Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Brief informations on technologies available for high throughput field based phenomics for plant breeding experiments. The instrumentations and technologies presented here are based on the year 2015. Phenomics is expanding area of plant science as more technogies and latest instruments were introduced to the scientific community
Seminar presentation entitled 'Towards the development of cost-effective and moderate throughput plant phenotyping system' that was formerly presented during Regional Training Course on Mutation Breeding and Efficiency Enhancing Techniques held by International Atomic Energy Agency (IAEA) 10-20 VI 2014 (Seibersdorf, Austria). Enjoy & share comments!
Brief informations on technologies available for high throughput field based phenomics for plant breeding experiments. The instrumentations and technologies presented here are based on the year 2015. Phenomics is expanding area of plant science as more technogies and latest instruments were introduced to the scientific community
Seminar presentation entitled 'Towards the development of cost-effective and moderate throughput plant phenotyping system' that was formerly presented during Regional Training Course on Mutation Breeding and Efficiency Enhancing Techniques held by International Atomic Energy Agency (IAEA) 10-20 VI 2014 (Seibersdorf, Austria). Enjoy & share comments!
High throughput phenotyping are fully automated facilities in greenhouses or growth chambers with robotics, precise environmental control, and remote sensing techniques to assess plant growth and performance
Perspectives and Challenges of Phenotyping in Crop Improvement. - Copy.pptxRonikaThakur
Plant breeding programmes have been supplemented with the rapid advancements in modern technology. But these cannot be exploited fully until a précised phenotypic data is available which can bridge the gap between Genotype and Environment.
So, this presentation is made to have an overview how the advanced high throughput phenotyping platforms are playing a crucial role in the crop improvement.
Speed Breeding and its implications in crop improvementANILKUMARDASH2
Introduction
History of speed breeding
Methods of speed breeding
Advantages over conventional breeding
Integration with various technologies
Case studies
Opportunities and challenges
Conclusions
Agriculture plays a dominant role in economies of both developed and undeveloped countries. Agricultural remote sensing is not new, starts in back 1950s, but recent technological advances have made the benefits of remote sensing accessible to most agricultural producers. Pakistan is a country of different agro-climatic regions.
The soil is a major part of the natural environment and is vital to the existence of life on the planet.
Satellite imagery will provide the visible boundaries of soil types and a shallow penetration of soils.
Crops yield estimation through remote sensingCIMMYT
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Presentation delivered by Dr. Jesse Poland (Kansas State University, USA) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
This presentation gives the insight idea about drought and its effect on the plant system also talks about development of drought-tolerant variety for ensuring food security.
India being agricultural driven country faces lot of challenges in agricultural sector because of several reasons. I have listed how GIS Technology can help in overcoming such issues
High throughput phenotyping are fully automated facilities in greenhouses or growth chambers with robotics, precise environmental control, and remote sensing techniques to assess plant growth and performance
Perspectives and Challenges of Phenotyping in Crop Improvement. - Copy.pptxRonikaThakur
Plant breeding programmes have been supplemented with the rapid advancements in modern technology. But these cannot be exploited fully until a précised phenotypic data is available which can bridge the gap between Genotype and Environment.
So, this presentation is made to have an overview how the advanced high throughput phenotyping platforms are playing a crucial role in the crop improvement.
Speed Breeding and its implications in crop improvementANILKUMARDASH2
Introduction
History of speed breeding
Methods of speed breeding
Advantages over conventional breeding
Integration with various technologies
Case studies
Opportunities and challenges
Conclusions
Agriculture plays a dominant role in economies of both developed and undeveloped countries. Agricultural remote sensing is not new, starts in back 1950s, but recent technological advances have made the benefits of remote sensing accessible to most agricultural producers. Pakistan is a country of different agro-climatic regions.
The soil is a major part of the natural environment and is vital to the existence of life on the planet.
Satellite imagery will provide the visible boundaries of soil types and a shallow penetration of soils.
Crops yield estimation through remote sensingCIMMYT
Remote sensing –Beyond images
Mexico 14-15 December 2013
The workshop was organized by CIMMYT Global Conservation Agriculture Program (GCAP) and funded by the Bill & Melinda Gates Foundation (BMGF), the Mexican Secretariat of Agriculture, Livestock, Rural Development, Fisheries and Food (SAGARPA), the International Maize and Wheat Improvement Center (CIMMYT), CGIAR Research Program on Maize, the Cereal System Initiative for South Asia (CSISA) and the Sustainable Modernization of the Traditional Agriculture (MasAgro)
Presentation delivered by Dr. Jesse Poland (Kansas State University, USA) at Borlaug Summit on Wheat for Food Security. March 25 - 28, 2014, Ciudad Obregon, Mexico.
http://www.borlaug100.org
This presentation gives the insight idea about drought and its effect on the plant system also talks about development of drought-tolerant variety for ensuring food security.
India being agricultural driven country faces lot of challenges in agricultural sector because of several reasons. I have listed how GIS Technology can help in overcoming such issues
precise weed management is very useful under large land holdings which reduces cost of cultivation to a greater extent. remote sensing plays a major role in site specific weed management
Phenotypic variability of drought avoidance shoot and root phenesTropical Legumes III
Research results suggests it is important to design an integrated strategy combining plant phenomics, genomics, agronomy and modeling to maximize crop productivity in a given environment or stress scenario and to develop guidelines for farming options in the face of climate variability in sub-Saharan Africa.
Transforming Maize-legume Value Chains –A Business Case for Climate-Smart Ag...CIMMYT
CIMMYT Senior Cropping Systems Agronomist Christian Thierfelder presented on climate-smart agriculture in southern Africa in a webinar titled Climate Resilient Agriculture Success Stories – Making a Case for Scale Up.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
18. Different categories of imaging
systems for remote-sensing
evaluation of vegetation and
examples of prototypes capable of
being carried by UAPs of limited
payload are shown: A) RGB/CIR
cameras; B) Multispectral cameras;
C) Hyperspectral VIS-VNIR imager;
D) Longwave infrared cameras or
thermal imaging cameras; E)
Conventional digital (RGB) cameras.
24. Numerical representation of color
There are a number of different systems for representing a given color.
•RGB: Red, Green and Blue
related with color reproduction by computer screens, etc.
•IHS
Intensity, Hue, Saturation
Hue wheel:
0º
Practical for image analysis
120º
240º
•CIE-lab
~ sensitivity of human visual system
Consistent distance
practical for arithmetics
CIE-Lab
27. Picture-derived Vegetation Indices calculated by BreedPix
•Components of the average color of the image
•H (from HIS color-space)
•a* (from CIE-Lab color-space)
•Counting green pixels
•Green Area (% pixels with 60<Hue<120)
•Greener Area (% pixels with 80<Hue<120)
32. Validation: Pic-VIs correlate with leaf area
(however, the relationship may change with phenology)
The relationships between LAI and Hue, a* and u* were similar to
these
Casadesus and Villegas 2013 J. Integ. Plant Biol.
33.
34. Pests and diseases monitoring
Cereal leaf beetle Oulema melanopus L. (Coleoptera, Chysomelidae).
Started in May.
Yellow rust Puccinia striformis f. sp. tritici. A very virulent new strain in
Europe named Warrior/Ambition, first cited in England in 2011. Started
mid-April.
35. Correlation coefficients of Grain Yield (GY) with leaf chlorophyll content and color
parameters calculated from the digital images at jointing (no infested), heading (mildly
infested) and two weeks post-anthesis (severely infested) across 12 wheat genotypes.
Jointing
Heading
Post-anthesis
GY
Chl
GY
Chl
GY
Chl
Chl
Intensity
Hue
-0.39*
0.1
-0.17
―
0.27
0.2
-0.29
0.23
-0.04
―
-0.15
0.37*
0.54***
-0.04
0.87***
―
0.01
0.66***
Saturation
Lightness
a*
0.13
0.19
-0.08
-0.22
0.11
0.09
-0.09
0.23
-0.12
-0.42*
-0.25
0.52**
-0.68***
0.14
-0.88***
-0.50**
0.16
-0.72***
b*
0.14
-0.18
0.09
-0.55***
-0.45**
-0.30
u*
0.01
-0.03
-0.14
0.38*
-0.87***
-0.72***
v*
0.15
-0.15
0.15
-0.54***
-0.08
0.01
GA
-0.2
0.13
0.33
-0.32
0.87***
0.72***
GGA
-0.22
0.21
0.36*
-0.14
0.89***
0.57***
Chl, flag leaf chlorophyll content (SPAD value); Intensity hue saturation (IHS) color space and
each of its components; lightness, a* and b*, color component from Lab; u* and v*, color
component from Luv; GA, green area; GGA, greener area. (*, P< 0.05; **, P < 0.01 and ***, P <
0.001, n = 36).
36. 10
GA
GGA r2 = 0.79***
8
-1
Grain yield (t ha )
r2 = 0.74***
6
4
2
0
0.0
.2
.4
.6
.8
1.0
GA and GGA
Relationships between G and GAA against grain yield across a set bread
wheats
38. Conclusions: Advantages of Pic-VIs
•Very low sampling cost and high resolution
•Sampling *almost+ not conditioned by weather
•Calculation of Pic-VIs can be automated
(a trial with hundreds of plots can be sampled and
processed in the same day)
•Good repeatability and representativity
(taking several pictures per plot allows accounting for its
spatial variability)
•Validated as Vegetation Indices
(before anthesis, GA, a* and u* show R2>0.8 with LAI, GAI
and CDW)
39. Conclusions: Comparison between Pic-VIs
•GA, GGA, a* and u* are more robust than Hue
to environmental conditions
•GA and GGA are almost unaffected by soil color
•GA is the easiest to interpret
(% soil covered by green canopy)
•GGA may be useful at late grain-filling stages to
exclude pixels representing senescent leaves
40. Conclusions: Limitations of Pic-VIs
•As other VI, they get saturated at high LAI
(e.g. at stages with much green biomass, under irrigated
conditions)
•As other VI, they get disturbed after anthesis by the
structure of the canopy
•Effect of spikes
•Vertical distribution of green biomass
41. Normalized Green Red Difference Index (NGRDI)
NGRDI = [(Green – Red)] / (Green + Red)]
Tucker, C.J., 1979. Remote Sensing of Environment 8
Gitelson et al. 2002 Remote Sensing of Environment 80
42. NGRDI = [(Green – Red)] / (Green + Red)]
• Image analysis was performed with ImageJ 1.46r
(http://imagej.nih.gov/ij/).
• ImageJ is a public domain Java image processing
and analysis program created by NIH Image.
• The original images stored by the camera were
converted to its main 3 channels (red-green-blue)
45. Relationship between Normalized Difference Vegetation Index (NDVI.2, left A, B) and the Normalized
Green Red Difference Index (NGRDI.2, right C, D) at anthesis versus grain yield (GY) and aerial
biomass (AB) at maturity.
46. Aerial picture about three weeks after
anthesis of a maize trial with 6 different
N fertilization treatments
(Fontagro Project. Algerri, Lleida, Spain)
Experimental design
49. Beyond vegetation indices
Other parameters could be estimated from digital images.
•Total soil cover
(green+dry vegetation)
•Physiological status
(N-content, Chl,...)
from the color of the
green area only.
•Agronomical yield
components (e.g. spikes
m-2)
50. Some examples of traits and tools
Proximal sensing
Laboratory analyses
Near infrared reflectance spectroscopy
51.
52. Technique
Parameter
Cost per sample
Time
Equipment
IRMS
EA
AACC Method
N content
Ash content
NIRS-prediction
13C
18O
10€
20€
3€
1.5€
0.5€
<10 min
<10 min
<10 min
≈24 h
≈3 min
EA-IRMS
EA
Muffle furnace
*previously reported by Clark et al. 1995; Ferrio et al. 2001; Kleinebecker et al. 2009
13C*
18O
Ash N
NIR spectrometer
53. NIRS a surrogate analysis of
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54. NIRS prediction of δ13C and δ15N
Kleinebecker et al. 2009 New Phytologist 184: 732-739
55. NIRS prediction of ash content and δ18O
Calibration statistics for global sample sets (including inbred lines and hybrids) for N, ash content and
kernels and leaves
Trait
Nkernels
Nleaves
ASHkernels
ASHleaves
18O
kernels
18O
leaves
N
126
152
129
150
128
151
Mean
1.81
1.57
1.47
14.31
31.69
32.97
SD
0.24
0.22
0.24
2.89
1.43
1.25
Range
1.15-2.38
1.04-2.05
0.91-1.90
8.78-21.46
28.05-34.99
29.37-36.46
CV
13.4
14.1
16.2
20.2
4.5
3.8
SEC
0.09
0.10
0.11
0.54
0.82
0.79
R2c
0.87
0.80
0.79
0.97
0.66
0.54
SECV
0.09
0.12
0.13
0.65
1.04
1.00
R2cv
0.87
0.72
0.72
0.95
0.49
0.38
Calibration statistics for hybrid sample set for leaf and kernel N and ash content and kernel
Trait
Nkernels
Nleaves
ASHkernels
ASHleaves
18O
kernels
N
73
86
75
84
70
Mean
1.73
1.49
1.37
14.89
31.03
SD
0.24
0.22
0.27
2.92
1.05
Range
1.15-2.24
0.92-1.95
0.91-1.80
10.02-20.82
29.06-33.53
CV
13.71
14.71
19.71
19.64
3.37
SEC
0.07
0.08
0.10
0.49
0.50
R2c
0.87
0.86
0.82
0.97
0.77
SECV
0.08
0.09
0.14
0.78
0.76
RPD
2.76
1.86
1.89
4.42
1.38
1.26
18O
in
Slope
0.90
0.80
0.79
0.98
0.66
0.57
18O
R2cv
0.87
0.83
0.70
0.93
0.51
RPD
2.79
2.46
1.92
3.76
1.38
Slope
0.87
0.86
0.82
0.98
0.77
N, number of samples; SD, standard deviation; CV, coefficient of variation; R2c, determination coefficient of calibration; R2cv,
determination coefficient of cross-validation; RPD, ratio of performance deviation; SEC, standard error of calibration; SECV, standard
error of cross calibration. All correlations were significant at P<0.001 level.
56. Conclusions
There are different low-cost methodological
approaches that makes high-throughput field
phenotyping affordable for NARS
57. Ackowledgements
•
•
•
•
Affordable field-based high Throughput Phenotyping Platforms
(HTPPs). Maize Competitive Grants Initiative. CIMMYT
Adaptation to Climate Change of the Mediterranean Agricultural
Systems – ACLIMAS.. EuropeAid/131046/C/ACT/Multi. European
Commission
Durum wheat improvement for the current and future Mediterranean
conditionsMejora del trigo duro para las condiciones mediterráneas
presentes y futuras. AGL2010-20180 Spain.
Breeding to Optimise Chinese Agriculture (OPTICHINA). FP7
Cooperation, European Commission - DG Research. Grant Agreement
26604 .