methods are available to assess the amount of nitrogen in crops, however, they are expensive, time-consuming, inaccurate, and/or require specialists to operate the tools. Researcher recently suggested remote sensing and specifically Low Altitude Remote Sensing (LARS) system of chlorophyll content in crop canopies as a low-cost alternative to estimate plant nitrogen status. The main objective of this study was to develop and test a new Vegetation Index (VI) to determine the status of nitrogen and chlorophyll content in rice leaf by analysing and considering all Visible (Vis) bands. Besides, capability of introduced VI has compared with all known VIs in both Vis and Near Infrared (NIR) bands in canopy scale. To develop the VI, images from 6-pannel leaf colour chart were acquired using Basler Scout scA640-70fc under light-emitting diode lighting, in which principal component analysis was used to retain the lower order principal component to develop a new index called I PCA . A conventional digital camera mounted to an Unmanned Aerial Vehicle (UAV) was also used to acquire images over the rice canopy in Vis bands. Simultaneously, Tetracam agriculture digital camera was employed to acquire rice canopy image in Vis-NIR bands. The results indicated that the proposed index at canopy (r = 0.78) scale could be used as a sensor to determine the status of chlorophyll content consequently for monitoring nitrogen in rice plant through different growth stages. Moreover, results confirmed that a lowcost LARS system would be suited for high spatial and temporal resolution images and data analysis for proper assessment of key nutrients in crop farming in a fast, inexpensive and non-destructive way.

Advantages of Amending Chemical Fertilizer with Plant-Growth-Promoting Rhizobacteria under Alternate Wetting Drying Rice Cultivation

“…The soil properties included a 15% wilting point, 30.5% field capacity, and 42.9% saturation. The recorded bulk density was 1.40 g/cm 3 . Soil has a matric potential of 11.09 bar and a hydraulic conductivity of 57 mm/h [28].…”

“…Plants absorb essential macronutrients such as phosphate ions (HPO 4 2− and H 2 PO 4 − ), nitrate (NO 3 − ), and ammonium (NH 4 + ). Pollution is known to occur when these elements discharge through leaching, mineralization, or volatilization, a situation that is further amplified through rapid degradation of the soil structure during the intensive rice cropping cycle [3][4][5].…”

A Review on the Use of Unmanned Aerial Vehicles and Imaging Sensors for Monitoring and Assessing Plant Stresses

“…In many instances, the nitrogen status is estimated indirectly from other variables, especially the chlorophyll content and leaf area index. Since the chlorophyll content is easier to measure than the nitrogen content (for example, using the SPAD device) [128], it is sometimes used as the target variable in investigations regarding remote nitrogen monitoring [110,117]. The problem with this approach is that the chlorophyll content may not be an accurate proxy of the nitrogen content if the concentration of the latter is high [111].…”

UAV- and Random-Forest-AdaBoost (RFA)-Based Estimation of Rice Plant Traits

“…Simultaneously, many recent studies [6][7][8][9][10][11][12][13][14][15][16][17] have demonstrated the capability of UAV based sensors to estimate common rice agronomics traits such as leaf or/and plant N content, the biomass of separate crop organs, yield components and other physiological responses that are useful for phenotyping studies. These traits are commonly used to evaluate the effects of fertilizers, irrigation management and weather on the rice crop growth development, either through field experiments or crop modelling [18][19][20] since they are direct indicators of rice growth and yield performance.…”

“…Generally, the results from past studies have illustrated that plant traits such as leaf or/and plant N content, biomass and yield could be inferred using various indices at different rice growing stages with good accuracy [6][7][8][9][10][11][12]. Fewer studies have been conducted for the rice leaf area index (LAI), plant height (PH), plant density and chlorophyll content [6,8,[13][14][15][16][17].…”