Estimation of Total Nitrogen Content in Forage Maize (Zea mays L.) Using Spectral Indices: Analysis by Random Forest

Abstract

Knowing the total Nitrogen content (Nt) of forage maize (Zea mays) is important so that decisions can be made quickly and efficiently to adjust the timing and amount of both irrigation and fertilizer. In 2017 and 2018 during three growing cycles in two study plots, leaf samples were collected and the Dumas method was used to estimate Nt. During the same growing seasons and on the same sampling plots, a Parrot Sequoia camera mounted on an unmanned aerial vehicle (UAV) was used to collect high resolution images of forage maize study plots. Thirteen multispectral indices were generated and, from these, a Random Forest (RF) algorithm was used to estimate Nt. RF is a machine-learning technique and is designed to work with extremely large datasets. Overall analysis showed five of the 13 indices as the most important. One of these five, the Transformed Chlorophyll Absorption in Reflectance Index/Optimized Soil-Adjusted Vegetation Index, was found to be the most important for estimation of Nt in forage maize (R2 = 0.76). RF handled the complex dataset in a time-efficient manner and Nt did not differ significantly when compared between traditional methods of evaluating Nt at the canopy level and using UAVs and RF to estimate Nt in forage maize. This result is an opportunity to explore many new research options in precision farming and digital agriculture.

Digital image processing technology under backpropagation neural network and K-Means Clustering algorithm on nitrogen utilization rate of Chinese cabbages

“…The traditional chemical methods to determine the total nitrogen content in crops include Dumar’s method and the Kjeldahl method [ 16 ]. The principle of applying Dumar’s method to monitor the nitrogen content of crops is to burn the collected samples to ensure that various forms of nitrogen are converted into gaseous nitrogen; then, the nitrogen content of the samples is calculated by calculating the volume of nitrogen [ 17 ]. Almost all the laboratory chemical analysis methods require drying and grinding procedures after collecting crop samples, involving drugs with potential safety hazards.…”

Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand ofAcacia schaffneriin Durango, Mexico

“…The Sentinel-2 mission consists of two satellites, and has a temporal resolution of 5 days, with 13 spectral bands located between the spectral region of visible to short-wave infrared which are as follows: four bands of 10 m of spatial resolution, six bands of 20 m, and three bands of 60 m, with a sweep width of 290 km (ESA, 2016). The Sentinel-2 mission incorporates three bands in the red-edge region, which allows to run spatial studies related to nutritional and stress conditions for plant covers (DELGADO et al, 2011;LÓPEZ-CALDERÓN et al, 2020).…”

A Computer-Vision-Based Approach for Nitrogen Content Estimation in Plant Leaves

“…Nitrogen is a key component of the chlorophyll that intensifies photosynthesis in crops [4][5][6][7], and plant yield is affected by irregularity in nitrogen content [8][9][10]. The amount of nitrogen required for each crop varies [11][12][13][14].…”