PMID- 29230230
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20240327
IS  - 1664-462X (Print)
IS  - 1664-462X (Electronic)
IS  - 1664-462X (Linking)
VI  - 8
DP  - 2017
TI  - Comparative Performance of Ground vs. Aerially Assessed RGB and Multispectral 
      Indices for Early-Growth Evaluation of Maize Performance under Phosphorus 
      Fertilization.
PG  - 2004
LID - 10.3389/fpls.2017.02004 [doi]
LID - 2004
AB  - Low soil fertility is one of the factors most limiting agricultural production, 
      with phosphorus deficiency being among the main factors, particularly in 
      developing countries. To deal with such environmental constraints, remote sensing 
      measurements can be used to rapidly assess crop performance and to phenotype a 
      large number of plots in a rapid and cost-effective way. We evaluated the 
      performance of a set of remote sensing indices derived from Red-Green-Blue (RGB) 
      images and multispectral (visible and infrared) data as phenotypic traits and 
      crop monitoring tools for early assessment of maize performance under phosphorus 
      fertilization. Thus, a set of 26 maize hybrids grown under field conditions in 
      Zimbabwe was assayed under contrasting phosphorus fertilization conditions. 
      Remote sensing measurements were conducted in seedlings at two different levels: 
      at the ground and from an aerial platform. Within a particular phosphorus level, 
      some of the RGB indices strongly correlated with grain yield. In general, RGB 
      indices assessed at both ground and aerial levels correlated in a comparable way 
      with grain yield except for indices a(*) and u(*), which correlated better when 
      assessed at the aerial level than at ground level and Greener Area (GGA) which 
      had the opposite correlation. The Normalized Difference Vegetation Index (NDVI) 
      evaluated at ground level with an active sensor also correlated better with grain 
      yield than the NDVI derived from the multispectral camera mounted in the aerial 
      platform. Other multispectral indices like the Soil Adjusted Vegetation Index 
      (SAVI) performed very similarly to NDVI assessed at the aerial level but overall, 
      they correlated in a weaker manner with grain yield than the best RGB indices. 
      This study clearly illustrates the advantage of RGB-derived indices over the more 
      costly and time-consuming multispectral indices. Moreover, the indices best 
      correlated with GY were in general those best correlated with leaf phosphorous 
      content. However, these correlations were clearly weaker than against grain yield 
      and only under low phosphorous conditions. This work reinforces the effectiveness 
      of canopy remote sensing for plant phenotyping and crop management of maize under 
      different phosphorus nutrient conditions and suggests that the RGB indices are 
      the best option.
FAU - Gracia-Romero, Adrian
AU  - Gracia-Romero A
AD  - Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of 
      Biology, University of Barcelona, Barcelona, Spain.
FAU - Kefauver, Shawn C
AU  - Kefauver SC
AD  - Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of 
      Biology, University of Barcelona, Barcelona, Spain.
FAU - Vergara-Diaz, Omar
AU  - Vergara-Diaz O
AD  - Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of 
      Biology, University of Barcelona, Barcelona, Spain.
FAU - Zaman-Allah, Mainassara A
AU  - Zaman-Allah MA
AD  - International Maize and Wheat Improvement Center, CIMMYT Southern Africa Regional 
      Office, Harare, Zimbabwe.
FAU - Prasanna, Boddupalli M
AU  - Prasanna BM
AD  - International Maize and Wheat Improvement Center, CIMMYT Southern Africa Regional 
      Office, Harare, Zimbabwe.
FAU - Cairns, Jill E
AU  - Cairns JE
AD  - International Maize and Wheat Improvement Center, CIMMYT Southern Africa Regional 
      Office, Harare, Zimbabwe.
FAU - Araus, Jose L
AU  - Araus JL
AD  - Integrative Crop Ecophysiology Group, Plant Physiology Section, Faculty of 
      Biology, University of Barcelona, Barcelona, Spain.
LA  - eng
PT  - Journal Article
DEP - 20171127
PL  - Switzerland
TA  - Front Plant Sci
JT  - Frontiers in plant science
JID - 101568200
PMC - PMC5711853
OTO - NOTNLM
OT  - RGB Vis
OT  - UAV
OT  - maize
OT  - multispectral Vis
OT  - phosphorous fertilization
OT  - remote sensing
EDAT- 2017/12/13 06:00
MHDA- 2017/12/13 06:01
PMCR- 2017/01/01
CRDT- 2017/12/13 06:00
PHST- 2017/09/06 00:00 [received]
PHST- 2017/11/10 00:00 [accepted]
PHST- 2017/12/13 06:00 [entrez]
PHST- 2017/12/13 06:00 [pubmed]
PHST- 2017/12/13 06:01 [medline]
PHST- 2017/01/01 00:00 [pmc-release]
AID - 10.3389/fpls.2017.02004 [doi]
PST - epublish
SO  - Front Plant Sci. 2017 Nov 27;8:2004. doi: 10.3389/fpls.2017.02004. eCollection 
      2017.