Exploring Novel Bands and Key Index for Evaluating Leaf Equivalent Water Thickness inWheat Using Hyperspectra Influenced by Nitrogen

Title Exploring Novel Bands and Key Index for Evaluating Leaf Equivalent Water Thickness in Wheat UsingHyperspectra Influenced by Nitrogen

Title (native language)

Category Recording or mapping technology

Short summary forpractitioners (Practiceabstract) in English)

Previous studies have shown that the transportation of amino acids from leaves to grains afteranthesis leads to physiological and biochemical changes in the organizational structures of leaves,which affect LEWT monitoring based on leaf hyperspectral reflectance. In this study, we demonstratedthat different water and nitrogen treatments affected the variation in LEWT and the leaf hyperspectralreflectance of wheat within the 350–2,500 nm range. Furthermore, the top 10% of the maximum|RLEWT| and |RLNC| values were found to share common wavelength ranges. Based on this studyand previous reports, when monitoring LEWT, the noise from the LNC should be considered. Themodel based on a three-band index (R1429−R416−R1865)/(R1429+R416+R1865) described in thispaper performed well for monitoring LEWT, with a higher predictability and stability for water contentand lower noise levels due to nitrogen under various water and nitrogen treatments.

Short summary forpractitionersWebsiteAudiovisual materialLinks to other websitesAdditional commentsKeywords Plant production and horticulture | Fertilisation and nutrients managementAdditional keywordsGeographical location(NUTS) EU

Other geographicallocation Global

Cropping systems Arable cropsField operations Fertilization | Crop and soil scoutingSFT users Farmer | ContractorEducation level of users University educationFarm size (ha) 0-2 | 2-10 | 10-50 | 50-100 | 100-200 | 200-500 | >500

Scientific article

Title Exploring novel bands and key index for evaluating leaf equivalent water thickness in wheat usinghyperspectra influenced by nitrogen

Full citation Yao, X.; Jia, W.; Si, H.; Guo, Z.; Tian, Y.; Liu, X.; Cao, W.; Zhu, Y. (2014). PLoS ONE,DOI:10.1371/journal.pone.0096352

Effects of this SFTProductivity (crop yield per ha) No effectQuality of product No effectRevenue profit farm income Some increaseSoil biodiversity No effectBiodiversity (other than soil) No effectInput costs No effectVariable costs No effectPost-harvest crop wastage No effectEnergy use No effectCH4 (methane) emission No effectCO2 (carbon dioxide) emission No effectN2O (nitrous oxide) emission No effectNH3 (ammonia) emission No effectNO3 (nitrate) leaching No effectFertilizer use Some decreasePesticide use No effectIrrigation water use No effectLabor time No effectStress or fatigue for farmer No effectAmount of heavy physical labour No effectNumber and/or severity of personal injury accidents No effectNumber and/or severity of accidents resulting in spills property damage incorrectapplication of fertiliser/pesticides etc. No effect

Pesticide residue on product No effectWeed pressure No effectPest pressure (insects etc.) No effectDisease pressure (bacterial fungal viral etc.) No effect

Information related to how easy it is to start using the SFTThis SFT replaces a tool or technology that is currently used. The SFT is better than thecurrent tool no opinion

The SFT can be used without making major changes to the existing system no opinionThe SFT does not require significant learning before the farmer can use it strongly disagreeThe SFT can be used in other useful ways than intended by the inventor agreeThe SFT has effects that can be directly observed by the farmer disagreeUsing the SFT requires a large time investment by farmer agreeThe SFT produces information that can be interpreted directly strongly disagree

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This factsheet was generated on 2018-Apr-03 11:57:17.