Agriculture Letters · 2020. 12. 6. · Algae Based Edible Vaccine P. Rajarajan and S. Maheswari*...

Agriculture Letters A monthly peer reviewed newsletter for agriculture and allied sciences

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Volume 01, Issue 08

Publishing date: DEC, 2020

ISSN: 2582-6522

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Volume 01, Issue 08


ISSN: 2582-6522

IN THIS ISSUE

1. Integrated Nutrient Management Sahaja Deva* and M. Reddi Kumar

3

2. Geographic information system (GIS) and geostatistics for natural resource mapping Tapan Gorai*, Pankaj Kumar Yadav and Anil Kumar

5

3. Artificial Intelligence: The Future of Indi-an Agriculture Swarup Anand Dutta1,Mainu Hazarika1 and Praveen Kumar2*

10

4. Solar-Powered Automatic Irrigation Sys-tem: a Giant Leap towards Sustainable

Agriculture Parijat Bhattacharya1* and Purabi Banerjee

14

5. Uniformity Trials: Determining Optimum Size and Shape of Experimental Units

Pramit Pandit1 and K. N. Krishna-murthy2*

17

6. Algae Based Edible Vaccine P. Rajarajan and S. Maheswari*

20

7. Prospect and Challenges of Flower in India Suvarna L Mahalle, Pinaki Roy* and Shailja Thakur

23

8. Sustainable Agriculture: A Step Towards Self - Sufficiency

Sagarika Paul1, Shantonu Paul 2, Mainu Hazarika3 and Praveen Kumar4

27

9. Nitrogen Fertilization in Waterlogged Soil Arunima Chakraborty1* and Kinjal Mon-

dal2

30

10. Papaya Black Spot: An Emerging Disease of Papaya in Bihar AgroEcological Con-

dition Prince Kumar Gupta* and Sneha Shikha

33


Editor-in-Chief

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Volume 01, Issue 08


ISSN: 2582-6522

IN THIS ISSUE

11. Papaya Black Spot: An Emerging Disease of Papaya in Bihar AgroEcological Con-dition Prince Kumar Gupta* and Sneha Shikha

37

12. The locust plague: Fighting a crisis within a crisis M. Swetha Sree 1* and K. Tressa2

43

13. Export Performance of Coir Industry in India G. Parthasarathi1*, T. R. Sridevi Krish-naveni2 and S. Anandha Krishnaveni3

46

14. Applications of Fluorescence Microscopy in Plant Science

Joshitha Vijayan1, Soham Ray2, Ramawa-tar Nagar1, Nimmy MS1 and Vinod Ku-mar3

49

15. What Do You Mean by Epigenetic ?? Praveen Kumar*1, Mainu Hazarika2, and

Niranjan Chourasia3

54

16. Vaccination by seed treatment for healthy growth of pulse crops

Sangita Sahni* and Bishun Deo Prasad

57

17. ‘MANGO GINGER’ – The Lesser Known Spice Crop Bhoomika, H.R.

60

18. Mass Production Technology of fungal Bio-agent Trichoderma viride

Vindyashree, M.1*, Suresh Patil2 and Maheswari, S.3

63

19. Biotechnological Approach on Banana Breeding

Shuvadeep Halder*

66

December, 2020 Agriculture Letters (ISSN: 2582-6522)

https://agletters.in/ Volume 01, Issue 08 (December, 2020) 3

Introduction

Indiscriminate use of fertilizers leads to loss of soil fertility, productivity, decreased microbial

population, environmental and groundwater pollution. In the coming years growing of crops will be-

comes a difficult task even after applying fertilizers if the situation continues. Converting to organic

farming will not give expected yields which reduces the farmers’ income. So following the Integrated

Nutrient Management which includes reducing the amount of chemical fertilizers and replacing with

organic manures, green manures and bio-fertilizers will reduce the cost of cultivation but gives good

and quality yields and also increases soil fertility.

Usage of organic manures

Application of Farm yard manure, poultry manure, goat manure, sheep manure or vermicompost

at the time of last ploughing will reduce the usage of chemical fertilizers by 25-30%.

Incorporation of green manure crops

Growing of green manure crops like Sesbania, Daincha, Pillipesara fodder cowpea or green leaf

manure crops like Pongamia, Neem, Calotropis will reduce the usage of chemical fertilizers by 25-30%.

Growing of green manure crops and incorporating them at flowering stage will not only supply nutri-

ents to crop but also adds nutrients to soil and improves soil fertility.

Application of bio-fertilizers

Usage of bio-fertilizers also reduces 25-30% of chemical fertilizers. In leguminous crops, Rhi-

zobium is used as nitrogen fixing bio-fertilizer. In non-leguminous crops like rice, Azospirillum and

Azotobacter are used as nitrogen fixing bio-fertilizers. In all crops Phosphorus Solubilizing Bacteria is

used for converting unavailable form of phosphorus to available form. PSB solubilizes the phosphorus

available in the soil in toxic form and make it available to plants.

Method of application of bio-fertilizers

There are four methods of bio-fertilizer application. Bio-fertilizers are available in both powder

and liquid forms. Compared to powder form of bio-fertilizers, liquid bio-fertilizers are highly effective.

So usage of liquid bio-fertilizers is more beneficial.

Integrated Nutrient Management Sahaja Deva* and M. Reddi Kumar

Krishi Vigyan Kendra, Kalikiri

Article ID: 20/12/0108194



a) Seed application: Bio-fertilizers like Rhizobium can be applied to seed and used for sow-

ing. Take 100 ml of water and add 10 g of jaggery or sugar or starch and prepare a solu-

tion. Let it cool and spread on the seed. Add 10 ml of Rhizobium per kg of seed and mix

well and let it dry for 10 minutes. Seed can now be used for sowing.

b) Seedling dip method: Bio-fertilizers like Azospirillum and Azotobacter can be used for

this method in Paddy. At the time of transplantation take 70 lit of water in a drum and add

300-500 ml of bio-fertilizer. Before transplantation dip seedlings of rice in water mixed

with bio-fertilizer for 10 minutes and then transplant for one acre.

c) Broadcasting method: Bio-fertilizer like PSB can be applied by this method. Mix 300-

500 ml of bio-fertilizer in any organic manure and broadcast in the field within 7 to 10

days after sowing or transplantation for one acre.

d) Drip irrigation: Mix 300-500 ml of bio-fertilizer in drip tank for one acre of field and

supply water to the field.

Micronutrients

Micronutrients like zinc, iron, manganese, boron etc. are essential for plant growth along

with macronutrients. Deficiency of micronutrients will cause growth retardation and yield loss

even after supplying macronutrients.



Introduction

Geographic information system (GIS) has been evolved as an inter-disciplinary branch compris-

ing geography, remote sensing, surveying and photogrammetry, cartography, mathematics, statistics

and computer science technology. GIS consists of spatial and non-spatial data in a database system with

specific set of operation for managing real world problems. There are three basic types of GIS applica-

tions like inventory, analysis and management application. The GIS applications are principally used

for mapping, measurement, monitoring, modelling and management of resources. Observing the bound-

less opportunities, Jack Dangermond, Founder and CEO, Environmental Systems Research Institute

(ESRI) famously said: ‘The application of GIS is limited only by the imagination of those who use it.’

There are tremendous use of GIS application in military, government and public service, business and

service planning, banking and financial services, real estate, logistics and transportation, market analy-

sis, education and utilities etc. Besides the above application, it is also widely used for natural resource

mapping and management. Geo-statistics branch and its principles was developed and applied first in

geosciences studies (Matheron, 1963) and subsequently applied in natural resource mapping for more

than 50 years (Burgess and Webster, 1980; Webster and Oliver, 2001; Gassner and Schnug, 2006;

Chilès and Desassis, 2018). Observing the potentiality and scope of GIS and geostatistics, its basic as-

pects have been briefly described in the present context.

Geographical information system (GIS)

Geographical information system (GIS) is defined on the basis of tool, database and organization

utility, quoted from Burrough and McDonnel (1998). It is ‘a powerful set of tools for collecting, stor-

ing, retrieving at will, transforming and displaying spatial data from the real world’. It is also consid-

ered as a database system in which both spatial and non-spatial data are indexed with a spatial entity,

and whereupon a set program operated to answer queries about spatial entities in the database. It is ‘a

decision support system involving the integration of spatially referenced data in a problem solving envi-

ronment’; ‘an institutional entity, reflecting an organisational structure that integrates technology with a

database, expertise and continuing financial support over time’.

GIS have three important components – (a) computer hardware and accessory, (b) GIS software

with five functional aspects like data input and verification; data storage and database management; da-

Geographic information system (GIS) and geostatistics for natural re-

source mapping Tapan Gorai*, Pankaj Kumar Yadav and Anil Kumar

Bhola Paswan Shastri Agricultural College, Purnea, BAU, Sabour, Bhagalpur Article ID: 20/12/0108195



ta output and presentation; data transformation; and interaction with user and (c) a proper or-

ganizational context including skilled people.

Geographical information system has potential role in mapping of vegetation, land and

water resources; land asset database and governmental services; digital soil mapping; monitor-

ing and management of agriculture and forest; irrigation system and network; land evaluation

and rural planning; monitoring, modelling and management for land degradation; landslides;

drought assessment; flood management; environmental monitoring and assessment such as air

and water quality, pollution control etc; weather and climate modelling and prediction. Recent-

ly, development of geospatial data infrastructure, geospatial solution for governance like animal

husbandry, species watch and species loss; geospatial solution for forest fire monitoring; air

quality monitoring & forecast system; decision support system etc. are being developed rapidly

with the progress of GIS software including 3D-GIS, mobile GIS, Web GIS, server GIS.

Geo-statistics

Geo-statistics is a branch of statistics used to analyse regionalized variable on earth sur-

face associated with spatial or spatiotemporal phenomena. It likewise honours the instinctive

sense that the value of attribute that are nearer together are more related (more similar) than at-

tribute values further separated. Kriging is one geostatistical technique with two basic tasks: (1)

estimation of semivariogram and covariance function of regionalized variable for analysing spa-

tial dependency (called spatial autocorrelation) and (2) prediction of unknown values using gen-

eralized linear regression techniques (kriging) along with assessment of prediction uncertainty.

Theory of regionalized variable

The spatial variation of any continuous property is frequently too unpredictable to ever be

demonstrated by basic, smooth numerical function, can be better depicted by stochastic surface.

This property is known as regionalized variable. There are several examples of regionalized var-

iable like elevation above sea level, ground water level, natural mineral deposit, soil properties,

variation of atmospheric pressure etc. As per the assumption of Regionalized variable theory

(RVT), the spatial variation of any variable Z(x) is sum total of three major components

(Burrough and McDonnell, 1998). These are (a) a deterministic variation or structural compo-

nent, having constant mean or trend or drift i.e. m(x); (b) a random, but spatially correlated

component, known as the variation of regionalized variable i.e. ɛʹ(x), and (c) a spatially uncorre-

lated random error or residual error term (ɛʺ). The variation of the regionalized variable, denoted

by ɛʹ(x), is the stochastic, locally varying but spatially residuals from m(x). This variation is rep-

resented by semi variance under assumption of intrinsic stationary field. In the combined

presence of the two assumptions such as (i) when E[Z(x)] = m(x) is constant and (ii) semivari-



ance is dependent on the separation vector i.e. lag (h), but not on the spatial location (x),

the spatial random field (SRF) is characterized as intrinsically stationary (Cressie, 1993). Then

the regional variable is considered as spatially dependent variable.

Semivariogram analysis

The empirical semivariance or classical semivariance (Matheron, 1963) was computed

as half the average squared difference between the measured values of data pairs.

Where N(h) is the number of data pairs separated by spatial vector (h) i.e. lag distance, z(xi)

and z(xi+h) are the attribute values at two locations xi and xi+h respectively, which are separat-

ed by spatial vector i.e. lag (h). A plot of semivariance against lag distance (h) is known

as the experimental semivariogram. The variogram provide useful information for determining

spatial pattern, optimizing sampling distance and interpolation. The semivariance values for cor-

responding lag distances (h) were computed and plotted as semivariogram using geo-statistical

software. Best fitted semivariogram are generally selected using weighed least square technique

from several existing semivariogram models such as spherical, exponential, circular, Gaussian

model etc The computed semivariogram values for corresponding lag (h) were fitted with

available theoretical. Weight for each lag was directly proportional to the number of sample

pairs and inversely proportional to the standard deviation of experimental semivariogram val-

ues. Expressions for Spherical semivariogram models as for example are given below.

In the semivariogram models, nugget variance, structural variance, sill and range were ex-

pressed by C0, C1, (C0 + C1) and a respectively. Nugget variance indicates error arising from

measurement, sampling and other undefined sources. Sill value is that value of semivariance

when it becomes equal to the variance of sampled population (if it has no trend). Range is the

distance beyond which the attribute values of sample pairs are not spatially correlated to each

other.

Kriging

Kriging is an optimal method of spatial stochastic interpolation of regionalized variables

and also known as best linear unbiased estimator (BLUE). Kriging is also a moderately quick



and exact interpolator creating smooth prediction surface map of the attribute. It is an exact in-

terpolator because kriging equation interpolates values at unknown location, which generally

coincide with the measured values at those points. Along with the interpolated map, kriging er-

ror (standard deviation) map gives valuable information about the reliability of interpolated val-

ues over the area of interest. The kriging methodology has been described in reference of Bur-

rough and McDonnel (1998).

Spatial estimation of an attribute value (z) {\displaystyle Z\colon \mathbb {R} ^{n}

\rightarrow \mathbb {R} }at an unobserved location (x0{\displaystyle x_{0}} ) is computed

from a linear combination of the measured values z(xi) {\displaystyle z_{i}=Z(x_{i})}and

weights λi{\displaystyle w_{i}(x_{0}),\;i=1,\ldots ,N}. The true value z(x0) is estimated by:

with , where is the estimated value at the unknown location (x0), z(xi) is the

measured value at the sampling site xi and n is the number of sites within the local neighbour-

hood window. The �i weights are selected with objectives of minimizing the estimation or error

variance i.e. the prediction error or kriging variance under the

principle of unbiasedness estimator. These weights are obtained by solving a system of linear

equations which is known as ‘kriging system’ (Goovaerts, 1999).

The common methods of kriging are simple kriging and ordinary kriging. Simple kriging

is prediction by generalized linear regression under the hypothesis of second order stationarity

with a known mean. Ordinary kriging is weighted linear regression of observed values, after

considering local fluctuations of the mean by limiting the domain of stationarity of the mean to

the local neighborhood but the mean is unknown (Goovaerts, 1999).

Geostatistical techniques such as kriging has great flexibility for interpolation, providing

ways to interpolate any attribute to area or volume larger than original sample area or volume

(block kriging), methods of interpolating binary data with objective that the value of the attrib-

ute in question exceeds a certain threshold (indicator kriging), methods for incorporating soft

information about trends when mean changes systematically with distance (universal kriging) or

stratification (stratified kriging), methods of interpolating an expensive-to-measure variable

from a cheap-to-measure co-variable (co-kriging). Multivariate kriging is the application of geo-

statistics to multivariate transformation, such as result of regression model, principal component

transformation, reciprocal averaging, or fuzzy-k-means.



Conclusions

Geographic information system has unlimited capability to manage geospatial problems

through tool and database based functionality and decision support system with increasing ac-

ceptability of government and public. Geostatistics is a complex set of statistical formula with

assumption and is effectively used for stochastic modeling of regionalized variables. Geostatis-

tical tool like semivariogram can define the spatial nature of regionalized variables and kriging

interpolation generate spatial distribution map of the variable alongwith kriging error map.

Kriging techniques have wide flexibility for spatial interpolation of regionalized random varia-

bles with inclusion of secondary information.

References

Burgess, T. M. and Webster, R. (1980). Optimal interpolation and isarithmic mapping of soil

properties. I: The semivariogram and punctual kriging. Journal of Soil Science, 31, 315-

331.

Burrough, P. A. and McDonnell, R. A. (1998). Principles of geographical information systems.

Oxford University Press, India.

Chilès, J. and Desassis, N. (2018). Fifty Years of Kriging. In Daya Sagar, B. S., Cheng, Q and

Agterberg, F (Eds.), Handbook of Mathematical Geosciences - Fifty Years of IAMG (pp.

589-612). Springer International Publishing AG part of Springer Nature, Switzerland.

Cressie, N. A. C. (1993). Statistics for Spatial Data. John Wiley and Sons, New York.

Gassner, A. and Schnug, E. (2006). Geostatistics for soil science. In Lal, R (Editor), Encyclope-

dia of Soil Science (Second Edition), Vol. 1, pp 760-764. Taylor and Francis/CRC Press,

Boca Raton.

Goovaerts, P. (1999). Geostatistics in soil science: state-of-the-art and perspectives. Geoderma,

89, 1-45

Matheron, G. 1963. Principles of geostatistics. Economic Geology, 58(8),1246-1266

Webster, R. and Oliver, M.A. (2001). Geostatistics for Environmental Scientists. Wiley & Sons

Ltd., Chichester.



Introduction

India is an agricultural country with nearly 66% of its rural population whose primary source of

livelihood is agriculture. Agriculture contributes nearly 18% to the Indian GDP. We all know that agri-

culture is the backbone of the Indian economy but with the rising population and increasing demand for

food production, a huge question mark arises on the present technology of farming. It is predicted that

by 2050, India will surpass China in terms of population with an estimated 1.67 billion people. With

this huge population and increasing demand for food production, ‘automation in agriculture’ will be the

only way as traditional agriculture is not sufficient enough to fulfill these requirements. Automation in

agriculture is currently the main concern and emerging subject across the world. The use of Artificial

Intelligence (AI) in Agriculture will not only increase food production but also revolutionize the Indian

agricultural system by using methods and technologies that are based on artificial human intelligence.

Artificial intelligence (AI) refers to complex software that performs tasks in a very similar way

as to a human brain by sensing and responding to a feature of their environment. AI is based on vast

subjects like Biology, Computer Science, Mathematics, linguistics, Engineering, and Psychology. This

technology is made by studying how the human brain thinks, learns, works, and make decisions while

solving a certain problem, and based on this, intelligent software and systems are developed. This soft-

ware is fed with training data and further these intelligent devices provide us with the desired output for

every valid input, just like the human brain.

AI can be regarded as an emerging sun in the field of agriculture. AI-based machines and equip-

ment have taken agriculture to another level. Yanh et al., 2007 studied that artificial intelligence has

increased grain production in the cereal, pulses, oilseed, and enhanced real-time monitoring, harvesting,

processing, and marketing. The latest technologies based on agricultural drones and robots have revolu-

tionized the agricultural system and are making a tremendous contribution to the agricultural sector.

Many hi-tech computer-based systems have been developed to study the various important parameters

for grain yield and its associated traits. The technology is also useful to determine the area covered by

weed as well as some other parameters to characterize crop quality such as oil content, protein content

(Liakos et al., 2018).

AI in Agriculture

Artificial Intelligence: The Future of Indian Agriculture Swarup Anand Dutta1,Mainu Hazarika1 and Praveen Kumar2*

1 Dept. of Horticulture, Assam Agricultural University, Jorhat-13 2 Dept. Genetics and Plant Breeding, Lovely Professional University, Phagwara, Punjab

Article ID: 20/12/0108196



Artificial intelligence can be used in agriculture in various ways and forms. Various

technologies in the form of software, applications, robots etc. are available which not only make

human tasks easier but also make agricultural activities precise, easy, and handy. Moreover, the

present-day challenges of climate change, food insecurity, high population, food wastage, locust

swarms, drought, and flood emerges as a threat to agriculture, and as such, technological inno-

vations like artificial intelligence helps us tackle and modify the agricultural activities according

to our convenience. AI seeks innovative approaches by protecting and improving crop yield. A

few very popular application of AI in the field of agriculture are discussed below.

1) Soil health monitoring: To get the best yield, the soil should have optimum nutrition,

adequate moisture along with favorable weather conditions. Remote sensing, image recognition,

and deep learning models are used for this purpose of soil health monitoring. AI models are

created by collecting historical data about monsoons, information about crop output, history of

soil health, farm snapshots, etc. These models are then used for soil health monitoring. Applica-

tions and software are developed which directly indicates farmer about the soil health, the cor-

rective measures to be taken, watering schedule, planning activities and even the date of fertiliz-

er application.

Proximity sensors are also used for soil health monitoring. These sensors are kept in contact

with soil or kept in a very close range which helps in soil characterization based on soil below

the surface.

2) Image-based alert generation: Agricultural drones with high tech cameras such infra-

red-based camera, lased based 3 D scanner are used to study 3D morphology of plant that will

help for crop monitoring, field analysis, scanning of fields, and also used to study the seed color

eg. virtuousness of maize kernels. etc. All the visual imaging technology-based systems are used

to investigate the morphology of fruits for color, size, and shape, etc. These drone images are

then combined with computer intelligence or computer vision technology so that farmers can

take rapid actions. Real-time weather alerts can also be generated by this technology.

3) Pest and weed management: Behavior of pest can be predicted with the help of AI for

advanced planning of pest control. Image classification tool remotely sensed data, weather data

are combined and used for weed control. AI automated robots can distinguish the weeds from

the cultivated plants and hence perform area-specific weed management. This confines the use

of weedicide to areas that require treatment. An AI-supported weed control technology devel-

oped by a US Company named ‘See and Spray’ reduces expenditure on weedicide by almost

90%.

4) Detecting crop diseases: Computer vision technology under white UV/A light captures



various images of crops which are then scanned and studied by computers to detect the crop dis-

eases and alert the farmers. Drones are also used for field scanning and agricultural robots are

used for area-specific spraying of chemicals.

5) Improving Crop Productivity: Predictive analysis with the help of AI is used for im-

proving crop productivity. This technology predicts the appropriate crops that can be grown in a

favorable environment along with the method of sowing to enhance crop productivity. It also

reduces costs and minimizes labor requirements.

A sowing app developed by International Crop Research Institute for the Semiarid Tropics and

Microsoft, powered by AI has been tested in Andhra Pradesh and very good results have been

obtained. Per hectare yield has increased by almost 30% average by using this sowing app..

6) Water management: Proper water management in agriculture is the key for high pro-

duction as well as for curbing the problem of water scarcity. Thermal imaging cameras are used

for crop monitoring to see whether the crops are getting adequate water or not. Mobile Near In-

fra-Red and visual spectrophotometers can allow for the detection of soil moisture in the field or

small plot. The information is then further processed and farmers are alerted about the irrigation

schedule and moisture status of the field. Smart irrigation technology is installed in a farmer’s

field for automation of irrigation according to the need of the crops.

7) Price realization: In India, the farmers do not get the adequate price for their produce

and it is estimated that only 6% of farmers get the MSP (Minimum Support Price). AI-powered

predictive modeling is used to make the Price Discovery Model which can present the demand-

supply information to the farmers. This can help farmers get accurate prices for their produce.

8) Harvesting and post-harvest management: AI-powered agricultural robots are used nowa-

days for the management of harvesting as well as post-harvest operations. The fruits are scanned

using Led lights and only ripe fruits are picked. Similarly sorting and grading operations are al-

so performed by intelligent robots. This reduces labor involvement as well as the cost of produc-

tion.

Drawbacks

Although AI has many advantages as discussed earlier, it also imparts a concern on the

labor force. India being a labor surplus country, it is difficult to implement AI-based agricultural

robots as AI technology reduces the use of manual laborers. It is predicted that there will be mil-

lions of unemployed field laborers shortly because of the impact of AI.

Understanding AI technology is not easy. Especially as the majority of the farmers are

not technically educated, it will be very difficult for them to use it, unless proper training is pro-

vided.



Moreover, AI technology is costly. Drones and robots are very costly machines and un-

less the government bodies funds, it will be very difficult for the farmers to use them.

Conclusion

The Agriculture industry is a dynamic industry which faces multiple challenges of

weather conditions, pest, and diseases, weeds, irrigation systems, nutrition, etc. All these aspects

are inter-related which directly influences the yield. Traditional agricultural practices surely can-

not fight these challenges and meet the demand of the increasing population and therefore

‘automation in agriculture’ will be the only way. AI-powered technology can surely assist farm-

ers and increase their income by increasing crop productivity. Nowadays, there are many

startup’s coming up in India which deal with AI-based technologies and many trials and re-

search are going on in various parts of the country. It is expected that shortly, artificial intelli-

gence-based technologies will revolutionize the entire agricultural system and attract the youth

generation into farming. Thus, we can predict that artificial intelligence can surely be the future

of Indian Agriculture.

Reference

https://www.sciencedirect.com/science/article/pii/S258972172030012X#bb0060.

https://emerj.com/ai-sector-overviews/ai-agriculture-present-applications-impact/.

https://medium.com/vsinghbisen/how-ai-can-help-in-agriculture-five-applications-and-use-cases

-f09c3dc326c9.

https://www.online-sciences.com/robotics/artificial-intelligence-in-agriculture-advantages-

disadvantages-uses/.

https://www.ciiblog.in/technology/artificial-intelligence-in-indian-agriculture/.

https://thecsrjournal.in/artificial-intelligence-in-agriculture-in-india/.

Liakos,K., Busato,P. Moshou, D. Pearson,S. andBochtis, D.Machine Learning in Agriculture: A

ReviewSensors, 18 (8) (2018), p. 2674, 10.3390/s18082674.

Yang, H.,Liusheng,W. and HongliJunminX.Wireless Sensor Networks for Intensive Irrigated

Agriculture, Consumer Communications and Networking Conference, 2007. CCNC

2007. 4th IEEE (Jan. 2007), pp. 197-201. Las Vegas, Nevada.



Introduction

Rapid population growth and subsequent demand surge for food grain production propel inno-

vative agricultural development in the post green revolution period. In an agriculture-based country like

India characterized by erratic and sporadic rainfall patterns, irrigation tolls for up to 70% of the total

water usage of the country. Generally, diesel operated pumps are used to draw water from the reservoirs

which incur a substantially higher degree of energy involvement. Conventional irrigation methodolo-

gies are severely jeopardized with huge loss of water through evaporation, seepage, and surface runoff.

Inefficient use of energy and water resources results in a manifold increase in the cost of cultivation.

Under these circumstances, one of the attractive, viable, and renewable but under-utilized sources of

energy is solar energy which is at a time abundant, environment friendly, and sustainable (Chandel et

al., 2015). To tune up these two factors i.e. irrigation and energy crisis, implementation of solar energy

into irrigation systems may prove a fantastic way out to meet the small-scale water requirements cost-

effectively.

Mechanism

Solar Powered Automatic Irrigation System (SPAIS) utilizes solar energy with the help of solar

panels (Gupta et al., 2016). Depending upon the intensity of sunlight, it pumps water automatically

from underground water reservoirs to a ground-level storage tank. Interestingly, here only a simple

valve mechanism regulates the flow of water into the field according to the practical requirement of wa-

ter in crop field indicated by a soil moisture sensor attached, implying a single stage consumption of

energy. Thus, a substantial amount of both water and energy is saved.

Fig. 1: Outline of SPAIS operational mechanism

Solar-Powered Automatic Irrigation System: a Giant Leap towards Sus-

tainable Agriculture Parijat Bhattacharya1* and Purabi Banerjee2 1 Department of Agricultural Chemistry and Soil Science, BCKV, Mohanpur 2 Department of Agronomy, BCKV, Mohanpur

Article ID: 20/12/0108198



As a whole, the irrigation system consists of two modules including Solar Pumping

Module (SPM) and Automatic Irrigation Module (AIM) (Figure 1). In the case of SPM, a solar

panel is placed near the pump set. A control circuit is employed to charge its battery, from

which a converter circuit gives power to the pump submerged inside the well. Now the water is

withdrawn into a ground-level tank for temporary storage before releasing into the field. The

second module i.e. AIM involves the water outlet valve in the tank, electronically controlled by

a circuit placed in the crop field sensing soil moisture. The function of this sensor is to convert

the moisture present in soil into equivalent voltage. This in turn confers to a sensing circuit hav-

ing a reference voltage adjusted by the farmer for setting up different moisture levels manually

for different crops. The difference between these two voltages is equivalent to the amount of

water needed for that particular soil and also to the rotational angle of a stepper motor which

controls the cross-sectional area of the valve used. When a control signal is sent to this stepper

motor, the valve opens to control the flow of water. Therefore the flow of water is proportional

to the moisture difference (Harishankar et al., 2014).

Benefits of solar-powered automatic irrigation system

1. Solar powered system efficiently uses potentially inexhaustible energy of the sun and

economizes energy requirement which ultimately curbs down the humongous cost of irri-

gation (Abayomi-Alli et al., 2018).

2. This system optimizes the water usage through curtailment of its wastage with minimum

human interventions.

3. It also avoids the emission of greenhouse gases as well as noise and air pollutions that are

otherwise faced in case of diesel, electric, gas, or coal-operated pumps (Kelley et al.,

2010).

4. Replacing the labour intensive irrigation allows the rural workforce to devote to other in-

come-generating activities.

5. Multiple usages of saved energy (i.e. electrification of the village) and water (domestic

use) lead to diversification of farm-based income.

Shortfalls of the system

1. Initial installation of the system involves high-cost involvement which is hard to afford by

small and marginal farmers of developing countries.

2. Optimization of design as well as timely maintenance of the system is not always in

place.

3. Farmers require a substantial degree of skill and technical knowledge through proper

training for the smooth functioning of SPAIS.



Conclusion

Undoubtedly, we are living in an era of water and energy crisis. Maximization of water produc-

tivity through optimizing water use in agriculture coupled with the economization of conventional non-

renewable sources of energy should be the prime focus of research. Innovative methods of irrigation

such as solar-powered automated irrigation systems can be a path-breaking solution. Just like every oth-

er new technology, it is also constricted with the previously discussed limitations that must be ad-

dressed with a scientific and technical point of view. This system will certainly usher new horizons in

the domain of irrigation in the near future.

References

Abayomi-Alli O., Odusami M., Ojinaka D., Shobayo O., Misra S., Damasevicius R. and Maskeliunas

R. (2018). Smart-Solar Irrigation System (SMIS) for Sustainable Agriculture. In: Florez H., Diaz

C., Chavarriaga J. (eds.) Applied Informatics. ICAI 2018. Communications in Computer and In-

formation Science, vol 942. Springer, Cham. doi: 10.1007/978-3-030-01535-0_15.

Chandel S.S., Naik M.N. and Chandel R. (2015). Review of solar photovoltaic water pumping system

technology for irrigation and community drinking water supplies. Renewable and Sustainable

Energy Reviews, 49: 1084–1099. doi: 10.1016/j.rser.2015.04.083.

Gupta, A., Krishna, V., Gupta, S., Aggarwal, J. (2016). Android-based solar powered automatic irriga-

tion system. Indian J. Sci. Technol., IX(47): 0974–6846.

Harishankar S., Sathish Kumar R., Sudharsan K.P, Vignesh U. and Viveknath T. (2014). Solar Powered

Smart Irrigation System. Advance in Electronic and Electric Engineering, 4(4): 341-346.

Kelley L.C., Gilbertson E., Sheikh A., Eppinger S.D. and Dubowsky S.(2010). On the feasibility of so-

lar-powered irrigation. Renewable and Sustainable Energy Reviews, 14: 2669–2682.

doi:10.1016/j.rser.2010.07.061.



In agricultural experiments, researchers aim at ascertaining the relative worth of a set of treat-

ments with reasonable confidence. To achieve this, particularly under field conditions, the experimenter

should have a clear idea about the about the area, where the experiment has to be conducted. A trial,

commonly known as uniformity trial, is usually conducted to have an idea about the conditions of the

proposed experimental area.

Uniformity trial involves growing a particular crop (usually of short duration) with uniform

package of practices (cultivation technique) by dividing the whole area into the smaller units. Some-

times the division of plot into the smaller units is also done before recording the response. At the time

of harvest, the produce from each such units are recorded separately. The smaller the basic units are, the

more detailed the measurement of soil heterogeneity become. In the past, different researchers have

tried various methods to study the soil fertility variation (Shukla et al., 2013; Schwertner et al., 2015;

Lohmor et al., 2017). Few of these methods are described below.

1. Fertility contour map

The most popular approach adopted by the researchers to describe the heterogeneity of land is

the construction of fertility contour map. This map is constructed by taking the moving averages of

yields of the unit plots. The regions of same fertility are demarcated further by considering those areas,

which have yield of same magnitude.

Fig. 1: Fertility contour map based on moving averages from uniformity trial conducted at CCS

HAU, Hisar (Nigam et al., 2004)

Uniformity Trials: Determining Optimum Size and Shape of Experi-

mental Units Pramit Pandit1 and K. N. Krishnamurthy2* 1 Department of Agricultural Statistics, Bidhan Chandra Krishi Viswavidyalaya, Mohanpur, West Bengal, India-741252 2 Department of Agricultural Statistics, Applied Mathematics and Computer Science, University of Agricultural Sciences, Bengaluru, Karnataka, India-560065 Article ID: 20/12/0108200



2. Maximum curvature method

Unit-wise basic information from uniformity trial experiment is used in maximum cur-

vature method. In this method, basic units of uniformity trials are combined to form new units.

These new units are formed by combining columns, rows or both. Combination of columns and

rows should be done in such a way that no columns or rows are left out. For each set of units,

the coefficient of variation (CV) is computed. A curve is then drawn by plotting the sizes of the

experimental units on the X-axis and corresponding coefficient of variation values on the Y-

axis. At the point of maximum curvature, one can get the optimum plot size. With the help of

the mini-max theory of the calculus, the optimum plot size for which the curvature is maximum

can be worked out (Celanti et al., 2016; Chen, 2019).

Fig.2 Maximum curvature method

3. Fairfield Smith’s variance law

H. Fairfield Smith (1938) proposed a law to describe the relation between plot size and

variance of mean per plot. The model is represented by the equation

where x is number of basic units in a plot, is the variance of mean per plot of x units, is

the variance of mean per plot of one unit, and b is the characteristics of soil and the measure of

correlation among contiguous units. Now, if b = 1, and the units making up the plots

of x units are not correlated at all. On the other hand, if b = 0, the x units are perfectly correlated



and , implying there is no gain due to the larger size of plot. Generally, b will range

between 0 and 1 so that an increase in plot size increases the precision of the experiment provid-

ed the number of plot remains the same. The values of and b are determined by the principle

of least squares.

References

Celanti, H. F., Schmildt, E. R., Schmildt, O., Alexandre, R. S., & Cattaneo, L. F. (2016). Opti-

mal plot size in the evaluation of papaya scions: proposal and comparison of meth-

ods. Revista Ceres, 63(4), 469-476.

Chen, H. (2019). The Existence of Solution of a Critical Fractional Equation. Journal of Applied

Mathematics and Physics, 7(1), 243-253.

Lohmor, N., Khan, M., Kapoor, K., & Bishnoi, S. (2017). Estimation of optimum plot size and

shape from a uniformity trial for field experiment with sunflower (Helianthus annuus)

crop in soil of Hisar. International Journal of Plant & Soil Science, 15(5), 1-5.

Nigam, A. K., Parsad, R., & Gupta, V. K. (2004). Design and analysis of on-station and on-farm

agricultural research experiments: a revisit. IASRI.

Schwertner, D. V., Lúcio, A. D., & Cargnelutti Filho, A. (2015). Size of uniformity trials for

estimating the optimum plot size for vegetables. Horticultura Brasileira, 33(3), 388-393.

Shukla, A. K., Yadav, S. K., & Misra, G. C. (2013). A linear model for uniformity trial experi-

ments. Statistics in Transition new series, 1(14), 161-170.

Smith, H. F. (1938). An empirical law describing heterogeneity in the yields of agricultural

crops. Journal of Agricultural Science, 28: 1–23.



Introduction

The edible vaccines encompass the selected desired genes from the plant, and then the altered

proteins are produced which have immunogenic property. The innate immunogenic properties are main-

tained by the genes encoding antigens of bacterial or viral pathogens and can be expressed in the plant.

Edible vaccine has more solicitation in the prevention of autoimmune disease and cancer therapy rather

than to prevent infectious diseases. Arntzen in 1990 developed the concept of edible vaccine and he in-

troduces the gene of interest by the transformation mechanism. The desired gene are expressed in the

plant tissue and are known as transgenic plants. The encoded genes in the plant tissue are punitively

protective against disease caused the viral, bacterial and parasitic diseases in humans and animals. Edi-

ble vaccine consists of antigenic proteins which are devoid of pathogenic genes, so that it is similar like

traditional subunit vaccines. Nowadays so many edible vaccines are produced for certain human and

animal diseases such as Hepatitis B, C and E, foot and mouth diseases, cholera and measles. The edible

vaccine can be enabled as multiple deliverer of antigen along with other vaccination programmes, so

that it is able to prevent diseases like hookworm, rabies and dengue etc.

Algae in Recombinant Protein Production

Green microalgae are having bounded proteins with complex disulphide bonds and also proved

that the algae will be useful for the protein production. The algae contain folding and unique enclosed

compartment so that, it can accumulate high levels of transgene products in the chloroplast. Like yeast,

the chloroplasts of algae encompass the same cellular folding machinery for the transgene products.

The green algae such as Chlamydomonas reinhardtii produce fibronectin and growth factor which acts

as therapeutically relevant proteins, signalling molecules and antibodies in human and animal.

The transgene expression shows increased levels highly variable in the expression of gene, pro-

teins, regulatory elements which is characterized by the ideal gene and improvement in codon optimiza-

tion.

Edible algal vaccines

Algae are water born plant with single cell which are exactly similar to edible plant vaccine. If

consider as edible algae for human beings only few strains of algae can deliver antigen by genetic engi-

Algae Based Edible Vaccine P. Rajarajan and S. Maheswari*

Department of Microbiology, Centre for Research & PG Studies, Indian Academy of Degree College - Autonomous, Karna-taka, Bengaluru – 560043, India

Article ID: 20/12/0108201



neering for various diseases. In edible algal vaccine, genetic modification is much easier due to

higher expression levels of foreign genes. Algal vaccines are inexpensive when compared with

the plant products. Many algal species are considered as potential food source for human beings.

Microalgae are resistant to many animal pathogens, so it is used for the vaccine production.

Table-1: Edible algal vaccine for various diseases

Microalgae can grow very fast and no limited habitat so that the entire structures of algae

used for the production of edible vaccine. The green alga Chlamydomonas reinhardtii has

been used as models for therapeutic processes in humans and animals since it can produce large

amounts of proteins and no cross-contamination with other field crops. Algae are accelerating

fast growth by cultivating in bioreactors. The structural content of the algae are unaltered after

lyophilisation so that the vaccine production is also very effective. In Chlamydomonas reinhard-

tii the desired antigen existing in the stability of algal lines of the chloroplast. The algal recom-

binant proteins can express both the viral structural protein VP1 and β-subunit of cholera toxin

(CTB). The desired proteins when injected in swine will provoke the immune system. The in

vivo efficiency of algal immunity by the surface protein E2 of swine fever (CSFV) expressed in

the chloroplast genome. Other algal antigens such as glutamic acid decarboxylase, E7 proteins,

different fragment of proteins, surface antigen are expressed against autoimmune agent of diabe-

tes, HPV, malaria, white spot syndrome respectively.

Advantages of Algal Edible Vaccines

1. Due to the fast multiplication of algae, they can be used to produce dehydrated or lyophi-

lized vaccine.

S.

No

Host algae Diseases Reference

1 Chlamdomonas reinhardtii Malaria Correia-da-Silva et al.

(2017)

2 Chlamydomonas reinhardtii Classical swine flu Smal et al. (2012)

3 Dunaliella salina Hepatitis B Mclaughlin-Drubin and

Munger (2010)

4 Chlamydomonas reinhardtii Foot and mouth dis-

ease

Alonso et al (2002)

5 Chlamydomonas reinhardtii Human papilloma vi-

rus

Medina and Guzma (2001)

6 Chlamydomonas reinhardtii White spot syndrome Hormaeche et al. (1990)

7 Chlamydomonas reinhardtii Hypertension

(angiotensin II)

Yap et al. (1978)



1. The expressed dry algae antigens shall be protected from acidic and protease rich gastric envi-

ronment. So that the bioactive molecules are enabled in the immune system that can stimulate

humoral and cellular responses.

2. In order to generate adequate algal vaccine, the cell nucleus machinery of the algae allows sub-

sequent modifications of glycosylation and new protein.

Limitations of Algal Edible Vaccines

Due to its larger size in the microalgae the chloroplast not only allows greater accumulation of

the antigen necessary for a vaccine, but also facilitates a more stable integration of the transgene by

avoiding the random integration problems.

References

Alonso LG, Garcia-Alai MM, Nadra AD, Lapeaa AN, Almeida FL, Gualfetti P. (2002). High-risk

(HPV16) human papillomavirus E7 oncoprotein is highly stable and extended, with conforma-

tional transitions that could explain its multiple cellular binding partners Biochemistry, 41:

10510–10518.

Correia-da-Silva M, Sousa E, Pinto MMM, Kijjoa A. (2017). Anticancer and cancer preventive com-

pounds from edible marine organisms. Semin Cancer Biol, 46: 55–64.

Hormaeche CE, Joysey HS Desilva L, Izhar M, Stocker BA. (1990). Immunity induced by live attenu-

ated Salmonella vaccines. Res Microbiol,141: 757–764.

Mclaughlin-Drubin ME and Munger K. (2010). The human papillomavirus E7 oncoprtein. Virology,

384: 335–344.

Medina E and Guzma CA. (2001). Use of live bacterial vaccine vectors for antigen delivery: potential

and limitations. Vaccine, 19: 1573–1580.

Smal C, Alonso LG, Wetzler DE, Heer A, de Prat Gay G. (2012). Ordered self-assembly mechanism

of a spherical oncoprotein oligomer triggered by zinc removal and stabilized by an intrinsically

disordered domain. PloS One, 7: e36457.

Yap K, Ada G, McKenzie IF. (1978). Transfer of specific cytotoxic T lymphocytes protects mice in-

oculated with influenza virus. Nature, 273: 238–239.



Summary

We are all aware that flowers have a significant function both in our daily lives and in our na-

tional economy. Flowers are used mostly for social and religious purposes in India. Many flowers are

medicinal and are also used in Ayurveda. Flowers are mentally charming and help to get out of sick-

ness. Flowers can be used as a commercial product and by exporting them they can produce enormous

foreign currencies. The setting-up of production farms for flower and perfume industries would contrib-

ute greatly to addressing the issue of unemployment. Floriculture garden in the countryside is part of

contemporary life and thus ornamental plants have found a place of pride in house gardening.

Present status of Floriculture in India

As demand for flowers has gradually increased, floriculture has become an important trade in

agriculture in the commercial sector. Therefore in controlled climatic conditions, commercial flower

farming has become a high-tech operation inside the greenhouse. Floriculture in India, as a high-growth

industry, has become significant from the export point of view. The liberalization of industrial and com-

mercial policies has paved the way for exportation-orienting cut flowers to grow. It has been grown into

the key floriculture centres of Maharashtra, Karnataka, Andhra Pradesh, Haryana, Tamil Nadu, Raja-

sthan and West Bengal.

On the export front, there has been steady growth in floriculture by 20 percent last year. In terms

of quantity and volume, the domestic flower trade has seen a significant increase in the last decade. Flo-

riculture in agriculture has been one of the main trades in society, both traditionally and seasonally. In

2014-2015, approximately 248.51 thousand hectares were cultivated in floriculture. Flowers are ex-

pected to grow 1,658,000 tonnes of loose flowers and 472,000 tonnes of cut flowers in 2014-2015. Ma-

jor Export Destinations (2016-17) were major importing countries for Indian floriculture in the same

period: United States, Germany, the United Kingdom, The Netherlands, and the United Arab Emirates.

Importance

Flowers are a sign of beauty, sophistication, and celebrations for our eyes. These are used for

every religious festival. Flowers are issued as birthday gifts, wedding present or at funeral meetings

with sick people. Most Hindu ladies stick, hairstyle with flowers. It's a huge floral ornament that will

add elegance to your beauty, Gajar and Veni. All the people love flowers regardless of nationality, race,

Prospect and Challenges of Flower in India Suvarna L Mahalle, Pinaki Roy* and Shailja Thakur

ICAR-NAHEP, Krishi Anusandhan Bhavan (II), New Delhi-110012

Article ID: 20/12/0108202



sex and frame. Devotees in temples, Gurudwara, church and masjids usually offer flowers. In

the floral craft or arrangement of the bouquets offering to receive the dignitaries, sometimes sea-

soned flowers are often used. When cut flowers are used for vase decoration, that becomes a

marvelous piece of indoor decoration. Flowers are not limited to the beautification, decoration

or preparation, but they also have industrial significance i.e Gajra, Garland, Veni or Bouquets

are also important. For the extraction of essential oil, some flower, such as Rose, Jasmine, Tu-

berose, Kevda, and Bakul are used to prepare perfumes, scents, and fragrance. Products are also

prepared from the rose are rose Gulkand, rose water, etc.

Scope

Flowers have always been an important component of Indian culture. Yet floriculture

has not gained the recognition it merits as a business proposition. The industry is still in the ear-

ly stages and has tremendous potential because soil, climates, labour, transport and the market

are important factors that determine their scale of commercial floriculture. Floriculture is not as

advanced as it should have been in India. Consequently, the potential of growth is enormous.

When floriculture is scientifically established on the pattern of industry, it will thrive and create

enormous money and jobs. Commercial flower cultivation has been found to have greater ca-

pacity per unit area than other crops and is therefore a lucrative business. The Indian floriculture

industry has moved from conventional to export flowers.

The liberalized economy has given the Indian entrepreneurs impetus to develop export-

oriented flower-growing units in a regulated environment. Crop farming consist mainly of cut

flowers, plants for potting, cut foiling, bulbs, tubers, roots and dried flowers and leaves. Rose,

carnation, chrysanthemum, gerbera, gladiolus, gypsophila, liatris, nerine, orchids, archilea, an-

thurium, tulips and lily are the main crops in international cut flora trade. Plants like gerbera,

carnation, etc are cultivated in green houses. Crystal clover, pink, gaillardia, marigold lily, aster,

tuberosis are all crops on the open ground. After initial difficulties, the floriculture industry,

now called the 'sunrise' industry, gained power in India. It has immense potential for growth, as

India enjoys certain advantages over other centres for flowering. It offers cheap labour, suffi-

cient farming areas for the production of flowers, and determined support for farmers, traders

and other parties by the government for example.

Major markets in India

The world floriculture trade is valued at 100 billion and has risen by 15 per cent per

year. However, more than 90 percent of overall global trade in floricultural products is in devel-

oped countries. The key varieties that India exports include dried flowers, cut foliage and cut

flowers. Indian cut flowers (flowers collected in clusters or in single, along with their stalks)



were exported mainly to Sri Lanka, Malaysia, Singapore, West Asia, the Netherlands, the Unit-

ed States and the United Arab Emirates (UAE) during 2014-15. The main producers and export-

ing countries of marigold are China, India and Peru.

Challenges

Growers face many challenges including:

1. Margins decreasing: While prices remain stable over the last few years, most pro-

duction costs have steadily increased. Producers must be more successful in production

and management in order to stay profitable.

2. Environment: Environmental concerns are critical to farmers. Growers reacted with

the use of water for irrigation, the reduction of pesticides and fertilizer use and greenhouse

rinse reductions.

3. Pest control: Public and producer worries regarding pesticide use, as well as pesti-

cide resistance and pesticide depletion, led farmers to pursue alternative methods of pesti-

cide control. Integrated Pest Management (IPM) has a greater role to control pest infesta-

tion in green house. Most farmers already use biological or bio-rational methods for the

supplement or substitution of existing pesticides.

4. Employment: Labor is a major production factor. Bedding and cutting flower grow-

ers face up to one third of gross revenue at the cost of labour. Hence, mechanization are

required in floriculture sector to compete with international markets.

5. Urban-rural conflicts: Since the ancient time, urban-rural conflicts play a crucial role.

Some municipalities look upon floriculture as more of a factory production industry rather

than agriculture. Most municipalities have zoning regulations concerning the maximum

site coverage for green houses

6. Capital costs: New and cutting-edge greenhouse businesses will cost up to $200 per

square metre. For several potential farmers, this is an obstacle to entry. Field-grown cut

flowers and the manufacture of bedding facilities have considerably lower cost of capital.

7. Seasonal demand: The demand for the flower is extremely perishable and seasonal.

Many people choose to purchase flowers for special events or holidays such as St. Valen-

tine’s Day, Easter, Mother’s Day and Christmas. Cultivators need to time the output to

accommodate these demanding times. In a spring duration of 3 weeks, some growers have

30% of their annual sales.



Marketing problems

Shortage of auction centres since only one auction hall is located in India and was opened

in Bangalore in 2007.

Lack of information on the market as farmers do not collect information on the market

prior to cultivation and have problems selling items.

Middleman intervention, since the grower does not get the real price for his products and

the profits are small.

Variable rates

Governance inadequacies in government.

However because of the relative new market, the floricultural industry faces many re-

strictions and growth problems. The industry faces some formidable challenges, including

weak logistics, high costs of freight transportation, inadequate facilities, natural disasters,

financial problems and insufficient databases.

Conclusion

Floriculture also provides many possibilities. It has become a lucrative business deal. It

has significant foreign currency capability. It has enormous job absorption potential and can

give rural economies great impetus. While the flower farming industry in India is expanding

rapidly, there are serious risks for it in the global flower markets as regards harsh and unhygien-

ic competition.



Introduction

Sustainable Agriculture is a process that completely focuses on long-term crops and livestock

with minimal effect on the environment. This technique is used to maintain a balance between the need

for food production and the preservation of the ecological system within the environment. The main

function of this type of agriculture is to reduce the use of fertilizers and pesticides and promote biodi-

versity in crops grown and the ecosystem. It also focuses on maintaining the economic stability of

farms and improving the techniques used by the farmers and their quality of life. A farmer engaged

with this type of agriculture utilizes the water management systems such as drip irrigation which gener-

ally wastes less amount of water. Sustainable agriculture aims to produce food naturally also plentiful

and not harmful to the environment.

As India is a fast-growing country sustainable agriculture is of great importance to accelerate

the productivity, efficiency, employment and reduces the practices of those systems that affect the qual-

ity of soil and water resource by providing guidance.

Role of Sustainable Agriculture for Food Security in India

India is a country where about 15% population is undernourished therefore food security is a

serious problem faced by India. It has been already estimated by the Food and Agriculture Organization

of the UN (FAQ) that over 190 million people go hungry every day in the country.

The yield per hectare of rice in India is 2177 kgs which show that the country is lagging behind

countries such as China and Brazil that have yield rates of 4263 kgs/hectare and 3265 kgs/hectare re-

spectively. The country’s cereal yield per hectare is also 2,981 kgs per hectare which also shows it is

lagging far behind countries such as China, Japan and the US.

The country’s slow growth of agricultural production is due to the inefficient rural transport sys-

tem, lack of awareness about the treatment of crops, limited access to modern farming technology and

the shrinking agricultural land due to urbanization. Apart from these, an irregular monsoon is also one

reason as 63% of agricultural land is dependent on rainfall further increasing the difficulties.

Despite these drawbacks, India has a greater potentiality to increase its agricultural productivity

to meet the food requirements of its growing population. With the adoption of sustainable farming prac-

tices, India and other countries have increased both productivity and reduced ecological harm. With the

use of lesser land, water and energy it has increased higher resource efficiency and profitability for the

Sustainable Agriculture: A Step Towards Self - Sufficiency Sagarika Paul1, Shantonu Paul 2, Mainu Hazarika3 and Praveen Kumar4 1 Department of Geography, J. B College, Jorhat-1 2 Krishi Vigyan Kendra, Dibrugarh, Assam Agricultural University 3 Dept.of Horticulture, Assam Agricultural University, Jorhat, Assam-13 4 Dept.of GPB, LPU, Phagwara, Jalandhar, Punjab-11

Article ID: 20/12/0108204



farmer. It includes the methods to protect and enhance the crops and soil, improve water absorp-

tion and efficient seed treatments. This new technology has helped the traditional farmers to-

wards new and effective agriculture.

One example can be taken as for enhancing the soil certified biodegradable mulch films

are available. It’s a thin layer of productive material which can be applied to the soil to conserve

the moisture and fertility of the soil. Some of the mulch films that are used in agriculture are

made of polythene and which has the unwanted problem of disposal. It requires a lot of time and

labour to remove PE mulch film after its usage. It is a labour intensive and time-consuming pro-

cess to remove the PE mulch film after usage and if it is not removed then it can affect the soil

quality as well as crop yield. Therefore an independently certified biodegradable mulch film is

essential which can be directly absorbed by the microorganisms in the soil and conserves the

soil properties, save labour cost and eliminates soil contamination that comes with the mulch

films.

Another important challenge for Indian Agriculture is the availability of water. The re-

quirement of water is high in crops like sugarcane and rice. Most of the agricultural land in In-

dia is rain-fed and low rainfall years can cause havoc for crops and many other problems which

can directly affect in access to essential food items Another technology that Indian farmers have

been using since long is water conservation and which can also be enhanced. To improve the

root systems seeds can be treated with an enhancement that will lead to more efficient water ab-

sorption. Better treatment of seed in addition to soil and water management can improve the

health of the crop and can boost productivity. This can be made possible by the application of

fungicides and insecticides to protect the seed from the unwanted fungi and parasites that can

damage the crops and decrease their productivity. With the proper use of soil, water and seed

management to increase crop yields and an efficient warehousing distribution system are neces-

sary, to ensure that the outcome reaches the consumer. Indian governments harvest-research

body CIPET put their views regarding the wastage of food in the entire state of Bihar in a year

which is about 67 million tons. Fruits and vegetables those are perishable rotten up in the store-

houses or during transportation due to erratic weather or lack of modern storage facilities. So,

food security can be increased by bringing down the food wastage and increasing the efficiency

in distribution. Using tarpaulins can help in keeping the perishables cool during transportation

and efficient insulation to reduce rotting and energy usage in cold storage. If India wants to

overcome the situation regarding food insecurity then it has to work on these three aspects –

production, storage and distribution.

BASF is one such company which has been working on to increase sustainability in the

entire agriculture sector. One of the examples of this company can be given that shows its ef-

forts towards sustainability is that it offers cutting edge seed treatments that can protect the



crops from some diseases and ultimately provides good plant health benefits such as enhanced

vitality and better tolerance for stress and cold. Besides, BASF has developed a biodegradable

mulch film from its Ecovio® bioplastic in addition to BASF developed a biodegradable mulch

film that can benefit the farmers for better soil without the risk of contamination or increased

costs of labours. Farmers of India are not only benefitted by these but many more companies to

achieve yields which are higher and sustainable.

Products are just one part but the main factor for sustainability is the training of the

farmers so that they use these products beneficially and most safely. Samruddhi is a programme

by BASF which has been outreached from 2007 to 2014 to spread awareness among the farmers

regarding sustainability. Another programme is Suraksha Hamesha (safety always) has reached

over 23,000 farmers and 4000 spray men in 2016 alone across India. Apart from these training

programmes the company also offers a kit to farmers including personal tools and equipment’s

known as “Sanrakshan”. These efforts have been taken to spread awareness regarding the sus-

tainable and responsible use of crop protection products and to ensure the farmers to stay safe

while producing quality good quality food.



Introduction

Nitrogen (N) is the most abundant (78%) gaseous element in atmosphere and acts as the primary

nutrient for plants. It plays a significant role in plant vegetative growth, root growth, metabolism, and

green pigmentation in plants. Deficiency of nitrogen results in yellowing of lower leaves and develop-

ment of V-shaped chlorotic patches on leaves. It also enhances reduced growth as well as restricted lat-

eral bud maturation. To supply optimum level of nitrogen to plants, nitrogenous fertilizers are used in

different forms (organic, in-organic, plant origin, ammonium-nitrogen, nitrate-nitrogen, ammonium and

nitrate, and amide-nitrogen). Commonly used nitrogenous fertilizers are urea (46% N), ammonium sul-

phate (21% N), ammonium nitrate (33% N), di-ammonium phosphate (18% N), calcium ammonium

nitrate (25-28% N), thio-urea (36.8% N), and ammonium chloride (26% N).

Waterlogging is a widespread global problem, occurr

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