Assessing Nitrogen Nutrition in Corn Crops with Airborne Multispectral Sensors

被引：5

作者：

Alberto Arroyo, Jaen ^{[1
]}

Gomez-Castaneda, Cecilia ^{[1
]}

Ruiz, Elias ^{[1
]}

Munoz de Cote, Enrique ^{[1
,3
]}

Gavi, Francisco ^{[2
]}

Enrique Sucar, Luis ^{[1
]}

机构：

[1] Inst Nacl Astrofis Opt & Electr, Comp Sci Dept, Luis Enrique Erro 1, Puebla 72840, Mexico

[2] Colegio Posgrad, Programa Hidrociencias, Montecillo, Mexico

[3] Prowler Io Ltd, Cambridge, England

来源：

ADVANCES IN ARTIFICIAL INTELLIGENCE: FROM THEORY TO PRACTICE (IEA/AIE 2017), PT II | 2017年 / 10351卷

关键词：

MAIZE; FERTILIZATION; SOIL;

D O I：

10.1007/978-3-319-60045-1_28

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a method to assess nitrogen levels, a nitrogen nutrition index (NNI), in corn crops (Zea mays) using multispectral remote sensing imagery. The multispectral sensors used were four spectral bands only. The experiments were compared with nitrogen levels sensed in the field. The corn crops were divided into three nitrogen fertilization levels (70, 140 and 210 kgN.ha(-1)) into three replicates. In this sense, we propose a method to infer nitrogen levels in corn crops by using airborne multispectral sensors and machine learning techniques. The presented results offered a simple model to estimate nitrogen with low-cost technologies (UAVs and multispectral cameras only) in small to medium size areas of corn crops.

引用

页码：259 / 267

页数：9

共 16 条

[1] Multispectral remote sensing for site-specific nitrogen fertilizer management [J].

Bagheri, Nikrooz ;

Ahmadi, Hojjat ;

Alavipanah, Seyed Kazem ;

Omid, Mahmoud .

PESQUISA AGROPECUARIA BRASILEIRA, 2013, 48 (10) :1394-1401

[2] Random forests [J].

Breiman, L .

MACHINE LEARNING, 2001, 45 (01) :5-32

[3] Nitrogen Status Assessment for Variable Rate Fertilization in Maize through Hyperspectral Imagery [J].

Cilia, Chiara ;

Panigada, Cinzia ;

Rossini, Micol ;

Meroni, Michele ;

Busetto, Lorenzo ;

Amaducci, Stefano ;

Boschetti, Mirco ;

Picchi, Valentina ;

Colombo, Roberto .

REMOTE SENSING, 2014, 6 (07) :6549-6565

[4] Remote sensing of chlorophyll concentration in higher plant leaves [J].

Gitelson, AA ;

Merzlyak, MN .

SYNERGISTIC USE OF MULTISENSOR DATA FOR LAND PROCESSES, 1998, 22 (05) :689-692

[5]

Guerif M., 2007, 4 INT S INT INF TECH

[6] Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture [J].

Haboudane, D ;

Miller, JR ;

Pattey, E ;

Zarco-Tejada, PJ ;

Strachan, IB .

REMOTE SENSING OF ENVIRONMENT, 2004, 90 (03) :337-352

[7] The range of the critical nitrogen dilution curve for maize (Zea mays L.) can be extended until silage maturity [J].

Herrmann, A ;

Taube, F .

AGRONOMY JOURNAL, 2004, 96 (04) :1131-1138

[8]

Lemaire G., 1997, Diagnosis of the Nitrogen Status in Crops, P3, DOI [10.1007/978-3-642-60684-7_1, DOI 10.1007/978-3-642-60684-7_1]

[9] Performance of Three Reflectance Calibration Methods for Airborne Hyperspectral Spectrometer Data [J].

Miura, Tomoaki ;

Huete, Alfredo R. .

SENSORS, 2009, 9 (02) :794-813

[10] Determination of the critical soil mineral nitrogen concentration for maximizing maize grain yield [J].

Peng, Yunfeng ;

Yu, Peng ;

Li, Xuexian ;

Li, Chunjian .

PLANT AND SOIL, 2013, 372 (1-2) :41-51

← 1 2 →