This PowerPoint explains the automation of horticulture and how artificial intelligence (AI) may be used to run related machines.

1. 00
Artificial Intelligence and mechanization in
Horticulture
Deepak Singh
Ph.D Horti. (Fruit Science)
En.Roll. 210133001
Department of Horticulture
College of Agriculture, JNKVV, Jabalpur 482 004
Raushan Kumar
M.Sc Horti. (Fruit Science)
En.Roll. 210143008

2. 01
Content
Introduction
History
Need
Manually Operated Machine
Power Operated Machine
AI Based Technologies
Conclusion
Limitations of AI
Advantage of AI

3. Introduction
02
Mechanization & Artificial Intelligence in Horticulture :
• Need of Modern Horticulture
• It is the use of machinery and equipment, ranging
from simple and basic hand tools to more
sophisticated, motorized equipment and machinery,
to perform various operations in Fruit production.
• AI in horticulture is a human less decision making
system that can process, understand and take the
necessary action according to the crop condition. Its
applications in the horticulture industry are diverse.

4. 03

5. History
04
• The first plough for planting seeds, emerged over 5000 years BC.
• Wooden Animal drawn ploughs were introduced around 1500 BC.
• In 1889, Watts and Kaisar introduced ploughs, corn grinders and chaff cutters at
Cawnpore (now Kanpur) Experimental Farm in Uttar Pradesh.
• SardarJoginder Singh (1897-1946), Agriculture Minister in Punjab introduced the
steam tractors in India in 1914 for the reclamation of wasteland and eradication
of ‘Kans’.
Image source: Report on the progress of agriculture
in India for 1918-19, Government of India, Plate -I.
Fordson Tractor with disc harrows

6. History
• Artificial Intelligence was invented by Herbert Simon
(1965) and the word Artificial Intelligence was coined
by John McCarthy.
• Application of AI in agriculture was first attempted
by McKinion and Lemmon in 1985 to Develop Crop
Simulation Model
• AI is the intelligence exhibited by machines, rather
than human or other animals. The intelligent agents
which perceives it’s environment and takes action to
maximize the success (Russel et al., 2003).
• The latest technologies of automated systems using agricultural robots and drones
have made a tremendous contribution in the agro-based sector. Various hi-tech
computer based systems are designed to determine various important parameters
like weed detection, yield detection, crop quality and many other techniques (Liakos
et al., 2018).
Herbert Simon: Father of AI
05

7. History
• The latest technologies of automated systems using agricultural robots and drones
have made a tremendous contribution in the agro-based sector. Various hi-tech
computer based systems are designed to determine various important parameters
like weed detection, yield detection, crop quality and many other techniques (Liakos
et al., 2018).
Herbert Simon: Father of AI
 There are 7 phases of AI Development :
• First Phases (1952-56) : Birth of Artificial Intelligence
• Second Phases (1956-74) : For algebra word, Theorems, English speaking
• Third Phase (1974- 80) : First AI Winter
• Fourth phases (1980-87) : Focus on mainstream AI research
• Fifth Phase (1987-93) : Second AI winter
• Sixth Phase (1993-2011) : Successfully being used in the technology industry
• Seventh phase (2011- present) : Used for Deep learning, processing of big Data,
General intelligence
06

8. Need
07
• Increase in area and production of horticulture
• Labour costs are increasing
• Availability of skilled labour is reducing
• To meet the food safety characteristics
• Reduce crop losses by harvesting at proper time
• Reduce labour cost and time
• To improve the overall harvest quality and accuracy
• Monitoring of Field
• To early disease detection
• For application of nutrition and fertigation
• For evaluating soil condition
• Reducing the cost of cultivation
• Increasing competition in the national and international markets.
Sharma et al. 2022

9. Steep Rise in Agricultural Wages since 2006-07 and its Effect
08
Source: Bureau of Labour and Employment, Indiastat, KPMG Analysis
*CAGR : Compound annual growth rate

10. 09
Horticulture production share in India Financial Year 2021, by state
0
21.00%
13.00%
10.78%
10.42%
8.67%
8.03%
7.28%
7.12%
6.00%
6.00%
4.00%
STATES
OTHERS
UTTER PRADESH
WEST BENGAL
MADHYA PRADESH
MAHARASHTRA
ANDHRA PRADESH
GUJRAT
BIHAR
KARNATAKA
TAMIL NADU
ODISHA
Source : Statista 2022

11. State-wise Average Daily Wage Rates in Rural India (Men - General
Agricultural Labourers)
10
State/Union
Territory
2014-15 2015-16 2016-17 2017-18 2018-19 2019-20 2020-21
Uttar Pradesh 191.9 199.6 211.8 229.8 247.1 258.8 274.5
West Bengal 216.0 220.2 237.6 255.9 263.1 267.5 288.6
Madhya Pradesh 150.5 160.4 173.1 191.3 196.3 198.6 217.6
Maharashtra 196.7 195.9 196.8 207.4 213.7 231.8 267.7
Andhra Pradesh 216.9 213.3 249.1 269.5 282.0 302.6 318.6
Gujarat 160.0 177.6 184.0 187.9 199.3 208.6 213.1
Bihar 198.9 207.1 212.7 223.0 240.3 258.4 272.6
Karnataka 205.1 228.3 251.9 267.3 288.7 292.0 312.5
Tamil Nadu 334.3 357.0 378.7 385.9 398.7 410.4 434.2
Odisha 180.0 191.3 208.7 222.6 227.4 232.5 255.6
Source: Indian Labour Journal, Labour Bureau, Government of India, Nov 2021
Unit : (₹)

12. Mechanization is required for various Horticultural practices
11
1. Field Preparation : i. Ploughing
ii. Land levelling
iii. Ridge–Furrow making
iv. Pol installation
v. Mulching
Vi. Irrigation trenches
2. Planting : i. Pit digging
3. Plant Nourishment : i. Fertilizer Application
ii. Irrigation - Drip & Sprinkler & Water pumps
iii. Fertigation
4. Training & Pruning
5. Harvesting : Fruit picking

13. Types of Machines
12
Machine
Mannually
Operated
Power
Operated
Man
Driven
AI Driven
A machine is a thing that is created
by people to make work easier

14. A. Manually operated
13
Grub Hoe Rake Showel Pruning Saw Looping Shear
Pruning Shear
Wheel Barrow
Hedge Shear Fruit Picker
Pruning Sword
Budding-Grafting Knife

15. A. Manually operated
14
Tree pruner
Hand Rotary Duster
Foot Sprayer
Knapsack Sprayer

16. B. Power Operated
15
Man Driven
1.1 : Tractor : (Force Orchard Mini)
• Specialized for vineyards, fruit & nut orchards
• Help farmers seat comfortably
• Pick high hanging fruits at the same time
• Allow easy passage between tree rows
• Mini space require
• Power lies between 11-36 HP
Diesel engine based
Price : 1,50,000 to
5,00,000 Rs
1.2 : Land Leveller :
• It improves crop establishment, crop stand
• Improve water coverage and water loss.
• It can reduce the operation time by 10 to 15 per cent.
• Can reduce weeds by up to 40 per cent by levelling.
• It should be tractor mouted with 30-60 HP.
Tractor Mounted
Price : 15,000 to
1,00,000

17. B. Power Operated
16
Man Driven
1.3 : Earth Auger/ Digger :
• Earth Auger is used in agriculture purpose for digging holes
in the soil.
• It makes holes for plantation or for erecting poles.
• It is much easier to dig the soil with this machine and the
process takes less time.
• Tractor mounted will required 35-40 HP.
Petrol engine based
Price : 8,000 to 35,000 RS
Tractor mounted
Price : 2,00,000 to
3,00,000
Digging Method Efficiency
Time
Requirement
Manual labour (100 X 100 X 100 cm) 2-4 pits 1day
Tractor operated post hole digger - gear
drive
250-300 1 Hour
Tractor operated Post hole digger -
hydraulic drive
300-400 1Hour
Lal et al., 2021

18. B. Power Operated
17
1.5 : Compact Spreader
• Specialized for vineyards, fruit & nut orchards
• Help farmers seat comfortably
• Pick high hanging fruits at the same time
• Allow easy passage between tree rows
• Mini space require
• Power required 25 HP.
Diesel engine based
Price : 5,00,000 to
7,00,000 Rs
1.4 : Mulch Laying Machine :
• Purpose of the machine is to lay the mulching paper on the beds
• Also punching the holes.
• It can help to reduce the capital cost and time of laying
• All operation in one pass of the machine.
• Controlling weed, moistening of soil, increasing of soil nutrients,
reduction of insect's pests and high crop yield
• Tractor Power required 35-55 HP .
Tractor mounted
Price 50,000 to 1,00,000
Capacity : 0.24 ha h-1
Parameter
Conventional Method Cost
(Through Labour)
Fertilizer Spreader Cost
Cost per acre 600 – 700/- 100 – 150/-
Time per acre 2 hour 1 hour
No. of labours 04 01
Lal et al., 2021
Man Driven

19. B. Power Operated
18
1.7 : Orchard Prunner
• Used for orchards like Lemon, Oranges, mandrains,
and vine yard
• Used for high density Mangoes where height of tree
is approximately 4-5 ft.
• For trimming of excessive branches
• Requires 80-90 HP Tractors for operation.
Tractor Mounted
Price : 4.62 lacs to 8 lacs
1.6 : Tractor Trailed Sprayer
• Suitable for High Density Planting
• Liquid Fertilizer Application
• Used for water projection, crop performance materials,
weed killer, pest maintenance chemicals,
• Moreover, a tractor mounted sprayer machine applies
pesticides, fertilisers, herbicides on farm crops.
• Sprayer speed 3.0 km/h
• booms width of 7-11.0 m
• Mouted tractor power require 3-5 HP.
Tractor Mounted
Price : 50,000 to
2,50,000

20. B. Power Operated
1.8 : Flower (Blossom) and Fruit
Thinner :
• Controlled thinning that you see
directly after execution
• Thins without chemical use
• Increase in fruit size and quality
by increasing early sugar
allocation to limited number of
fruit
• Reduces biennial tendencies
• Fast travel speed ensures high
treated area per hour
• Thinning can be performed in all
weather conditions
• Can be used for all current
cultivars
• 20-30 HP tractor are required
19

21. B. Power Operated
20
 Time (h ha−1) required to perform the mechanical thinning, and the hand thinning follow-
up, as compared with the only manual thinning
Assirelli et al., 2018
Engineering and Transformation Research Centre
Monterotondo, Italy
Parameters Unit Apricot Peach
Flowers Fruits Flowers Fruits
Mechanical
Thinning
h ha−1 0.51 0.76 0.51 0.44
Hand Thinning
follow up
h ha−1 22.2 37.3 87 120
Control (Only
manual thinning)
h ha−1 45.4 72 152 125
Labour Saving by
using Machines
% 51.1 48.2 42.8 40
CASE
STUDY

22. Mechanical Fruit Harvester :
21
Limb Shaker :
• The shaker was powered by a 2-stroke (spark ignition)
engine.
• crank mechanism to transmit power to a limb through a
boom and C-shaped clamp
• Shakers can be controlled remotely from the operators
handle on the shaker
• using limb shaker citrus fruits, apricots, peaches and
cherries can be harvested.

23. Mechanical Fruit Harvester :
22

24. Mechanical Fruit Harvester :
23
Trunk Shaker :
 Fruit tree shaker is special equipment for quick shaking of ripe fruits from
trees.
 The tree shaker facilitates the process of harvesting from any trees, saves
your energy, significantly reduces time to perform this difficult work and
also prevents trees from broken branches.
 Fruits mainly deciduous fruits, olives, nuts, and citrus are used to remove
by trunk shaker.
 Mostly a tractor-mounted trunk shaker
 Overall, the tractor mounted shaker was more effective
 With 72% detachment accuracy

25. 24
• Comparison of mean values of fruit detachment (%) at different levels of shaking
frequencies in Sweet cherry.
• Comparison of mean values of fruit detachment (%) at different levels of shaking
duration in Sweet Cherry.
Zhou et al., 2013
Applied Engineering in Agriculture, Vol. 29 issue 5

26. Crop Type of Shaker Method of Clamping Reference
Sweet / Tart
Cherry
Hydraulic trunk Shaker
Hydraulic limb shaker
Clamp the trunk
Impact limb
Norton et al., 1962
Peterson and Wolford,
2001
Gas engine powered
handheld shaker
Hook limb Chen et al., 2012
Citrus
Oscillated air-flow shaker
Hydraulic vertical canopy
shaker
Air blast canopy
Clamp
secondary limb
Whitney and Patterson,
1972 Sumner, 1973
Canopy shaker Impact limb Savary et al., 2010
Apple/ Peach
Impulse trunk shaker
Spring activated impact
Trunk shaker
Clamp trunk
Clamp trunk
Pellerin et al., 1979
Pellerin et al., 1982
Mango Mechanical limb shaker Clamp limb
Parameswarakumar and
Gupta, 1991
Peach/Apricot
Hydraulic limb shaker
Gas engine powered
handheld shaker
Clamp limb
Hook limb
Erdoğan et al., 2003
Torregrosa et al., 2008
Olive
Pneumatic limb shaker
Hydraulic trunk shaker
Hook limb
Clamp trunk
Sessiz and Özcan, 2006
Blanco-Roldán et al., 2009
Pistachio nuts Hydraulic limb shaker Clamp limb Polat et al., 2007
Stone pine Hydraulic trunk shaker Clamp trunk and shake Castro-García et al., 2011
Summary of shaking and clamping based mechanical harvesting of various fruit crops 25

27. Artificial Intelligence
26
Progression Of Artificial Intelligence -
Narrow AI
Artificial general
intelligence
Artificial super
intelligence
Hossani et al., 2020

28. Artificial Intelligence
27
Various field Where AI can be used :
1. AI-Remote Sensing: Crop Health
Monitoring
2. AI - Driver less Tractor
3. AI For Weeding
4. Automated Irrigation System
5. Robots
6. Use of Weather Forecasting
7. Analyzing Crop Health by Drones
8. Precision Farming
9. Artificial Intelligence in Harvesting
the Crops
10. Chatbots
11. AI- Crop Simulation Models

29. Working Principle of Artificial Intelligence
28
AI Tractor
AI Based Machine

30. AI- CROP SIMULATION MODELS :
 Artificial intelligence with Crop Simulation Models to Understand and Predict
Agricultural Systems Dynamics.
Applications of AI- Crop simulation modeling:
 Environmental characterization
 Optimizing crop management
 Pest and disease management
 Impact of climate change
 Yield Forecasting
 Models in Horticulture : Aloha Pineapple Model, SIMPINA Model,
29

31. CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
30
AI Based Weed Control

32. CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
31
AI Based Weed Control

33. CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
32
AI Based Weed Control
• The Robot having the sensors that are mounted with it
and their respective local frames.
1. Stereo Camera
 The camera baseline is 12 cm.
 It recorded synchro-nized left and right images
 Resolution of image is 672 ×376 px.
2. Motors encoders
 Used three Hall effect sensors coupled with each
wheel to measure rotational angle increments.
 Assist with motion in right path

34. CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
33
AI Based Weed Control
• 3. GPS
 It has two GPS module mounted with the robot
 One is for geographical location on the land
 Another one is for provide AI-based detected weed
population’s imagery position on the land
4. IMU
 It Stands for Inertial measurement Unit
 Its is a device which work on the principle of
Gyroscope
 Give the info about Orientation of the device or
machine

35. 34
 Artificial Intelligence For Weed Detection - A Techno-efficient Approach
Case Study
Johnson and Akerele, 2020
: Department of Computer Science, Federal University of Agriculture, Nigeria
Image Capture
Image Processing
Reconvert the image to specification
Background Colour Removal
Grey Transformation for
weed detection Detected images of
selected weeds from
binary images
Now the Data Has been
send to Device for
Execution of Weeding
Machine Network System
Acuracy of
Weeding
1. Convolution Neural Network (CNN) 95 %
2. Support Vector Machine (SVM) 95 %
3. Artificial Neural Network (ANN) and Scatter
Transformation Technique (STT)
92.5%
4. K-Nearest Neighbourhood (KNN) classifier 96.4%
5. Fuzzy Real Time Classifier (FRTC) 91.9%

36. 35
CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
2) Crop and Soil Health Monitoring AI
Image Data Base of
soil and Leaf for
Image Processing to
differentiate Healthy,
Diseased, Nutrient
status, Moisture
Level
Image aquisition

37. 36
CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
2) Crop and Soil Health Monitoring AI
Spectroradio meter Canopy Analyser
Line Quantum

38. 37
CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
2) Crop and Soil Health Monitoring AI

39. 38
 Mango Disease Detection by using Image Processing
Case Study
Veling et al., 2019
: Department of Electronics and Telecommunication, Mumbai University
Disease
Image Factor
Healthy
leaf
Anthracnose
(Leaf)
Powdery
Mildew
Healthy
Fruit
Anthracnose
(Fruit)
Autocorrelation 24.0686 17.3715 16.0947 39.9239 16.2034
Contrast 0.2551 0.5068 0.2033 0.3645 0.2669
Correlation 0.9743 0.8764 0.9631 0.9540 0.9196
Cluser
Promenance
461.461 86.4571 185.303 802.258 96.3784
Cluser Shade 22.7937 13.2901 19.9951 92.5885 16.3252
Energy 0.3272 0.4911 0.3064 0.6684 0.5730
Entropy 1.22003 0.8621 1.2864 0.5658 0.7224
Variance 24.0454 17.4817 16.1352 39.9117 16.2204
Dissimilarity 0.06867 0.1689 0.0828 0.0729 0.09645

40. 39
 Identification of Citrus Greening using A VIS-NIR Spectroscopy Technique
Case
Study
Mishra et al., 2012
: American Society of Agricultural and Biological Engineers

41. 40
 Comparison of healthy leaf, Huanglongbing and Citrus Canker infected
leaves
Case
Study
Shankaran & Ehsani, 2013

42. CHATBOTS :
 Chatbots (sometimes referred to as a chatterbots) are
evolutions of Apps with the aim to provide fast solution
to simple, urgent problems and being much easier and
cheaper to develop.
 In the agricultural sector, chatbots are still very few but
have great potential to provide farmers with fast answers
and recommendations on specific problems (e.g. plant or
animal disease identification and treatment).
 As a chatbot receives new words and dialogues, the
number of inquiries that it can reply to and the accuracy
of each response will increase.
 Chatbot virtual assistants are increasingly used as they
allow to save time and gain in knowledge by providing
answers on-the-fly.
Chatbot virtual assistants
41
Chat GPT
Kishan Suvidha
App
Farmer Bot

43. 42
CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
AI Based Fruit Harvester
Tevel Aerobotics Technologies
Advantages :
• Manual harvesting of fruits and vegetables is a
laborious, slow, and time-consuming task in crop
production so used of AI can benefit for that.
• Managing the crops in a short period of time,
• Reduced labor involvement, higher quality, and
better control over environmental effects.

44. 43
CURRENT APPROACHES & ACHIEVEMENTS OF AI IN HORTICULTURE:
AI Based Fruit Harvester
Tevel Aerobotics Technologies

45. 44
 Fruit recognition method for a harvesting robot with RGB-D cameras
Case
Study
Yoshida et al., 2022
(a) Pear b) Apple
Figure: Fast recognition and
location of target fruit.
Fruit Sorting system
Result of sphere shaper estimation
(a) Pear b) Apple
(a) Pear b) Apple
Confirmation of
Harvestability

46. 45
 Fruit recognition method for a harvesting robot with RGB-D cameras
Case
Study
Yoshida et al., 2022
Methods Harvestable fruits
Harvestibility confirmation by skilled worker 137 Fruits
Harvestibility confirmation RGB-D camera
based robot
119 Fruits
Accuracy percentage with RGB-D method 87 %
Peduncle length estimation
Measured Value Estimated Value Error
Case -1 (Pear) 0.913 m 0.919 m -0.006 m
Case -2 (Apple) 0.992 m 0.961 m 0.032 m

47. Future Prospects :
46
The future of AI in Horticulture will need a
major focus on universal access because
most cutting-edge technologies are only
used on large, well-connected orchards.
Increasing outreach and connectivity to even
small farms in remote areas across the world
will cement the future of machine learning
automated agricultural products and data
science in farming. To cope with upcomming
challenges, horticulture requires a
continuous and sustainable increase in
productivity and efficiency on all levels only
possible with use of precision by
incorporating of new Techs

48. 47
 Artificial intelligence, if coded properly, helps in reducing the error
 AI allow logical applications without emotions
 They are programmed for long hours and can continuously perform
 AI allows handling multi-dimensional and heterogeneous sources of data
and discovering.
 Specific trends and patterns that would not be apparent to humans.
 AI adapts through progressive learning algorithms to let the data do the
programming.
 AI can help predicting what a user will type, ask, search, and do. They can
act as assistants and recommend actions/solutions.
Advantages of Artificial Intelligence :

49. 48
 Lack of familiarity with high tech machine learning solutions in farms across
most parts of the world
 Cost is a big challenge
 AI systems also need a lot of data to train machines and to make precise
predictions
 Require a skilled person to operate this system
 Total dependency on AI
 It’s expensive
 Unemployment or Joblessness
 Hacking of data
 The AI can be programmed to do something devastating.
 Knowledge gap
 AI applications do not include emotions and moral values.
Limitation of Artificial Intelligence in Horticulture :

50. 49
Name of machine Cost in percentage of purchase price for usable life
(in Year)
1 2 3 4 5 6 7 8 9
Stationary engine 3.8 10.8 19.8 30.3 42 55.5 70.3 86.4 102.6
Electric motor 2 5.8 10.7 16.5 23 30.1 38.4 46.7 56.1
Power tiller 3.8 10.8 19.8 30.3 42 55.5 70.3 86.4 102.6
Tractor (wheeled and crawler) 3.2 9.0 16.5 25.3 35 46.2 58.6 72 85.5
Combine (self-propelled) 4.9 13 23 34.3 46.8 60.6 - - -
Combine (mounted and drawn) 6.6 17.3 30.4 44.8 61.9 80 100.3 - -
Seed drill 4 10.5 18.6 27 38.9 49 60.9 73.4 86.5
Seed-cum-fertilizer drill 5.5 14.4 25.4 38 52.5 67 83.2 100.3 -
Planter 6 14.8 29 36.4 48.7 61.6 75.4 88.7 104.4
Plough 6 14.8 29 36.4 48.7 61.6 75.4 88.7 104.4
Disc harrow 6 14.8 29 36.4 48.7 61.6 75.4 88.7 104.4
Cultivator 6 14.8 29 36.4 48.7 61.6 75.4 88.7 104.4
Power sprayer 5.5 14.4 25.4 38 52.5 67 83.2 100.3 -
Seed cleaner 12.6 33.2 58.9 87.3 120.5 - - - -
Agricultural trailer 2.5 6.5 11.5 17.2 23.8 30.4 37.7 45.4 53.6
 Percentage of accumulated repair cost of farm machinery
Singh & Mehta, 2015
CIAE, Bhopal
Case Study

51. B. Power Operated
14
Man Driven
1.1 : Tractor : (Force Orchard Mini)
• Specialized for vineyards, fruit & nut orchards
• Help farmers seat comfortably
• Pick high hanging fruits at the same time
• Allow easy passage between tree rows
• Mini space require
Diesel engine based
Price : 5,00,000 to
7,00,000 Rs
1.2 : Land Leveller :
• It improves crop establishment, crop stand
• Improve water coverage and water loss.
• It can reduce the operation time by 10 to 15 per cent.
• Can reduce weeds by up to 40 per cent by levelling.
Tractor Mounted
Price : 15,000 to
1,00,000
: Percentage change in population of male and female agricultural labourers in 2011 as compared
to 2001 superimposed with tractor density for states in plain areas.
Mehta et al., 2018
ICAR-CIAE, Bhopal
50

52. Conclusion
51
The cultivation of crops with high yield and improved quality is becoming
an increasingly difficult undertaking as the population grows. In addition
to assisting farmers with automating their crop cultivation techniques,
artificial intelligence in horticulture also encourages farmers to switch to
precision cultivation for increased crop production and better quality while
using fewer resources. In this manner, extra resource and energy loss can
be reduced and more advantages can be realised.

53. XXX
Thank You