Abstract
<p class="1Body">Sustainable agriculture with use of Arbuscular Mycorrhizal Fungi (AMF) is an emerging farm management that improves crops nutrient and water use efficiency. Decision making on the effect of AMF is still dependent on agronomic diagnosis which is long, tedious, expensive and destructive. This study demonstrates the applicability of proximal fluorescence and reflectance spectroscopy for evaluating and detecting at early stage distinct types of mycorrhized plantain from two cultivars (<em>Musa paradisiaca</em>).</p><p class="1Body">Visible-near infrared (400-1000 nm) reflectance and fluorescence data were collected from control and three levels mycorrhized plants designed in randomized and complete block under greenhouse conditions. Two spectral measurements at a week interval were performed on plant leaves by using an USB spectrometer mounted with an Arduino-based LED driver clip.</p>A new normalized reflectance water NWI5 index shows with Datt5 alone highly significant differences at P&lt;0.001 respectively for Orishele and fhia21 cultivars. dNIRmin920_980, NDVI3 and GI reflectance index are significant at P&lt;0.01. Seven other reflectance and 3 fluorescence indices ANTH, FRF_R and NBI_R are significant at P&lt;0.05. The two first principal components for each cultivar spectral features explaining 94.1 % of variance were used to build predictive classification models. LogitBoost algorithm indicates accuracy of 90.27% on stratified cross-validation and 87.5% on test split. Our results confirm that fluorescence and reflectance spectroscopy is a valuable tool for early assessment of mycorrhization success rate evaluation and pattern recognition. They also show promise for the development of non-destructive and cost-effective detectors in monitoring crops under biofertilizers with arbuscular mycorrhizae.
Highlights
Agricultural remote sensing has gained great importance in sustainable and intensification farming management
This study demonstrates the applicability of proximal fluorescence and reflectance spectroscopy for evaluating and detecting at early stage distinct types of mycorrhized plantain from two cultivars (Musa paradisiaca)
LogitBoost algorithm indicates accuracy of 90.27% on stratified cross-validation and 87.5% on test split
Summary
Agricultural remote sensing has gained great importance in sustainable and intensification farming management. It generates digital data from sensors that help in reducing the risk and minimize damage of inappropriate fertilization. Low or excessive uses of chemical fertilizers can have high adverse impact on the environment and grain production system. Unused nitrogen released to the environment can have detrimental effects (Cameron, Di, & Moir, 2013). Large application of phosphate fertilizers and by-products has been practiced on arable lands, to improve crop production, induced soil nutrients deficiency, and increasing the levels of available S and P (Kassir, 2014). In the increasing demand of environmental sustainability, more attention of agricultural scientific community is being turned on biofertilizers Arbuscular Mycorrhizal Fungi www.ccsenet.org/apr
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