Computer Integrated Agricultural Production

Copyri ght © (FAC 11th Triennial Wo rld Congress, T allinn , Estonia, USSR , 1990

COMPUTER INTEGRATED AGRICULTURAL PRODUCTION K. Hatou, H. Nishina and Y. Hashimoto Department of Biomechanical Systems, Ehime University, M atsuyama, Japan

Abstract Greenhouse production of vegetables has been remarkably developed.

Furthermore. vegetables could be

cultivated in the factory where such environmental factors as light intensity and temperature are controlled just like in process industries.

In the system, many computers are used for environmental

control, nutrient control and management of cultivation.

Of course, the artificial intelligence is also

introduced for the expert system for control and diagnosis of the cultivated vegetables. hand,

On the other

progress in automated mechanization for seeding and transplanting has made "greenhouse

automation" fit for practical use just like "factory automation (FA)" in industries. Now, process industries are rationalized based on the concept of so called "Computer Integrated Manufacture (CIM)", Therefore, it might be noted that the system in the agricultural production such as the vegetable factory should also be considered based on the concept of CIM, That is the "Computer Integrated Agricultural Production (ClAP)". In this paper, we examine the vegetable factory from the "ClAP" point of view. Computer network composed of both us ual personal computer for environmental control and the special computer for the artificial in t elligence is examined. It seems evident that the ClAP discussed in this paper is expected as the most effective system in the

coming generation. Keywords Computer application; Artificial intelligence; Control application; Agriculture INTRODUCTION

first plant factory in the world was built in Denmark. But

Environmental control in the plant factory with artificial

cultivation stage is treated as a manufacturing process, and

lighting is similar to that in the growth chamber. On the

several cultivating processes are combined into a batch

other hand,

in the plant factory using solar energy,

process and controlled as assembling line. This makes a

environmental control is similar to that in the greenhouse. Con trolling the en vironmen t in greenhouse is difficult from

grea t change in the concept of agriculture, and impacts the

the engineering

because of the great

Since then, several plant factories have been developed in

disturbance from sunlight.

the world.

In environmental control of greenhouse, great progress has

environmental control system like a large growth chamber

been made in Holland as the leader in the world on this

(Hashimoto, 1987). In this system, the emphasis is laid on

the history is not so long.

point of

view,

In the original system, the

image of the traditional cultivation in the world. Now, the plant factory noticed in Japan has

It is impossible to introduce all the results that

the process control other than on manufacturing process. It

they have achieved in this limited space, Summarizing the researches about greenhouse control from the dynamical

is the system with standardized cultivating process, with

aspect.

which the maximum production can be realized in the short

approach, we can consider that experiments are mainly

period, In detail, the system can make plants grow three to

carried out based on transport phenomena by Bot (1983),

five times faster than in the field cultivation by supplying

feedback control by Udink ten Cate (1983), controller by

the twenty-four daily illumination hours with artificial

Tantau (1981), control algorithm and the relation between

lighting system,

those

problem and computer,

At present,

research is

controlling the C0 2 concentration in

several times of that in the natural environment and

introduced to the optimal control or adaptive control for

regulating temperature, pH and EC in the optimal state.

energy saving in the greenhouse.

This system is not only used to save !abor, it aims at making

Comparing with the greenhouse, perhaps plant factory is not

the plant productivity to the maximum by applying an

so familiar to our readers.

Therefore, we would like t o

optimal environmental control for the cultivation.

describe it in more detail.

When plant is limited for

system is the factory in which computer and all the sensors

producing vegetable only, it is sometimes called vegetable

are invested to reduce the personal expenses to get the

factory.

If we are asked to find the origin of the plant

This

maximum harvest in the short period. In other words, this system is the factory automation in agriculture.

factory, we should go back to thirty years ago when the

281

Control algorith.

Data acquisition

Manil1ulation for environ.ental control r-

(a) Outside cl iute data

(e) Hu.idity D/ A or/and Relay

(b) Ins ide data (c)

(d) Air te.perature

(0 Light intensity (g) CO. concentration

Plant response (physiological ecological) data

(h) Nutrient solution

(a) Air te.perature, Hu.idity, Light intensity, Wind, etc. (b) Air te.perature, Hu.idity, Light intensity, CO. concentration, Nutrient solution (Te.perature, EC, pH, Ion concentration), etc. (c) Transpiration flo~ Photosynthetic rate , Respiration rate, Leaf te.perature , Translocation, etc. Fig. I

Co.puter aided cultivation syste. for greenhouse and plant factory .

Now in the plant factory, not only vegetables are produced,

all the sub-systems by one micro computer into a time

but also the cultivation of mushroom and horse-radish are

sharing system. To control the environment more flexibly,

Although it is difficult to say that cultivating

it is necessary to change the set point of the environment

systems for various crops are not different from the process control or the system automation point of view, they may be

and the system parameters disturbed by the sudden changes in the outside. This belongs to adaptive control problem. To

much the same.

reduce the cost to the minimum or increase some element in

COMPUTER CONTROL FOR CULTIVA TING ENVIRONMENT

the crops to the maximum, the optimal stress is needed. This can be solved with the optimal con trol theory . For these

started.

situations, experience of the diligent farmer is important. AI system is responsible for the problem.

The computer aided cultivation system is shown in Fig. l CHashimoto, 1984). Computer calculates the data obtained from the change of the environmental factors and the

NEW AGRICULTURAL SYSTEM BASE!) ON

responses of the plants based on various algorithm, and

ENVIRONMENTAL CONTROL

determines the optimal operation for the environmental control. At present, in the general commercial system, the

It will be appreciated to prospect that agricultural system

data about the plant responses to the environmental changes

based on the en vironmen tal con trol should be approached

is not integrated into the control system. Desperate efforts

from three aspects, i. e., process optimization, labor saving

are made to control the environment in a constant with feedback control algorithm. Present situation shows that

and information. At first, to promote the process optimization including the

the en vironmen tal control is primitive and the computer is

hydroponic system and the shoot system, the identification

not used efficiently.

of the rela tion between the en vironmen tal change and the physiological ecology of plants can not be lacked. In

To improve computer utilization, in

Holland and other countries, computer is entrusted to make decision from cultivation to all the management.

another word, it is important to improve the environmental

Changing the environment and stimulating the plant by

control from the basic to advanced level.

various stresses with the reference of plant response or

sensors and instruments for measuring the plant responses play an important part for the identification. In the

controlling the environment based on biotronics are the

Certainly, the

works that the computer can best do. But at present, this is

hydroponic cultivation, there comes a limitation when only

only on researching level
pH

use is the problem to be solved in the future.

concentration in nutrient solution can not be controlled

Now, we would like to survey the computer control of

properly without the practical use of ion sensors.

and

EC

are

monitored

as

black-box.

The

ion

cultivating environment from the engineering point of view.

Next, let us discuss the problem of labor saving.

Micro computer is usually used. Environmental factors including the light, temperature, humidity and C02

controlled environmental cultivation system, human labor is necessary in seeding, transplan ting, harvesting and

concentration can be divided into several sub-systems when

spreading farm chemicals. Automation about those works are

In the

respectively. But several

being studied, and good results have already been obtained

minutes of sampling time will be sufficient enough for

in the application of robots to transplant in tissue culture

controlling the environmental factors, furthermore, only

and harvest fruits.

very short time is needed for processing sampled data in PID

intelligent robot and intelligent tele robot will substitute

control algorithm, therefore, it is not difficult to combine

the human labor in greenhouse and plant factory.

those factors

are con trolled

282

In the near future, robot including

r------ ............. --- .. ----- .. -........ _- ..... --_ . -- .... ---_ .. -- ...................... -_ ........ _.... ----. Cultivation Systea (Greenhouse or Plant Factory) Coaputer for Artificial Intelligence (AI)

Knowledge Base

Coaputer for Measureaent and Control

-

Environaental Factor Air teaperature, Huaidity Light intensi ty C02 concentration Nutrient solution (Teaperature, EC, pH, Ion concentration)

LAN 0- .. - - - - - - - - - _ .... _ - - - .. - .

:, Data base

,

.------------ .... ------.

,--.-- ...... _---_ ...... _--, : Identi fication :, and control ,

Cultivation Manageaent Disease ,l __ • _________________ Insect pest , .........

Question

l Fig.2

Tab I e 1

... _..

Answer

Expert

Question

I

I

, _. PI ant Response . -- ------; : Transpiration flow : Photosynthetic rate : Respiration rate : Leaf teaperature : Translocation , .. ---- .. - .. -- _. ----- .. -- ..... - ---_.

_----_ .... _------ .....

I

Answer

User

~--

I

Conceptional system of Computer Integrated Agricultural Production (ClAP).

Languages used in mai n menu.

Main Menu

micro-computer.

Mi cro COlIPuter AI Computer

UN

C, BASIC

ESP-

Identification and Control

C, BASIC

-

Expert Sys tea

C, BASIC

ESP'

Agricultural Strategies

C, BASIC

ESP'

Necessary menu is chosen through the

conversation between operator and computer. Four main menu are prepared; these are "LAW, "Identification and Control", "Expert System" and "Agricultural Strategies" as shown in the left part of Fig. 3. Each menu is used for the purpose described in the right part of Fig. 3. The languages used in the main menu are shown in Table 1. Menu for "LAW deals with computer communication with proper protocol. Menu for "Identification and Control" is always used for

• Extended Self-contained Prolog.

identification of the physical environment and on-line

As to the informationization of the environmental control

computing for feedback loop of the environment, and also used for data base of the culti va ting en vironmen t. This

system, it can be predicted that LAN (Local Area Network)

menu is mainly mathematical and physical.

will be built. Factory automation in industries has been arranged by the protocol using large computer system. In

hand, menu for "Expert System" is more biological. and use of AI computer is inevitable. Whole cultivating processes of

the solar plant factory or greenhouse. computer network is

some crops are supported by this menu, choosing the type of

On the other

necessary for realizing the optimal control (Hashimoto,

the cultivated crop. In the important stage through the

1985a). These system may become a LAN system like the factory automation. Furthermore, by the practical use of AI

whole cultivating term, the status of the crop is able to be discriminated based on the AI computer. Thus, the adequate

system. advanced environmental control with expert system

set-point ef the environmental control could be decided

and the plant diagnosis system will be popularized as the

based on the status of the crop. Finally, the menu for "Agricultural Strategies" is expected for CIM in agriculture,

development of information processing.

in other words, for high-level decision from the management point of view.

EXAMPLE OF COMPlITER INTEGRATED AGRICULTURAL PRODUCTION (ClAP)

EXPERT SYSTEM FOR DIAGNOSIS OF CROP DISEASE Fig.2 shows the recent system for ClAP. The system has the computer network composed of both usual micro-computer for environmental control of crops and the special computer for

We would like to present the expert system for diagnosis of disease. Several reports (Hoshi, 1988 etc.) are presented

the artificial intelligence.

about plant disease using micro-computer with BASIC or C.

The status of the crops is

identified based on the knowledge base accumulated from the

But there seems no paper about the system described here

experts, who have a lot of experiences through the cultivation, as well as the data base obtained from scientific

such as in the computer network containing AI computer with Prolog.

measurements. Then. effective control strategy is decided for

The expert system consists of human interface, WM (working

the successful cultivation. The structure of the software is unable to be easily understood from the system diagram,

memory). knowledge base and inference engine as shown in

though the concept of the system is not so complicated.

Into the WM through the human interface. The processes are

Therefore, more detailed diagram is shown in Fig.3.

Fig. 4.

Fig.3

The facts such as disease symptom are introduced

programmed as shown below. This is the question which ask

shows menu displayed on CRT as the output of the main

the stage of growth of plant.

283

Menu for LAN 1- I. CoIIIPuter cOllllllunication aaong lIIicro cOlllputers 1- 2.CoIIIPuter cOllllllunication between AI cOlllputer and lIIicro cOlllputer Menu for Identification and Control 2- 1. Environlllental condition Air telllperature , Hu.idi ty Light intensity C02 concentration Nutrient solution (TelllPerature, EC, pH, Ion concentration) ,

• ••

••

----------------------------------------

2-2.Plant response : Transpiration flow Photosynthetic rate Respiration rate Leaf temperature 2- 3.System identification 2-4. Control

Main Menu 1. LAN 2. Identification and Control 3. Expert System 4. Agricultural Strategies

Menu for Expert System 3-1.Choice of crops ;

-

Micro computer NEC PC98XF

Main CPU aeaory

Hard disk

803863.6MB

80MB

EPSON PC- 286VE 802864. 6MB

40MB

AI coaputer MITSUBISHI MELCOM PSI n (Personal Sequential Inference lIIachine) Micro program type CPU 53bits/tlord Main lIIelllory 40MB Hard disk 140MB

....... _------ ---- ----_ ........................ -_ ...... ..

: Tomato : Orange : Me Ion

I

3-2. Discrimination of crop status

-

: : : :

Normal Abnoraal Disease I nsect pest : . . . .. .. _--------_ .... _... __ .......... - .......... --- .. -3-3. Decision of set-points ........ _.................... -- ... -------------

: Constant desired value : Adapti ve : Optiaal

L .. ____________ .................. ___ .... ___ .... ___ ... ..

-

Menu for Agricultural Strategies 4-1 . Production cost 4-2. Adjustlllent of harvest time 4-3 . Market inforaation

Fig.3

Main lIIenu and sub-IIIenu of ClAP.

284

I

CONCLUSION ClAP is composed of four sub-systems. which are "LAW. "Identification and Control". "Expert System" and "Agricultural Strategies". These sub-systems cover the

Interface

process control of plant factory (greenhouse). plant factory automation and

Base

management

just like CIM in process

industries. For industrization of agricultural production. biological characteristics have been big barriers. which is quite different from non-biological production. But it might be

Fig.4

expected that utilization of computer network containing

Expert systell in AI cOIIputer.

the expert system is free from the barrier.

Even in the

environmental control system for cultivating crops. it seems evident that ClAP proposed in this paper should be the most % What stage of growth?

reasonable system.

class Ouestion_6 has : questionCClass) :Item = [("Ouestion_6:What stage of growth?",

REFERENCES

no_select, _, off), {"Harvest stage", pick_up, Harvest_stage, _, off),

Bot,

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end.

2039-2044. Pergamon Press. Oxford. Hashimoto. Y.• T. Morimoto and T. Fukuyama.<1985a). Some speaking plant approach to the synthesis of control

Rules of various diseases are stored in the knowledge base. The following is one of the programmed rules. That is a rule of gray mold of tomato, and the contents are that disease

system in the greenhouse.

symptom appears in young fruits and that the color of mold

219-226.

Acta

Horticulturae. 174:

Hashimoto. Y. and T. Morimoto. <1985b). Identification of water relation and C02 uptake in physiological

is gray. % Rule of gray mold

ecological processes in a controlled environment. Proc.

class rule_28 has : referenceCClass) :-

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: factCifwm, Disease_symptom, Young_fruits, _, _),

Oxford. Hashimoto. Y.. Y. Yi.. T. Morimoto. F. Nyunoya. H. Nishina

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and

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Y.

Nakane

(1987).

Pilot

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: referenceCClass) : - true:

factory.

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Proc.

10th IFAC World Congress.

Vo!.2:

338-343. Hoshi. T.. and T. Kozai. (1988). Disease and pest diagnosis

Inference of disease is carried out in the inference engine using rules such as shown above. The following indicates

for

that three rules are referenced in order to inference whether

Computer Technology-Knowledge Based Systems in

tomato.

2nd

International

DLG-Congress.

Agriculture-. Deutsche Landwirts hafts-Gesellschaft.

the disease is gray mold.

Frankfurt: 457-472. Tantau. H. -J. (1981).

% Reference rules of gray mold

The ITG digital greenhouse climate

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class Gray _maId has : inference
: reference(ifrule_29):

Press. Oxford. ten Ca te. A. J. (1983).

Modelling and (adaptive)

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: reference
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end. The result of inference is introduced into the WM. and is shown on CRT. This expert system works well and makes collect diagnosis.

285