Use of fluorescence indices as predictors of crop N status and yield for greenhouse sweet pepper crops

Author:

de Souza RominaORCID,Peña-Fleitas M. Teresa,Thompson Rodney B.,Gallardo Marisa,Grasso Rafael,Padilla Francisco M.

Abstract

AbstractTo increase nitrogen (N) use efficiency and reduce water pollution from vegetable production, it is necessary to optimize N management. Fluorescence-based optical sensors are devices that can improve N fertilization through non-destructive field monitoring of crop variables. The aim of this work was to compare the performance of five fluorescence indices (SFR-R, SFR-G, FLAV, NBI-R, and NBI-G) to predict crop variables, as dry matter production, crop N content, crop N uptake, Nitrogen Nutrition Index (NNI), absolute and relative yield, in sweet pepper (Capsicum annuum) crops grown in greenhouse. Fluorescence measurements were periodically made with the Multiplex® 3.6 sensor throughout three cropping cycles subjected to five N application treatments. The performance of fluorescence indices to predict crop variables considered calibration and validation analyses. In general, the five fluorescence indices were strongly related with NNI, crop N content and relative yield. The best performing indices to predict crop N content and NNI at the early stages of the crops (i.e., vegetative and flowering phenological stages) were the SFR indices, both under red (SFR-R) and green (SFR-G) excitation. However, in the final stage of the crop (i.e., harvest stage), the best performing indices were NBI, both under red (NBI-R) and green (NBI-G) excitation, and FLAV. The two SFR indices best predicted relative yield of sweet pepper at early growth stages. Overall, the fluorescence sensor and the fluorescence indices evaluated were able to predict crop variables related to N status in sweet pepper. They have the capacity to be incorporated into best N management practices.

Funder

Ministerio de Economía y Competitividad

Universidad de Almería

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences

Reference43 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3