Comparison of Different Vegetative Indices for Calibrating Proximal Canopy Sensors to Grapevine Pruning Weight

Quantification of actual plant consumption of nitrogen (N) is necessary to optimize fertilization efficiency and minimize contamination of earth resources. We examined the performance of fruit-bearing pomegranate trees grown in soilless media and exposed to eight N-fertigation treatments, from 5 to 200 mg N L−1. Reproductive and vegetative indices were found to be optimal when 20 to 70 mg N L−1 was supplied. Nitrogen application levels over 70 mg L−1 reduced pomegranate development and reproduction. N uptake in low-level treatments was almost 100% and decreased gradually, down to 13% in 200 mg N L−1 treatment. N usage efficiency was maximized under 20 mg N L−1, in which case 80% to 90% of added N was taken up by the trees. At high N application, its efficiency was reduced with less than 50% utilized by the trees. Leaf N increased to a plateau as a function of increasing irrigation solution N, maximizing at ~15 to 20 mg N g−1. Therefore, analysis of diagnostic leaves is not a valid method to identify excessive detrimental N. The results should be valuable in the development of efficient, sustainable, environmentally responsible protocols for N fertilization in commercial pomegranate orchards, following adaptation and validation to real soil field conditions.

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Optical sensors for variable rate nitrogen application in dairy pastures

Journal of New Zealand Grasslands ◽

10.33584/jnzg.2017.79.533 ◽

2017 ◽

Vol 79 ◽

pp. 223-227

Author(s):

K. Wigley ◽

J.L. Owens ◽

J.A.K. Trethewey ◽

D.C. Ekanayake ◽

R.L. Roten ◽

...

Keyword(s):

Optical Sensors ◽

Vegetation Index ◽

N Uptake ◽

Variable Rate ◽

Water Index ◽

Foliar N ◽

Normalised Difference Vegetation Index ◽

Fertiliser Application ◽

Vegetative Indices ◽

Simple Ratio

Reducing the amount of nitrogen (N) fertiliser applied to dairy pastures down to agronomically optimised levels would have positive economic and environmental results. The ability of commercially available optical sensors to estimate biomass yield and foliar-N uptake in pastures was investigated. Vegetative indices (Simple Ratio, SR; Water Index, WI; and Normalised Difference Vegetation Index, NDVI) from two active optical reflectance sensors (N-Sensor, Yara; and Greenseeker, Trimble) were compared with manually measured biomass and N-uptake in above-ground foliage. There were three measurements over time, from pastures that had received different N fertiliser applications rates (0, 10, 20, 40 and 80 kg N/ha). It was found that the sensors were able to detect differences in biomass and foliar N-uptake following defoliation of grazed pastures. The tested optical sensors have the potential to inform a real-time variable rate fertiliser application system. Keywords: pasture, nitrogen, optical sensors

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A Methodology for Improving Vegetation Representation and Health Exploiting a Semantic Robotic System and Its Dynamic Stability Control

International Journal of Semantic Computing ◽

10.1142/s1793351x18400020 ◽

2018 ◽

Vol 12 (01) ◽

pp. 25-41

Author(s):

Daniela D’Auria ◽

Fabio Persia

Keyword(s):

Dynamic Stability ◽

Production Cost ◽

Semantic Information ◽

Agricultural Productivity ◽

Precision Farming ◽

Stability Control ◽

Robotic System ◽

The Real ◽

Vegetative Indices ◽

Dynamic Stability Control

Precision farming technologies have been increasingly recognized for their potential ability for improving agricultural productivity, reducing production cost, and minimizing damage to the environment. In this context, the main goals of this paper are the following: First, we present a methodology that can be applied to extract semantic information, more specifically some vegetative indices, from plants, in order to further improve the vegetation representation and health by means of a specific semantic robotic system; then, we study in detail the tracked robot’s behavior, by emulating the real settings in a field and analytically analyze the simulation of the robot on an up and down slope path.

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