Post Harvest Technology-A Keyto Survivalof Indian Agriculture


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Modern Food Processing Tecchnologies- A Survival Kit for Indian Agriculture:

Modern Food Processing Tecchnologies - A Survival Kit for Indian Agriculture Dr. R.T. Patil Former Director, CIPHET, Ludhiana Chairman & ED, Benevole for PHT, Bhopal

Indian Perspective:

Indian Perspective Value addition to fruits and vegetables only 2% and to food grain 7% Export market share <1.5% mainly of primary processed goods with low price realization Indian produce have unique aroma, flavour, taste, nutritional properties and health benefits, such as Jamun, Bel fruit, Aonla, Pomegranate, Custard Apple etc. Increase in export potential of Indian processed foods and to meet aspirations of growing middle class highest quality and food safety issues need modernization Emerging Post Harvest Technologies need to be adopted for indigenous commodities involving proper engineering principles……

Status of Food Processing Industries:

Status of Food Processing Industries Size of food market in India - Rs. 8,60,000 Crores Primarily processed food market – Rs. 2,80,000 crore Value added processed food market – Rs. 1,80,000 crore Investment during the 10th plan was about Rs . 62,105 Crores Industry growth rate during the last 10 th plan was about 7.14% against GDP of 6.2% Investment required during next ten years – Rs. 1,10,000 crores Food Quality and Safety Issues are Prime Important

Drivers of R&D in Post Harvest Sector :

Drivers of R&D in Post Harvest Sector Preference for Natural, Fresh-like, Minimally processed, Nutritious, Preservative-free and safe Foods Environmental Sustainability Improved understanding of dietary requirements Breeding of processable varieties

Present Methods of Enhancing Shelf Life/Processing:

Present Methods of Enhancing Shelf Life/Processing Pasteurization (milk, juice, honey etc.) Sterilization (milk, juice, etc.) Canning Hurdle Technology Addition of chemicals as preservative Drying/Dehydration Irradiation Most of these are thermal techniques, detrimental to the preservation of natural flavour and texture

Emerging Technologies for Food Processing :

Emerging Technologies for Food Processing Pulse electric field High pressure processing Ultrasound Cryogenic processing Supercritical fluids including water Ohmic heat processing Irradiation Nano-technology Extrusion processing Microwave and Infrared Processing Nutrigenomics

Microwave Heat Processing:

Microwave Heat Processing Effective for inactivating enzymes, reduced indirect heating requirement and water use Result in improved product flavour, colour, texture and nutritive value.

Ohmic Heat Processing:

Ohmic Heat Processing Alternating electrical current is passed through a food sample. Internal energy generation in foods. Produces an inside-out heating pattern at different frequencies than MW. Uniformly heats foods with different densities.


Micronisation Short time exposure of electromagnetic radiation at a wavelength of 1.8-3.4  m m, Promotes internal heating and increased digestibility Instantized product due to increased ability to uptake of water. Starch is gelatinized, seed microstructure becomes more penetrable and thus short cooking times.

Extrusion Processing:

Extrusion Processing

Extruded Products from Coarse Cereals:

Extruded Products from Coarse Cereals Extrusion is a high temperature short time processed to produce expanded & textured products CIPHET has modified the low cost collet extruder to produce expanded ready to eat snacks using rice and pulse brokens. The cost of the unit is Rs 2 Lakh, capacity 25 kg/h, cost of accessories Rs. 2 lakh and thus earn about minimum of Rs. 50,000 per month


Biotechnology Fermenter of 30 litre capacity with controls for temperature, pH, DO and CO 2 monitoring installed at CIPHET, Ludhiana

Bioprocessing Technologies for Crop Residues:

Bioprocessing Technologies for Crop Residues Efficient process for production of ethanol Production of enzymes such as cellulase, xylanase, pectinase and protease Production of industrially important products such as citric acid Single Cell Protein ( SCP ) production

Smart and Bio-degradable Packaging of Foods:

Smart and Bio-degradable Packaging of Foods Controlled release mechanism technology using volatiles of plant origin for shelf-life extension packaging Food specific packaging having insect-repelling and water absorbing properties Smart packaging interventions for retention of volatile and flavour in packaged food Time-temperature indicators and colour code schemes for shelf-life detection of packaged foods. Poly-lactic acid based bio-degradable clamshell containers and films/coatings for packaging of food materials. Bio-polymer films embedded with nano-composites (biodegradable smart packaging)

Non-thermal Protocols for Food Processing and Preservation (PEF&HPP):

Non-thermal Protocols for Food Processing and Preservation (PEF&HPP) Enhancement of Shelf Life of Milk and RTS Beverages Enhancement of diffusivity of enzymes (xylanase, protease; etc.) and effectiveness of modified enzymes on de-hulling and cooking quality of pulses Development of extraction processes for bioactive mixtures/ compounds from by products and process wastes

High Pressure Processing:

High Pressure Processing HPP can replace conventional processes, while maintaining safety and quality. Effects of HPP are generally marked as retention of color, flavor and fresh appearance

Nano-technologies for Controlled Release and Functional Foods:

Nano-technologies for Controlled Release and Functional Foods Micro-encapsulation and nano-encapsulation of herbal extracts and bioactive compounds Nano-composites for food packaging with improved barrier or antimicrobial properties Nano-emulsions/delivery systems for increased absorption of nutraceuticals and health supplements. Nano-sensors for traceability and monitoring conditions of foods during transport and storage (Hyper homogenisation, Molecular mixing, Multi-emulsion technology)

PowerPoint Presentation:

Designer foods using super critical carbon dioxide having desirable texture, flavours and micro nutrients through extrusion processing Short-time continuous bread making extrusion process without yeast to bread proofing Super critical carbon dioxide and water as solvent for extraction of Bio-active compounds, essential oils Amino acids from fish, meat etc. Supercritical Fluid in Food Processing

Irradiation Technologies for Processing and Preservation:

Irradiation Technologies for Processing and Preservation Standardize the irradiation protocols for retention of properties and shelf-life enhancement Optimized irradiation protocol suitable for Sprouting inhibition, Delay in ripening and senescence, Insect disinfestation, Pasteurisation/sterilisation of processed and raw foods, Reduction in anti-nutritional factors and Improved keeping quality of food grains and flours


Irradiation Gamma - irradiation reduces antinutritional factors Reduces the phytic acid content and flatulence causing oligosaccharides in leguminous crops Helps improved keeping quality of food grains and flours

Biosensors for Rapid and Precise Quality Assessment:

Biosensors for Rapid and Precise Quality Assessment Principle: A biosensor is a probe that integrates a biological component, such as a whole bacterium or a biological product (e.g., an enzyme or antibody) with an electronic component to yield a measurable signal. Characterization of bio-indicators in relation to quality of food and its interaction with electro-mechanical sensing system. Biosensor based online monitoring system

Use of Artificial Intelligence in the Context of Food Processing:

Use of Artificial Intelligence in the Context of Food Processing I n artificial intelligence the tolerance for imprecision and uncertainty is exploited to achieve tractability, lower cost, high Machine Intelligence Quotient (MIQ) and economy of communication Artificial intelligence makes use of multivalued or fuzzy logic Artificial intelligence can deal with ambiguous and noisy data Artificial intelligence can yield approximate answers but good enough to solve the practical problems of trade

Artificial Intelligence:

Artificial Intelligence Artificial intelligence can be used to model and analyse very complex problems where conventional methods have not been able to produce cost-effective, analytical, or complete solutions. In agricultural and biological engineering, researchers and engineers have developed methods to analyse the operation of food processing. Fuzzy Logic (FL), Artificial Neural Networks (ANNs), Genetic Algorithms (Gas), Bayesian Inference (BI), Decision Tree (DT), and Support Vector Machines (SVMs)

Complex Food Process Control:

Complex Food Process Control A single sensory property like color or texture can be linked individually to several dimensions recorded by the human brain. The food industry works with non-uniform, variable raw materials that, when processed, should shaped into a product that satisfies a fixed standard. The process control of foods are highly non-linear and variables are coupled. In addition to the temperature changes during a heating or cooling process, there are biochemical (nutrient, color, flavor, etc.) or microbial changes that should be considered. The moisture in food is constantly fluctuating either loss or gain throughout the process which can affect the flavor, texture, nutrients concentration and other properties. Other properties of foods such as density, thermal and electrical conductivity, specific heat, viscosity, permeability, and effective moisture diffusivity are often a function of composition, temperature, and moisture content, and therefore keep changing during the process. The system is also quite non-homogeneous and hence detailed input data are not available. Often, irregular shapes are present.

ANN for Crispness of Snack Foods:

ANN for Crispness of Snack Foods The crispness was evaluated by acoustic testing. The acoustic patterns were generated by crushing the snack samples with a pair of pincers The inputs for training the NNs comprised 102 amplitudes of sound signals in 0–7 kHz frequency range at the intervals of about 69 Hz with crispness grades as outputs P robabilistic (PNN) models showed good performance in classifying the snack foods into four grades of crispness. The prediction accuracy of models ranged approximately from 96 to 98% Plot of average amplitude of acoustical signal spectrum for different moisture content of Pringles potato chip samples

Detection of Plant Diseases:

Detection of Plant Diseases Electronic nose incorporating AI was used to detect plant disease caused by Ganoderma boninense fungus affecting oil palm. The electronic nose, Cyranose 320, has the front end sensors and artificial neural networks for pattern recognition. The system was able to differentiate healthy and infected oil palm with a high rate of accuracy.

Detection of Spongy Tissue in Mango:

Detection of Spongy Tissue in Mango "spongy tissue", affects about 30% of ‘Alphonso’ mangoes Fruits show no external symptoms at harvest or on ripening but cutting reveals internal damage which adversely affects fruit quality. Both fully grown green, unripe mangoes and ripe fruits show spongy tissue. A non-destructive x-ray inspection can detect affected mangoes. The method could be used for quality control for on-line detection and separation Central Electronics Engineering Research Institute (CEERI)

ANN in image recognition and classification of crop and weeds:

ANN in image recognition and classification of crop and weeds The images were taken, Colour index values were assigned to the pixels of the indexed image and used as ANN inputs. There were 80 images, 100x100 pixels, for training, and 20 images for testing. Many back propagation ANN models were developed with different numbers of PEs in their hidden and various output layers. Six different evaluation schemes for two ANN output strategies were used. The performance of the ANNs was compared and the success rate for the identification of corn was observed to be as high as 80 to 100%, while the success rate for weed classification was as high as 60 to 80%. The results indicated the potential of ANNs for fast image recognition and classification. Fast image recognition and classification can be useful in the control of real-world, site-specific herbicide application.

Identification of citrus disease using color texture and discriminant analysis:

Identification of citrus disease using color texture and discriminant analysis Color co-occurrence method (CCM) with texture based hue, saturation, and intensity (HSI) color features in conjunction with statistical classification algorithms were used to identify diseased and normal citrus leaves under laboratory conditions. The leaf sample discriminant analysis using CCM textural features achieved classification accuracies of over 95% for all classes. Although, high accuracies were achieved when using an unreduced dataset consisting of all HSI texture features, the overall best performer was determined to be a reduced data model that relied on hue and saturation features. This model was selected due to reduced computational load and the elimination of intensity features, which are not robust in the presence of ambient light variation.

Milestones of AI in Food Processing:

Milestones of AI in Food Processing 2004 Brudzewski et al. Classification of milk by an electronic nose 2005 Pierna et al. Classification of modified starches 2006 Chen et al. Identification of tea varieties 2006 Onaran et al. Detection of underdeveloped hazenuts from fully developed nuts 2006 Wang and Paliwal Discrimination of wheat classes 2007 Zhang et al. Differentiate individual fungal infected and healthy wheat kernels. 2008 Fu et al. Quantification of vitamin C content in kiwifruit 2008 Kovacs et al. Prediction of different concentration classes of instant coffee with electronic tongue 2008 Li et al. Classification of paddy seeds by harvest year 2008 Sun et al. On-line assessing internal quality of pears 2008 Wu et al. Identification of varieties of Chinese cabbage seeds 2009 Deng et al. Classification of intact and cracked eggs 2012 Jha et al. Method of determining maturity of intact mango in tree

Researchable Issues:

Researchable Issues Online non destructive measurement of quality of food grains, fruits and vegetables using NIR sensors Electronic nose to assess the quality and authenticity of food products. Electronic tongue - for recognition (identification, classification, discrimination), quantitative multi-component analysis and artificial assessment of taste and flavour of various liquids Affordable instrumentation for measurement of spoilage of grain in bags and silos Smart labels of food packets to detect their shelf life with automatically changing bar codes Simple gadgets like pH meter to detect pollutants in drinking water Method to detect adulterants and harmful chemicals in foods

PowerPoint Presentation:

Thank You!!! With an appeal to support demand for mandatory employment food professional in food establishment

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