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Plant	
  water	
  assessment	
  through	
  aerial	
  
thermography	
  
	
  A	
  mul4-­‐copter	
  prac4cal	
  case	
  in	
 ...
SUMMER	
  
«More	
  crop	
  per	
  drop»	
  
1-­‐Agricultures	
  consumes	
  most	
  of	
  
the	
  world	
  water	
  resources	
  (70...
Photosynthesis
Stomatal	
  conductance	
  
0
2
1
Two	
  main	
  “ways”	
  to	
  improve	
  Water	
  Use	
  Efficiency	
  (WU...
WHY	
  gs?	
  
gs	
  is	
  a	
  good	
  indicator	
  of	
  plan	
  water	
  status	
  and	
  permit	
  characterize	
  
th...
How	
  to	
  scale-­‐up	
  levels?	
  
Engines	
  MK3638	
  Li-­‐Po	
  BaFery	
  8Amp	
  
30C	
  
Camera	
  mount	
  
servo-­‐stabilized	
  
carbon-­‐fiber	
  
UA...
Advantages	
  and	
  limita4ons	
  of	
  the	
  different	
  types	
  for	
  
plant	
  ecophysiology	
  
Parameter	
   Wing...
How	
  to	
  detect	
  water	
  stress	
  from	
  an	
  UAV?	
  
Reference	
   UAVs	
  type	
   Crop	
   Thermal	
  
Index	
  
gs	
  (R2)	
   Poten4al	
  
hydric	
  (R2)	
  
Baluja	
  et	...
Thermal	
  indexes…	
  an	
  aqempt	
  to	
  normalize	
  the	
  environment	
  (Idso	
  et	
  al.,	
  1980;	
  
Jones,	
 ...
​ 𝑇↓𝑙 −​ 𝑇↓𝑎 =  ​[​ 𝑟↓𝐻𝑅 (​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 )𝛾​ 𝑅↓𝑛𝑖 − 𝑝​ 𝑐↓𝑝 ​ 𝑟↓𝐻𝑅 𝐷]⁄{𝑝​ 𝑐↓𝑝 [𝛾(​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 )
+ 𝑠​ 𝑟↓𝐻𝑅 ]} 	
  
​ 𝑟↓𝑠...
More	
  thermal	
  arial	
  
results	
  with	
  an	
  
hexakopter	
  
	
  
DEM	
  model	
  by	
  Agisov	
  
Photoscan	
  
...
Plant	
  truth-­‐data	
  at	
  leaf	
  level	
  
-­‐Leaf	
  water	
  poten4al	
  
	
  
-­‐Leaf	
  gas-­‐exchange	
  measur...
More	
  integra4ve	
  plant	
  truth-­‐
data	
  at	
  stem-­‐plant	
  level	
  
	
  
	
  
	
  
-­‐Stem	
  Sap	
  flow	
  	
...
Grenache,	
  several	
  days	
  of	
  campaign:	
  thermal	
  indices	
  vs	
  gs	
  at	
  leaf	
  level	
  
CWSI	
  IG	
 ...
Grenache,	
  several	
  days	
  of	
  campaign:	
  Tc-­‐Ta	
  and	
  Canopy	
  conductance	
  vs	
  
gs	
  at	
  leaf	
  l...
Tc-­‐Ta	
  and	
  Canopy	
  conductance	
  vs	
  midday	
  water	
  poten4al	
  at	
  leaf	
  level	
  
in	
  both	
  cv	
...
Grenache,	
  several	
  days	
  of	
  campaign:	
  Tc-­‐Ta	
  and	
  Canopy	
  conductance	
  vs	
  
sap	
  flow	
  at	
  s...
So…	
  we	
  have	
  an	
  es4ma4on	
  of	
  the	
  transpira4on…	
  but	
  we	
  also	
  need	
  to	
  
know	
  the	
  fo...
Environmental	
  factors	
  sensi[vity	
  of	
  the	
  leaf	
  energy	
  balance	
  model	
  
Meteodruino	
  
:	
  a	
  micro-­‐open-­‐hardware	
  meteorological	
  sta[on	
  for	
  mul[-­‐copters:	
  	
  
-­‐Piranom...
:	
  a	
  micro-­‐open-­‐hardware	
  meteorological	
  sta[on	
  for	
  mul[-­‐copters:	
  	
  
Meteodruino	
  
calibra4on...
:	
  sampling	
  around	
  vines	
  	
  
-­‐UAVs	
  can	
  assess	
  crop	
  water	
  status	
  
through	
  termography	
  
	
  
-­‐Improve	
  spa4al	
  and	
  tem...
Thanks	
  
	
  
	
  
	
  
And	
  
Good	
  Fligths!!	
  
	
  
Micro-DRONES for low-cost high-throughput
phenotyping?
Micro-drones for low-cost high-through-put
phenotyping?
Micro-DRONES for low-cost high-throughput
phenotyping?
Micro-drones for low-cost high-through-put
phenotyping?
TOSHI	
  PLANTS	
  
Lecture by  Xurxo Gago
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Lecture by Xurxo Gago

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Plant water assessment through aerial thermography
A multicopter practical case in a vineyard

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Lecture by Xurxo Gago

  1. 1. Plant  water  assessment  through  aerial   thermography    A  mul4-­‐copter  prac4cal  case  in  a  vineyard     Xurxo  Gago  
  2. 2. SUMMER  
  3. 3. «More  crop  per  drop»   1-­‐Agricultures  consumes  most  of   the  world  water  resources  (70%)     2-­‐Another  industries  compite  for   the  water     3-­‐45%  of  food  supply  is  produced   in  irrigated  fields       4-­‐Irrigated  fields  just  cover  18%  of   total  agriculture  lands   Doll  &  Siebert,  2002;  Gilbert  et  al.,  2012  
  4. 4. Photosynthesis Stomatal  conductance   0 2 1 Two  main  “ways”  to  improve  Water  Use  Efficiency  (WUE)   M a x i m i z i n g photosynthesis G e n e t i c improvement & Biotechnology Regulated deficit irrigation Soil and crop management Irriga4on  control  ,  the   quickiest  way  to  improve   on  farm  WUE  
  5. 5. WHY  gs?   gs  is  a  good  indicator  of  plan  water  status  and  permit  characterize   the  degree  of  stress   Stomatal conductance (mmol H2O m-2 s-1) 0 100 200 300 400 AN(µmolCO2m -2 s-1 ) 0 2 4 6 8 10 12 14 16 18 Without  water  stress   Moderate  water  stress   Severe  water  stress   gs > 150 mmol m-2s-1 50 < gs < 150mmol m-2s-1 gs < 50mmol m-2s-1 Medrano  et  al.  2002.  Ann  Bot.   89,895-­‐905     Data  of  10  years  of   measurements  in  pot   and  field  plants  of  Manto   negro  and  Tempranillo   and  in  22  cvs  in  pots  
  6. 6. How  to  scale-­‐up  levels?  
  7. 7. Engines  MK3638  Li-­‐Po  BaFery  8Amp   30C   Camera  mount   servo-­‐stabilized   carbon-­‐fiber   UAVEurope  ®   Mul4-­‐copter  6  engines  equipped  with  a  thermal  camera  :   Main  parts   Thermal  camera   GOBI384  Xenics®!   Ubiquiwifi  ,   on  line    wi-­‐fi  data     streaming  (Ubiqui[   Networks®)   Propellers     (APC  12x3,8  inc)   Frame   (carbon  fiber  Air-­‐Sci   UAVEurope®)   Electronic  systems:   Mikrokopter®  
  8. 8. Advantages  and  limita4ons  of  the  different  types  for   plant  ecophysiology   Parameter   Wing-­‐span   planes   Helicopters   Mul4-­‐copters   Camera   resolu4on   Lower,  +  al4tude     Higher,  -­‐  al4tude   Higher,  -­‐  al4tude   No  hovering   Hovering   Hovering   Mapping     Wider     Reduced   Reduced   Logis4cs   Land-­‐off   requirements   No  requirements   No  requirements   Exper4se   ++  technical   knowledge   +++  technical   knowledge   Plug´n´play   Flight   ++  technical   knowledge     +++  technical   knowledge   User  friendly  
  9. 9. How  to  detect  water  stress  from  an  UAV?  
  10. 10. Reference   UAVs  type   Crop   Thermal   Index   gs  (R2)   Poten4al   hydric  (R2)   Baluja  et  al.   2012   Wing-­‐span   fixed  wing   Grapevine   Tcanopy  –   Tair   0.69   0.5   CWSI   0.68   0.5   IG   0.72   0.5   I3   0.5   0.42   Zarco-­‐ Tejada  et   al.  2012   Wing-­‐span   fixed  wing   Citrus   sinensis   Temperature   0.78   0.34   González-­‐ Dugo  et  al.   2013   Wingspan   fixed-­‐wing   Almond   Tc-­‐Ta   0.67   Peach     0.92   Lemon   0.48   Orange   0.27   Apricot   0.64   Aerial  thermography  for  water  stress  detec4on  in  crops   Berni  et  al.    2009   González-­‐Dugo  et  al.  2012  
  11. 11. Thermal  indexes…  an  aqempt  to  normalize  the  environment  (Idso  et  al.,  1980;   Jones,  1999)     CWSI  =  T  canopy  –  Twet  /  Tdry  –  Twet     IG  =  T  dry  –  Tcanopy  /  Tcanopy  –  Twet     I3=    T  canopy  –  Twet  /  Tdry  –  Tcanopy     And  the  leaf  energy  balance:   ​ 𝑇↓𝑙 −​ 𝑇↓𝑎 =  ​[​ 𝑟↓𝐻𝑅 (​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 )𝛾​ 𝑅↓𝑛𝑖 − 𝑝​ 𝑐↓𝑝 ​ 𝑟↓𝐻𝑅 𝐷]⁄{𝑝​ 𝑐↓𝑝 [𝛾(​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 ) + 𝑠​ 𝑟↓𝐻𝑅 ]}    ​ 𝑟↓𝑠 =  ​− 𝑝​ 𝑐↓𝑝 ​ 𝑟↓𝐻𝑅 [𝑠(​ 𝑇↓𝑙 −  ​ 𝑇↓𝑎 )+ 𝐷]  ⁄{𝛾  [(​ 𝑇↓𝑙 −​ 𝑇↓𝑎 )𝑝​ 𝑐↓𝑝 −  ​ 𝑟↓𝐻𝑅 ​ 𝑅↓𝑛𝑖 ]}−  ​ 𝑟↓𝑎𝑤     How  to  detect  the  drought  from  an  UAV?  
  12. 12. ​ 𝑇↓𝑙 −​ 𝑇↓𝑎 =  ​[​ 𝑟↓𝐻𝑅 (​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 )𝛾​ 𝑅↓𝑛𝑖 − 𝑝​ 𝑐↓𝑝 ​ 𝑟↓𝐻𝑅 𝐷]⁄{𝑝​ 𝑐↓𝑝 [𝛾(​ 𝑟↓𝑎𝑤 +  ​ 𝑟↓𝑠 ) + 𝑠​ 𝑟↓𝐻𝑅 ]}    ​ 𝑟↓𝑠 =  ​− 𝑝​ 𝑐↓𝑝 ​ 𝑟↓𝐻𝑅 [𝑠(​ 𝑇↓𝑙 −  ​ 𝑇↓𝑎 )+ 𝐷]  ⁄{𝛾  [(​ 𝑇↓𝑙 −​ 𝑇↓𝑎 )𝑝​ 𝑐↓𝑝 −  ​ 𝑟↓𝐻𝑅 ​ 𝑅↓𝑛𝑖 ]}−  ​ 𝑟↓𝑎𝑤     Leaf  energy  balance  (Jones,  1992)  +  meteorological  data  =  gs   es4ma4on   How  to  detect  drought  from  an  UAV?  
  13. 13. More  thermal  arial   results  with  an   hexakopter     DEM  model  by  Agisov   Photoscan     -­‐Flying  al4tude:  30  m     -­‐Resolu4on  :  1,4  cm/px     -­‐RMSE  :  1,1  cm     -­‐2  cv  under  3  irriga4on   treatments   Gago  et  al.  2013  a  &  b  Gago  et  al.  2013  a  &  b   Tempranillo  Grenache   WW   D   C   C   WW   D  
  14. 14. Plant  truth-­‐data  at  leaf  level   -­‐Leaf  water  poten4al     -­‐Leaf  gas-­‐exchange  measurements    
  15. 15. More  integra4ve  plant  truth-­‐ data  at  stem-­‐plant  level         -­‐Stem  Sap  flow           -­‐Whole-­‐plant  chamber      
  16. 16. Grenache,  several  days  of  campaign:  thermal  indices  vs  gs  at  leaf  level   CWSI  IG   Gs  (mol  H2O  m-­‐2  s-­‐1)   Date  1   Date  2   Date  3   D  WW   C  
  17. 17. Grenache,  several  days  of  campaign:  Tc-­‐Ta  and  Canopy  conductance  vs   gs  at  leaf  level   Tc-­‐Ta  (ºC)  Gc    (mol  H2O  m-­‐2  s-­‐1)   Gs  (mol  H2O  m-­‐2  s-­‐1)   Date  1   Date  2   Date  3   D  WW   C  
  18. 18. Tc-­‐Ta  and  Canopy  conductance  vs  midday  water  poten4al  at  leaf  level   in  both  cv  Tc-­‐Ta  (ºC)   Midday  water  poten4al  (MPa)   Tc-­‐Ta  (ºC)   Tempranillo   Grenache  Date  1   Date  4  
  19. 19. Grenache,  several  days  of  campaign:  Tc-­‐Ta  and  Canopy  conductance  vs   sap  flow  at  stem  level   Date  1   Date  2   Date  3   Tc-­‐Ta  (ºC)  Gc    (mol  H2O  m-­‐2  s-­‐1)   Sapflow  (l/h)   Sapflow  (l/h)   Drought   Watered  
  20. 20. So…  we  have  an  es4ma4on  of  the  transpira4on…  but  we  also  need  to   know  the  foliar  area  to  can  calculate  the  needed  irriga4on     WW  D   C   Tempranillo  Grenache   WW  D   C   R²  =  0,9301   P<0.05   0   2   4   6   8   10   12   14   16   0   2   4   6   8   Canopy  es4mated  (m2)   Plant-­‐truth  foliar  area  (m2  /plant)   R²  =  0,9497   P<0.05   0   2   4   6   8   Plant-­‐truth  foliar  area  (m2/plant)   W   D   C   Tempranillo   Grenache  
  21. 21. Environmental  factors  sensi[vity  of  the  leaf  energy  balance  model  
  22. 22. Meteodruino   :  a  micro-­‐open-­‐hardware  meteorological  sta[on  for  mul[-­‐copters:     -­‐Piranometer   Apogee  SP110   Sensirion  SHT  75   (Temp  +  HR  (%)   Collec4ng  micro-­‐ meteorological   data  close  to  the   plants  
  23. 23. :  a  micro-­‐open-­‐hardware  meteorological  sta[on  for  mul[-­‐copters:     Meteodruino   calibra4on  
  24. 24. :  sampling  around  vines    
  25. 25. -­‐UAVs  can  assess  crop  water  status   through  termography     -­‐Improve  spa4al  and  temporal   resolu4on  than  aircravs  and  satellites   but  cover  minor  areas     -­‐S4ll,  all  the  process  must  be  more   «user-­‐friendly»  and  automated  to  can   be  generalized  for  agriculture  
  26. 26. Thanks         And   Good  Fligths!!    
  27. 27. Micro-DRONES for low-cost high-throughput phenotyping? Micro-drones for low-cost high-through-put phenotyping?
  28. 28. Micro-DRONES for low-cost high-throughput phenotyping? Micro-drones for low-cost high-through-put phenotyping?
  29. 29. TOSHI  PLANTS  

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