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A Fourier transform infrared spectroscopy (FTIR) coupled with multivariate analysis was developed to detect and quantify the contamination of aflatoxin B1 (AFB1) in pure milk. FTIR spectra of milk spiked with known AFB1 concentrations (viz. 10, 20, 30, 40 and 50 ppb) were acquired which revealed differences in absorption between pure and contaminated milk samples, specifically in the wavenumber range of 1800–1331 cm−1. Principal component analysis showed distinct segregation and clustering of AFB1 contaminated milk samples at 5% level of significance. Soft independent modelling by class analogies was used to assess the feasibility of detecting AFB1 in pure milk, and developed models could successfully classified contaminated with the pure milk samples. AFB1 concentration in milk was best predicted in the spectral range of 1484–1423 cm−1 using partial least square and multiple linear regression with coefficient of determination of 0.92, 0.90 and 0.97, 0.92 for calibration and validation, respectively.

Patulin is a dangerous mycotoxin and is relatively stable to heat treatment and thus difficult to inactivate. Its presence in juice is necessary to detect before sale. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy with chemometrics showed potential for its detection in apple juice by modulating pH. Spectra (4000–500 cm−1) of patulin spiked (25, 50 75 ppb) apple juice (pH 4, 6, 8) revealed distinct variations specifically in 1605–1543 cm−1 range. Absorption peak for all the spiked sample having pH 8 were higher than those of spiked samples maintained at pH 6–4. Principal component analysis showed concentration based sample clustering (p ≤ 0.05) at pH 8. Developed models successfully classified different levels of patulin into their respective classes using soft independent modeling of class analogy. Patulin in apple juice was best predicted in wave number range of 1605–1543 and 3049–2975 cm−1, using partial least square regression with coefficient of determination of 0.92–0.88 for calibration and validation, respectively. Current study demonstrated that patulin-contaminated (50 ppb; permissible limit set by FSSAI) juice sample and uncontaminated juice samples could be effectively discriminated using ATR-FTIR spectroscopy by modulating pH of apple juice.

Silo storage is considered the best option for wheat storage. However, the storage losses in warehouse storage are also equivalent to silo storage of wheat when proper storage management practices are adopted and the Food Corporation of India (FCI) is the best example of a sustainable food storage system with only 0.3% storage losses in 3 years of wheat storage. The wheat procurement, storage, and distribution system of FCI is unique in the world and handles about 85 million tons of food grains annually by procuring from farmers at the guaranteed Minimum Support Price that meets certain quality standards. This article discusses the role of FCI in food security, warehouse storage management practice as a model, and storage loss level of wheat during storage.

Pure ghee is superior to other fats and oils due to the presence of bioactive lipids and its rich flavor. Adulteration of ghee with cheaper fats and oils is a prevalent fraudulent practice. ATR-FTIR spectroscopy was coupled with chemometrics for the purpose of detection of presence of pig body fat in pure ghee. Pure mixed ghee was spiked with pig body fat @ 3, 4, 5, 10, 15% level. The spectra of pure (ghee and pig body fat) along with the spiked samples was taken in MIR from 4000 to 500 cm−1. Some wavenumber ranges were selected on the basis of differences in the spectra obtained. Separate clusters of the samples were obtained by employing principal component analysis at 5% level of significance on the selected wavenumber range. Probable class membership was predicted by applying SIMCA approach. Approximately, 90% of the samples classified into their respective class and pure ghee and pig body fat never misclassified themselves. The value of R2 was >0.99 for both calibration and validation sets using partial least square method. The study concluded that spiking of pig body fat in pure ghee can be detected even at a level of 3%. Practical applications The adulteration of pure ghee with cheaper animal body fats is a menace and reports pertaining to the same appear in newspaper frequently. Lard, due to the presence of higher amount of fat, is a choice of unscrupulous manufacturers to be used for adulteration purposes. Thus, techniques for detection of presence of lard in pure ghee needs to be investigated. In this context, the present study was envisaged with the aim to detect presence of pig body fat in pure ghee by using ATR-FTIR. It can be seen that the strong absorbance at the specific wavenumber ranges (3030–2785, 1786–1680, 1490–919 cm−1) are seen in case of pig body fat and the samples spiked with the same and can be used as the regions for detecting the presence of pig body fat in pure ghee. The results of PCA, SIMCA and PLS statistically prove that the said region is good for detecting the presence of pig body fat in ghee, indicating the utility and robustness of the FTIR technique.

Consistent and slow mass flow rates of granular materials through a small diameter orifice (D) at the center of the bottom of a hopper is difficult to obtain when D is less than 5 times of the characteristic seed size. Rotation of the bottom in the horizontal plane with the orifice placed at an off-center distance (R) from the center of the hopper can sustain controlled flow rates even at small D. A simple feeding system was developed in this study for discharging roasted makhana seeds of different sizes (7.48–12.40 mm diameter) at 10–30 kg h−1 consistent mass flow rates. The feeding system consists of a rotating orifice plate at an off-center distance, which is placed inside a pipe connected with the bottom of a trapezoidal hopper. The effects of rotational rate (ω), D, and R on the mass flow rates of makhana seeds and plastic beads of different sizes have been investigated. The materials did not discharge when the orifice was stationary. The mass flow rate increased with the increase in ω, D and R. Finite mass flow rates in the range of 2.25–29.81 kg h−1 were obtained for different seed sizes of roasted makhana seeds with varying D (15–20 mm), R (20–30 mm), and ω (0.52–7.86 rad s−1). The mass flow rates >30 kg h−1 were obtained at D ≥ 25 mm, however, finite mass flow rate ranges were not be obtained for all seed sizes at R ≥ 20 mm. The seed discharge was in the funnel flow regime for all D, R, ω, and seed sizes because of the geometry of the hopper and feeding system. The existing Beverloo equation did not describe the mass flow rate adequately for the developed system. Therefore, Beverloo equation was modified using a function similar to the Froude number to describe the mass flow rate. The developed feeding system performed well in feeding makhana seeds and plastic beads of different sizes and maintained finite mass flow rates.

The postharvest quality and storage life of vegetables are controlled by maturity due to their cells still alive after harvest and continue their physiological activity. The objective of this study was to monitoring physico–chemical quality parameters of intact tomato ( Lycopersicum esculentum ) during storage (18 °C, 85% RH) for 12 days, based upon visible/near-infrared (VIS/NIR) absorbance spectroscopy from 350 nm to 1050 nm. Partial least squares regression (PLSR) was applied to estimate soluble solids content (SSC), Titratable acidity (TA), and lycopene content of the tomatoes. The PLSR calibration model with SSC at 12 days storage, gave the highest coefficient of determination (R 2 ) = 0.91, root mean squared error of prediction (RMSEP) = 0.285 and bias = −0.003. While the lowest R 2 with lycopene (0.73) and bias of −0.002 at harvesting day. Changes of sweetness index (SI), SSC, TA and lycopene content varied from 7.16 to 11.39, 4.25 to 5.51 °Brix, 0.5936 to 0.4837% and 8.65–42.69 mg/kg fresh tomato, respectively. While, Hunter colour values L*, a*, and b* were changed from 60.5 to 38.86, −2.85 to 36.59 and 37.07 to 30.92, respectively. The results showed that physico–chemical quality parameters changes significantly during storage of turning maturity tomatoes and have potential application in the field of post-harvesting.

Storage quality of shelled green peas (Pisum sativum var. sativum L) was investigated under modified atmosphere packaging (MAP: perforated and non perforated) compared to unsealed samples, respectively, at T1 (4 ± 1 °C and 94 ± 2 % RH) and T2 (10 ± 1 °C and 90 ± 2 % RH) for each sample and during period of storage (8, 16 and 24 days). Modified atmosphere (MA) was created using low density polyethylene (LDPE) film packages having 107 μm of film thickness and package size of 0.022 m(2). Quality parameters viz., weight loss (WL), total phenolic content (TPC), instrumental colour, ascorbic acid (AA) and sensory characteristics were evaluated during storage period. Weight loss was in the range of 0.18 to 3.54 (zero perforation at T1), 0.21 to 6.48(unsealed samples at T2) and 0.31 to 9.64 % (zero perforation at T1) after 8, 16 and 24 days of storage, respectively. Total phenolic content significantly increased to 102.47-161.54 mg/100 g from an initial value of 91.53 mg/100 g for all the samples and treatments studied. The MAP non perforated sample stored at T2 recorded maximum Hunter 'L' and '-a' colour values than all other samples. A significant decrease in AA content was observed in all the samples with maximum loss (53.77 %) in unsealed sample stored at T2, whereas MAP (3 perforations) sample stored at T1 retained maximum AA (90.50 %). Sensory quality analysis revealed that MAP (3 perforations) sample stored at T1 was in acceptable quality, with good appearance and overall acceptance. The study shows that shelled green peas can be stored in MAP with 3 perforations (0.4 mm dia) in the temperature range of 4 to 10 °C and 90-94 % RH to extend shelf life with marketable quality for 24 days.

Milk consumption is steadily increasing, especially in India and China, due to rising income. To bridge the gap between supply and demand, unscrupulous milk vendors add milk-like products from vegetable sources (soymilk) to milk without declaration. A rapid detection technique is required to enforce the safety norms of food regulatory authorities. Fourier Transform Infrared (FTIR) spectroscopy has demonstrated potential as a rapid quality monitoring method and was therefore explored for detection of soymilk in milk. In the present work, spectra of milk, soymilk (SM), and milk adulterated with known quantity of SM were acquired in the wave number range of 4000-500cm(-1) using Attenuated Total Reflectance (ATR)-FTIR. The acquired spectra revealed differences amongst milk, SM and adulterated milk (AM) samples in the wave number range of 1680-1058cm(-1). This region encompasses the absorption frequency of amide-I, amide-II, amide-III, beta-sheet protein, α-tocopherol and Soybean Kunitz Trypsin Inhibitor. Principal component analysis (PCA) showed clustering of samples based on SM concentration at 5% level of significance and thus SM could be detected in milk using ATR-FTIR. The SM was best predicted in the range of 1472-1241cm(-1) using multiple linear regression with coefficient of determination (R(2)) of 0.99 and 0.92 for calibration and validation, respectively.

Milk adulteration with synthetic chemicals is a serious concern for human health. Urea is added in milk which causes severe stomach ailments. Potential of attenuated total reflectance (ATR)-Fourier transform infrared (FTIR) spectroscopy was evaluated for rapid detection and quantification of added urea in milk. Altogether, 210 spectra (4000–700 cm−1) of milk adulterated with known urea concentration (viz., 100 ppm, 500 ppm, 700 ppm, 900 ppm, 1300 ppm, and 2000 ppm) were analyzed. The spectral range of 1670–1564 cm−1 comprising four smaller spectral regions (1670–1653, 1649–1621, 1615–1580, and 1594–1564 cm−1) showed clear differences in absorption values. Pattern recognition analysis using Soft Independent Modeling of Class Analogy (SIMCA) provided well-separated clusters, viz., pure milk and urea 900 ppm. Quantity of urea was best predicted in the spectral range of 1649–1621 and 1611–1580 cm−1 using partial least square (PLS) regression with coefficient of determination 0.906 and 0.879 for calibration and validation, respectively.

A method of preparing microcapsules using two-fluid glass nozzle was studied for microencapsulation of food ingredients. In this method, a solution of sodium alginate and starch was sprayed using a two-fluid glass nozzle into a reaction vessel containing calcium chloride gelling bath. The aim of this work was to study the effect of some process variables on particle size of microcapsules. Response Surface Methodology by applying Box-Behnken design was used to optimize four independent variables viz., sodium alginate concentration (% w/v), starch concentration (% w/v), pressure (bar), and flow rate (ml/min) for obtaining target particle size. The ANOVA of the regression model demonstrated that the model was highly significant and adequate (p = 0.0054, R 2 = 0.8837). The microcapsules produced have average particle size ranging from 104.56 to 734.69 μm. The results revealed that concentration of sodium alginate solution and air pressure used for atomization had significant effect on particle size of microcapsules (p

This study proposes a formula for prediction of maturity index ( I m ) using physico-chemical characteristics and overall acceptability (OA) of a sensory panel for mangoes from orchards of nine Indian states. Computed I m values were found to be in agreement with both OA scores and the perceptions of experienced farmers. NIR spectra of 1180 mangoes were acquired. Multiple-linear regression (MLR) and partial least square (PLS) models were developed in the wavelength range of 1200–2200 nm to predict I m . The best prediction was achieved using PLS model after MSC data treatment in the wavelength range of 1600–1800 nm. Multiple correlation coefficients ( R ) for calibration and validation of PLS model were 0.74 and 0.68, respectively. Lower difference in standard errors of calibration (0.305) and prediction (0.335), indicated the potential of NIRS in prediction of the maturity non-destructive.

Onion powder has an extensive demand and wide application worldwide as flavour additive in convenience foods and medicinal products. Conventionally onion powder is prepared by hot air drying of onion slices followed by grinding. Convective air drying when used alone demands longer drying time and thus has a high expense of energy. As bulk of onion is water (82-87 %), removal of moisture prior to drying can reduce moisture loading on dryer and hence the energy consumption. Keeping this in view, onions were partially dewatered using centrifugal force before convective drying. The effect of partial mechanical dewatering and drying air temperature was studied on drying time, specific energy consumption and onion powder quality (colour and flavour). The combination process was also optimized to achieve increased drying rate and product quality comparable to products obtained using convective drying alone. Onions subjected to 60 % partial mechanical dewatering and hot air drying at 70 °C exhibited significantly (p ≤ 0.5) shortened drying time, decreased energy consumption and maintained colour and flavour of the dried product.

Mango cultivars are presently identified phenotypically. In the present study, near-infrared spectroscopy in the wavelength range of 1,200–2,200 nm, in combination with chemometrics was evaluated for the purpose. Principal component analysis and partial least square (PLS) discriminate analysis were applied using characteristic variables as 0 and 1 for cv Alphonso and Banganapalli, respectively, in one group and for Dasheri and Malda, respectively, in the other group. PLS was carried out with and without pre-processing of spectral data. Wavelength range of 1,600–1,674 nm was found to be suitable for the classification of Alphonso and Banganapalli after detrending of data, while Dasheri and Malda could be classified in the wavelength range 1,200–2,200 nm after computing Norris-Gap derivative. Alphonso–Banganapalli could be differentiated from each other with 99 % accuracy, whereas, accuracy for Dasheri and Malda was about 94 at 5 % level of significance.

Pediocin is small antilisterial polypeptide bacteriocin. Direct addition of pediocin has been studied so far and is found to be effective only for a limited duration of time. The controlled release or slow release is an efficient method to prolong the effectiveness of pediocin and other such antimicrobials. Encapsulation is one of the numerous strategies that can be employed for achieving controlled release. Diverse wall materials such as phospholipids, proteins and carbohydrate polymers and combinations of these are used to encapsulate active ingredients. One of the aims of this study was to evaluate the effect of process parameters, viz. concentration of phospholipid (lecithin, phophatidylcholine) at the rate of 0.1, 0.2 and 0.3 % (w/v), amplitude for sonication (40, 50 and 60 %) and sonication time (3, 5 and 7 min), on size of nanoliposomes. There was an increase in liposome size with increase in concentration of phospholipids; however, there was decrease in size with increase in amplitude and duration of sonication. The main aim of the study was to compare the controlled release behaviour of pediocin loaded in delivery systems of different wall materials, viz. nanoliposomes (lecithin, phophatidylcholine), capsules of alginate plus guar gum and hybrid capsules of alginate plus guar gum incorporated with nanoliposomes. Encapsulated pediocin was found to be more effective in inhibiting bacterial growth than directly added pediocin. Hybrid capsules of alginate plus guar gum incorporated with pediocin-loaded nanoliposomes of phosphatidylcholine were found to be the best delivery system for controlled release of pediocin.

Ghee forms an important component of the diet of human beings due to its rich flavor and high nutritive value. This high priced fat is prone to adulteration with cheaper fats. ATR-FTIR spectroscopy coupled with chemometrics was applied for determining the presence of goat body fat in ghee (@1, 3, 5, 10, 15 and 20% level in the laboratory made/spiked samples). The spectra of pure (ghee and goat body fat) and spiked samples were taken in the wavenumber range of 4000–500 cm−1. Separated clusters of pure ghee and spiked samples were obtained on applying principal component analysis at 5% level of significance in the selected wavenumber range (1786–1680, 1490–919 and 1260–1040 cm−1). SIMCA was applied for classification of samples and pure ghee showed 100% classification efficiency. The value of R2 was found to be >0.99 for calibration and validation sets using partial least square method at all the selected wavenumber range which indicate that the model was well developed. The study revealed that the spiked samples of goat body fat could be detected even at 1% level in ghee.

Aflatoxin M1 (AFM1), a potentially carcinogenic compound, is found in milk obtained from animals that consume contaminated feed. Spectra of bovine milk, spiked with AFM1 (0, 0.02, 0.04, 0.06, 0.08 and 0.1μg/l) were acquired using attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectrometer. Spectra revealed significant differences among pure and AFM1 spiked samples in spectral regions 1800-650cm-1 and 3689-3499cm-1, which may be attributed to complex chemical structure of AFM1. Principal component analysis (PCA) showed clear clustering of samples (p⩽0.05). The models could successfully classify (>86%) and detect even 0.02μg/l AFM1 in milk (p⩽0.05) using SIMCA. AFM1 was best predicted in wavenumber range of 1800-650cm-1 with coefficient of determination (R2) of 0.99 and 0.98, for calibration and validation, respectively, using partial least square (PLS) regression. The study indicated feasibility of ATR-FTIR spectroscopy and chemometrics in rapid detection and quantification of AFM1 in milk.

Food is defined as a substance—whether processed, semiprocessed, or raw—that is intended for human consumption and is essential for nourishment and subsistence of life. Food safety and quality are therefore of paramount importance and have drawn attention of all stakeholders. With the increasing liberalization of the agro-industrial market and consumer awareness, the food supply chain is becoming integrated. Food safety and quality therefore have become major concerns. It is not enough to just produce food; the food must first be safe to consume and, second, be wholesome and nutritious throughout the supply chain, from production to consumption. This chapter deals with definitions of food safety and quality; types of physical, chemical, and microbiological adulterants, contaminants, residues, and toxins; as well as Hazard Analysis and Critical Control Points (HACCP), with an example of producing and supplying safe food.

There are basic techniques, biosensors, and spectroscopy combined with chemometrics for the detection and quantification of adulterants and contaminants. The first method usually destroys the sample, whereas the second and third ones give surface or subsurface information only (if the samples are solid). It is therefore difficult to know the infected, rotten areas (microbes, etc.) if they are inside a solid food (e.g., a fruit fly or stone weevil in mango or guava) and any other internal undesirable artifacts in any solid food. These internal infected areas and/or bacteria or fruit flies can be only seen using suitable imaging techniques. The basic theory of X-ray, computed tomography, magnetic resonance imaging, and ultrasonic and hyperspectral imaging and their applications for the detection of these internal defects in foods are described briefly in this chapter so that one can have a complete spectrum of knowledge to test food materials with regard to internal artifacts.

Biosensors are emerging as an attractive solution for rapid detection of food-borne pathogens, toxins, pesticides and drug residues, and heavy metal ions in foods. Biosensors combine the selectivity of biology with the processing power of modern microelectronics and optoelectronics to offer powerful new analytical tools with major applications in medicine, environmental diagnostics, and foods and their processing industries. It is gaining importance and popularity over conventional analytical techniques because of specificity, low cost, fast response time, portability, ease of use, and continuous real-time signal; conventional methods, on the other hand, are costly, laboratory-bound, and require trained personnel. Biosensors offer rapid and accurate detection with minimal sample preparation. They are also amenable for online analysis. This chapter describes type of biosensors and their conceptual understanding with practical applications.

Food standards are legislative instruments, often called “food laws,” which are enacted to protect consumers against unsafe products, adulteration, and fraud; to ensure quality compliance; as well as to protect honest food producers, processors, distributors, and traders. They also facilitate the movement of goods within and between countries by providing a common lexicon for food quality and safety. Standards are designed for many purposes. The main concern is quality and safety, but any standard/regulation cannot be set to the zenith level of quality; therefore, above-average quality is generally taken into consideration in enforcement on a wider scale. Quality level and safety are of prime focus during the formulation of laws or standards to ensure the availability of nutritious food and fair trade practices across countries. Governmental agencies help prominently in the standard formulation process and describe fully what is required to meet a certain standard. Standards, grades, and their definitions and specifications act as reference points in aspects of quality, safeguarding the interest of farmers, processors, distributors, traders, and ultimately consumers. Standards help to ensure that food is wholesome and contains whatever the label claims, and they minimize the chances of deceit in terms of quality and economic value and associated risk. Permissible limits are often defined in the majority of food standards to identify maximum or minimum levels acceptable and thus provide an aid for avoiding foods having risk or any health hazard. Establishment of these limits or levels depends on the intended objective of examination by law enforcement agencies and bodies involved in enforcing the laws or standards. Scientific developments in the field of agriculture had led to increased use of modern-day chemicals: insecticides, pesticides, herbicides, veterinary drugs, and many exogenous chemicals with undesirable compounds, for example, plant toxicants, and mycotoxins, which can penetrate the food supply chain. Their residual effects on foods have magnified the associated risk, and they need to be scientifically monitored, with precise limits for labeling foods as safe for human consumption.

Spectroscopy together with chemometrics is a powerful tool for detecting and quantitatively predicting the chemical composition of a material. Studying properties of matter through their interaction with different-frequency components of the electromagnetic spectrum is called “spectroscopy.” In Latin spectron means “ghost” or “spirit,” and in Greek, σκοπeιν means “to see.” With light, you are not looking directly at the molecule—the matter—but its “ghost.” You observe the light's interaction with different degrees of freedom of the molecule. Each type of spectroscopy with a different light frequency gives a different picture, which is called a spectrum. Spectroscopy is a general methodology that can be adapted in many ways to extract the needed information (energies of electronic, vibrational, rotational states; structure and symmetry of molecules; dynamic information). Extraction of information is possible using different techniques, and one of them is chemometrics, which means performing calculations using measurements of chemical data. This can be anything from calculating pH from a measurement of hydrogen ion activity to computing a Fourier transform interpolation of a spectrum. Chemometrics, therefore, is the science of extracting information from chemical systems by data analyses using various multivariate statistical techniques. This chapter deals with different types of infrared spectroscopy, data analysis techniques, and their practical applications.

The competitiveness of food production is now more dependent on safety, quality, and production procedures than on quantity and price. Food safety is related to the protection of human health from microbiological, chemical, and physical hazards. These hazards are difficult to detect by consumers and thus mostly are implemented by food-regulating bodies of respective countries. There are numerous detection techniques, but their acceptance varies from country to country depending on their own standards, the methodologies available, the level of accuracy, and so on. This chapter deals with some basic conventional microbiological, molecular, microscopic techniques, among others, to give readers an idea about detection before moving on to the chapters describing rapid/modern detection techniques.

Nisin is a widely used bacteriocin active against gram positive bacteria and is also reported to be active against some gram negative bacteria. Incorporation of nisin into food systems is another challenge as directly added nisin is prone to inactivation by food constituents. Encapsulation of nisin has been done so far in liposomes which is rather an expensive technology involving multiple processes. Other cost effective alternatives with good encapsulation efficiency and better control release properties are sought. Alginate is useful as a matrix for entrapment of bioactive compounds. Present study was aimed at optimizing conditions for microencapsulation of nisin using calcium alginate as primary wall material and guar gum as filler at different air pressures using response surface methodology. The optimum conditions were: sodium alginate concentration (2 % w/v), guar gum concentration (0.4 % w/v), and air pressure (0.5 bar gauge). The encapsulation efficiency of nisin in microcapsules produced under optimal conditions was 36.65 %.

This paper presents a rapid ATP assay for monitoring the total bacterial load associated with mango fruit surface. Conventional methods such as total plate count for the determination of total microbial counts are time consuming and prone to contamination resulting in low accuracy. Thus the need for quick and accurate methods for determination of total microbial count has led to development of many rapid techniques such as ATP bioluminescence. In this study the potential of ATP bioluminescence method for the determination of total bacterial count on mango surface has been evaluated using two types of luminescence techniques based on fluorescence spectroscopy and bioluminescence. Various mechanical and chemical extraction processes were employed for the extraction of ATP from bacterial cells and the best extraction was achieved with 0.03 M TCA. Minimum level of detection of ATP using fluorescence spectrophotometer and bioluminometer was found to be 10 −8 M and 10 −13 M, respectively. This ATP concentration was correlated with the number of bacterial cells present on mango surface. The minimum level of detection of bacterial cells in fluorescence spectroscopy and bioluminescence was found to be 10 7 cfu/ml and 10 2 cfu/ml, respectively.

The antioxidant activity of extract of berries of Spreng (curry tree), Murraya koenigii (L.), was estimated by DPPH free radical scavenging activity method. Total phenolics, total flavonoids, and reducing power were also estimated. The additional study was carried out to evaluate the antioxidant potential of curry berry extract (CBE) in raw chicken meat homogenate during refrigerated (4 ± 1 °C) storage. Total phenolics in CBE were 9.5 ± 0.03 mg TAE/gdw and total flavonoid contents were 11.9 ± 0.66 mg CE/gdw. CBE also showed remarkable DPPH radical scavenging activity (20.9 ± 0.15 %) and reducing power. During refrigerated storage, the TBARs (mg malonaldehyde/Kg), FFA (%), and odor scores at all stages were significantly (P < 0.01) more in control than CBE treated groups. Thus, curry tree berries may be a good natural source of antioxidative compounds to prevent oxidative damage of meat and meat products.

Agriculture industries are continuously in search of new user friendly technologies to evaluate the intrinsic properties of fruits before it is put in the market for the consumer. In the current study the potential of near-infrared (NIR) spectroscopy in the wavelength range of 1200–2200 nm was evaluated to determine total soluble solids and pH for seven major cultivars of mangoes from seven states of India. NIR models were developed based on multiple-linear regression (MLR) and partial least square (PLS) regression employing preprocessing technologies (baseline correction, smoothening, multiplicative scatter correction (MSC) and second order derivatisation). The multiple correlation coefficients for calibration and validation were found to be 0.782 and 0.762 for total soluble solids and 0.715 and 0.703 for pH respectively. The standard errors of calibration, prediction, biases and differences in them were low which indicated the NIRS potential to predict internal quality parameters (TSS and pH) of mango non-destructively for both models.

Potential of spectroscopy in the wavelength range of 299–1100 nm for nondestructive prediction of dry matter (DM) content, pH, sweetness (total soluble solids, TSS), and acid–Brix ratio (ABR) for banana was studied to have proper estimation of their maturity and ripening stage. Partial least square (PLS) and multiple linear regression (MLR) employing pre-processing techniques were carried out. PLS models were found to be the best with multiple correlation coefficients for calibration and validation were found to be 0.88 and 0.81 °Brix for TSS, 0.85 and 0.78 for ABR, 0.88 and 0.83 for pH and 0.90 and 0.87% for DM, respectively. The standard errors of calibration, prediction, biases and differences in them were low, which indicated that NIRS has potential to predict maturity and ripening parameters of banana nondestructively.

Banana is an important sub-tropical fruit in international trade. It undergoes significant textural and color transformations during ripening process, which in turn influence the eating quality of the fruit. In present study, color ('L', 'a' and 'b' value) and textural attributes of bananas (peel, fruit and pulp firmness; pulp toughness; stickiness) were studied simultaneously using Hunter Color Lab and Texture Analyser, respectively, during ripening period of 10 days at ambient atmosphere. There was significant effect of ripening period on all the considered textural characteristics and color properties of bananas except color value 'b'. In general, textural descriptors (peel, fruit and pulp firmness; and pulp toughness) decreased during ripening except stickiness, while color values viz 'a' and 'b' increased with ripening barring 'L' value. Among various textural attributes, peel toughness and pulp firmness showed highest correlation (r) with 'a' value of banana peel. In order to predict textural properties using color values of banana, five types of equations (linear/polynomial/exponential/logarithmic/power) were fitted. Among them, polynomial equation was found to be the best fit (highest coefficient of determination, R(2)) for prediction of texture using color properties for bananas. The pulp firmness, peel toughness and pulp toughness showed R(2) above 0.84 with indicating its potentiality of the fitted equations for prediction of textural profile of bananas non-destructively using 'a' value.

Mango is an important commercial fruit and is marketed based on their colour, firmness and taste. These sensory parameters vary with individual mango and person involved in testing. There is little or no information available on the instrumental estimation of these sensory attributes. The present study, therefore, was conducted to correlate sensory and instrumental textural attributes to explore the possibility of predicting them for seven major cultivars of mango influenced by harvesting dates and ripening period (10 days). In general, the textural property of peel, pulp and fruit decreased while sensory attributes increased during fruit ripening. Sensory qualities like taste, flavour and overall acceptability were significantly affected by harvesting date, cultivar and ripening period. Harvesting time and cultivars, however, did not influence the fruit appearance. Among textural attributes, peel firmness was closely associated with all the sensory parameters indicating that textural parameters could be useful to predict sensory profile of mango cultivars during their ripening. Cultivar-specific variations were observed while evaluating various equations (linear/polynomial/exponential/logarithmic/power) for correlating their textural and sensory attributes. Polynomial equation was found to be the best fit (highest coefficient of determination, R2) for prediction of sensory quality using textural properties of majority of mango cultivars. All cultivars under study except Alphonso collected from Maharashtra showed R2 value above 0.911 which indicated potentiality of the fitted equations for the prediction of sensory attributes using textural characteristics of mango.

Physico-chemical quality parameters of apple were measured during storage using standard techniques and fitted to model expressions for developing an overall quality index (Iq). Predicted Iq was validated with the trends of sensory scores. Total Soluble Solids (TSS) and acidity varied from 13.2 to 12.3 ºBrix and 0.161 to 0.079%, respectively whereas, Hunter colour values L, a, b and yellowness index were 48.7-56.1, 11.0-19.4, 18.8-20.2 and 84.6-98.2, respectively. The gloss at 45 and 60º incidence angles, density and Iq varied from 7.5 to 4.3 and 6.7 to 2.6 GU, 1.01 to 0.96 kg m(-3) and 0.26 to 1.02, respectively. The variation in sensory overall quality scores with storage period was found to be in line with computed overall quality index. The Iq thus, could be defined as the ratio of product of acidity and TSS to the mode of product of a and b Hunter colour values. The polynomial regression equations for Iq with TSS, acidity, a, b, and storage period yielded the correlation coefficients of 0.8443, 0.9838, 0.7130, 0.7183 and 0.9665, respectively; which indicated that overall quality index could be predicted nondestructively using any one of these parameters during storage.

Quality inspection of food and agricultural produce are difficult and labor intensive. Simultaneously, with increased expectations for food products of high quality and safety standards, the need for accurate, fast and objective quality determination of these characteristics in food products continues to grow. However, these operations generally in India are manual which is costly as well as unreliable because human decision in identifying quality factors such as appearance, flavor, nutrient, texture, etc., is inconsistent, subjective and slow. Machine vision provides one alternative for an automated, non-destructive and cost-effective technique to accomplish these requirements. This inspection approach based on image analysis and processing has found a variety of different applications in the food industry. Considerable research has highlighted its potential for the inspection and grading of fruits and vegetables, grain quality and characteristic examination and quality evaluation of other food products like bakery products, pizza, cheese, and noodles etc. The objective of this paper is to provide in depth introduction of machine vision system, its components and recent work reported on food and agricultural produce.

Fourier transform infrared spectrometer equipped with attenuated total reflection and chemometrics were used to determine added sugar content (ASC), total soluble solids (TSS) and real juice content (RJC) in fresh and commercial mango juice. Sucrose solutions (0–27%), fresh mango juice adulterated with 0–27% sucrose, and two commercial brands were evaluated in wavenumber range of 4000–650 cm � 1 . Partial least squares (PLS) discrimination and principal component analysis (PCA) were used to classify the samples with or without ASC. PLS and multiple linear regression (MLR) were carried out with and without data treatments. The detection limit for ASC was 3% for samples with low natural TSS, 5% for samples with natural TSS more than 10% and 3.6% for commercial samples. ASC, TSS, and RJC were predicted in the wavenumber range of 1476–912 cm � 1 using PLS (multiple correlation coefficient, R = 0.99) and three wavenumbers (1088, 1050, 991 cm � 1 ) using MLR (R = 0.98).

Betel leaves were stored for 10 days at 20C under modified atmosphere packaging (MAP) to assess the impact of differential in-pack gaseous atmospheres on the pigments and an antioxidant. Under all the packaging treatments, chlorophyll was maintained during the entire storage period, and the final retention levels were highly influenced by package headspace atmosphere dynamics. Among different packaging treatments, the in-pack partial pressures of 2.5 kPa for O2 and 6.2 kPa for CO2, respectively, for the film packages containing 750 g of betel leaves, resulted in better retention of chlorophyll. The β-carotene content remained largely unaffected. Results suggested that although the build-up of CO2 is necessary for the prevention of browning and maintenance of chlorophyll in the betel leaves. However, either the packaging film with appropriate permeabilities for O2 and CO2 or in-pack weight of betel leaves might be such that equilibrated O2 partial pressures could be still higher (9 kPa) to effect only a beneficial increase in the phenolic content. PRACTICAL APPLICATIONS Betel leaf has an enormous market around the world, and the crop, worth billions of Indian Rupees, is exported from India. Traditional packaging, handling, storage and transportation techniques reduce the shelf life and its various nutritional and phytochemical components. This research has focused on the application of modified atmosphere packaging (MAP) technology for the packaging of betel leaf for retail handling and storage, which is, at present, carried out in ice boxes or gunny bags. The results of the study have implied that the pigments and phenolic content of betel leaf can be sufficiently maintained in polypropylene film packages, which shows the potential of MAP for the packaging of betel leaf. Utilization of the results of this research is likely to benefit the wholesaler and the retailer in the value chain to better maintain its shelf-life and various physicochemical properties, as compared with that obtained using traditional storage techniques.

This study examined the surface micro-flora on nine major mango varieties collected from nine states of India in three different harvesting stages (early, mid and late). Mango surface supported substantial microbial component, including various species of bacteria, filamentous fungi and yeasts. Total microbial population was in the range of 105–108 and was significantly different in different cultivars as well as harvesting stages. However, all the mango varieties invariably showed highest microbial population in third harvesting stage. Comparative microbial population of yeast, mold and bacteria showed significant variation in different mango varieties at the third harvesting stage except for Alphonso from Maharashtra and Karnataka. Microbial population on mango fruit surface was strongly influenced by climatic factor, stages of fruit development and varietal specificity.

The king of fruits “Mango” (Mangifera indica L.) is very nutritious and rich in carotenes. India produces about 50% of the total world’s mango. Many researchers have reported the maturity indices and quality parameters for determination of harvesting time and eating quality. The methods currently used for determination of quality of mango are mostly based on the biochemical analysis, which leads to destruction of the fruits. Numerous works are being carried out to explore some non-destructive methods such as Near Infrared (NIR), Nuclear Magnetic Resonance (NMR), X-ray and Computed Tomography (CT), electronic nose, machine vision and ultrasound for quality determination of fruits. This paper deals with some recent work reported on quality parameters, harvesting and post-harvest treatments in relation to quality of mango fruits and reviews on some of the potential non-destructive techniques that can be explored for quality determination of mango cultivars.

Broccoli was stored under modified atmosphere packaging (MAP) at 20 °C in perforated and unsealed polypropylene film packages for a storage period of 10 days to evaluate the effect of modified atmospheres on the chromatic changes. At the end of storage, MAP resulted in differential changes in the original green color of broccoli under different packaging treatments. Instead of conventional CIELAB color space system utilizing only L*, a* and b* values, the chromatic changes were analyzed as per L*C*h* color space system using lightness, chroma, and hue angle values to evaluate the final hue (color) along with its associated attributes. On 10th day of storage, broccoli samples kept under different modified atmospheres were observed to be yellow-green only for 4 holes, but between yellow-green and yellow for 8, 12, and 16 hole treatments, respectively. Further, the saturation of final hue attained under different packaging treatments kept on increasing in the order of 4, 8, 12, and 16 holes. On the other hand, broccoli kept in air in unsealed packages turned orange-yellow with higher saturation as compared with MAP samples. The direction of color difference for different treatments with respect to fresh broccoli samples was observed as light and the degree of color difference indicated that 4 and 8 hole treatments were only slight and medium light, respectively. The 4 hole treatment had best color retention as it had slightly saturated yellow-green hue, which was only slightly lighter than the fresh broccoli. Also, the results of sensory and visual analysis confirmed the results obtained from L*C*h* color space diagram and indicated that the modified atmosphere (6.1% O2and 9% CO2) generated inside the perforated film packages having 4 macro-holes was the most suitable in maintaining the chromatic quality of the broccoli heads.

Mango, an important tropical fruit, is marketed throughout the world. Quality of ripened mango depends on its maturity at harvest, which is hitherto determined subjectively by experience. In the present investigation, the potential of a nondestructive method for predicting maturity using color values taken by a handheld colorimeter was explored. Maturity of mango was defined in term of maturity index (Im), a ratio of total soluble solids (TSS) of mango under experiments and minimum level of TSS (8 °Brix) of matured mango, expressed in percentage. Hunter L, a, and b values of 315 freshly harvested mangoes ranging from immature to over matured were measured using HunterLab colorimeter. TSS of whole mango juice was measured by a handheld refractometer and maturity index was computed. The maturity index and L, a, and b values of 160 samples were fitted in different forms of models using multiple linear regression (MLR), partial least square and principal component regression. The model using MLR on variables a, b and the product ab was selected. The prediction performance of the model was tested with another set of 100 unripe samples. Precision of prediction was also verified by sensory evaluation of 55 ripe mangoes and was found that the fruits predicted to be mature could ripe with high-satisfied taste while the ones predicted to be immature or over mature were mostly rejected by the panels.

Adulteration of milk to gain economic benefit is rampant. Addition of detergent in milk can cause food poisoning and other complications. Fourier Transform Infrared spectroscopy was evaluated as rapid method for detection and quantification of anionic detergent (lissapol) in milk. Spectra of pure and artificially adulterated milk (0.2-2.0% detergent) samples revealed clear differences in wavenumber range of 4000-500cm-1. The apparent variations observed in region of 1600-995 and 3040-2851cm-1 corresponds to absorption frequencies of common constituents of detergent (linear alkyl benzene sulphonate). Principal component analysis showed discrete clustering of samples based on level of detergent (p⩽0.05) in milk. The classification efficiency for test samples were recorded to be >93% using Soft Independent Modelling of Class Analogy approach. Maximum coefficient of determination for prediction of detergent was 0.94 for calibration and 0.93 for validation, using partial least square regression in wavenumber combination of 1086-1056, 1343-1333, 1507-1456, 3040-2851cm-1.

The measurement of firmness and yellowness is of paramount importance to know proper maturity and ripening stage during growth and storage of mango. Evaluation of firmness by present methods destroys the sample and yellowness is estimated by the human eye. In the present investigation, the potential of a non-destructive method for predicting firmness and yellowness index using a handheld colorimeter was explored. Spectra of 290 mango samples were acquired in the visual wavelength range 400–700 nm and they were split into two sets, each of 145 samples, for calibration and validation purposes. Calibration models of partial least-squares regression (PLS1 and PLS2), principal component regression (PCR) and multiple linear regression (MLR) with respect to relative reflectance and its second-order derivatives, smoothing, multiplicative scatter correction (MSC) in different ranges of wavelengths were developed, and tested with validation samples set. The PLS2 model of smoothed, followed by MSC treated, spectra in the wavelength range of 530–550 nm was found to be the best. The standard error of calibration, standard error of prediction and correlation coefficients were found to be 5·0–5·45, 4·87–5·76, 0·88–0·90 and 0·95–0·97 for firmness and yellowness index, respectively. Negligible biases during validation and satisfactory correlation coefficients between predicted and measured showed potential for prediction of firmness and yellowness index of intact mango non-destructively using visual spectra acquired by a colorimeter.

The measurement of maturity is of paramount importance to harvest good quality mango. Changes in size, sphericity, total soluble solids (TSS) content, surface color and firmness of mango were studied during growth and storage at ambient temperature. Size and sphericity were measured using the standard methods. Surface color was determined using a HunterLab colorimeter and the firmness by texture analyzer. The size of the fruits increased gradually during growth and the sphericity remained in the range of 0.67–0.70. Size and sphericity decreased due to shrinkage during storage. The firmness of the fruits remained almost constant over the period of growth and it decreased after attaining the maturity, whereas yellowness of fruits increased during both growth and storage. Maturity of mango could be predicted by measuring size, color and firmness.

Preference for mangoes depends on aroma and sweetness. Evaluation of these parameters by present methods destroys the samples, takes more time and is not usable in continuous packing systems. In the present investigation, the potential of a non-destructive method for predicting sweetness in term of total soluble solids using a handheld colorimeter was explored. Spectra of 329 mango samples were acquired in the visual wavelengths ranging from 400 to 700 nm and they were split into two sets, one of 165 samples for calibration and other of 164 samples for validation purposes. Calibration models of different ranges of wavelengths for prediction of total soluble solids by partial least-squares regression (PLS), principal component regression (PCR) and multiple linear regression (MLR) methods with respect to reflectance and its second-order derivatives, smoothing, multiplicative scatter correction (MSC), were developed and tested with validation sample sets. The MLR model of original spectra in the wavelength range of 440–480 nm was found to be the best. The standard error of calibration (SEC), validation (SEP) and correlation coefficients were found to be 1·91 °Brix, 1·98 °Brix and 0·90, respectively. Similarity in SEC and SEP values and satisfactorily high correlations between predicted and measured values indicated that the developed model has potential for prediction of the total soluble solids of intact mango non-destructively using visual spectra.

Summary Consumer's acceptance of tomato juice depends on its sourness to sweetness ratio and measuring this is important for quality control and marketing. Traditional methods destroy the samples, are time consuming and cannot be used in continuous packing or bottling systems. A non-destructive method of quality evaluation, using near infrared (NIR) techniques, was tested, by using a portable NIR measuring unit. Spectra of tomato juice of known acid and brix values were determined and, in the wavelength range 703–1124 nm (NIR), a calibration model for acid–brix ratio (ABR) was developed, by using unscrambler software. When used to predict ABR of tomato juice statistical analysis showed minimal standard error (0.009) and satisfactorily high correlation coefficients (0.92) over the wavelength range 1059.5–1124.8 nm, for both calibration and prediction. These values were hardly different from analytical results and the NIR model has potential for non-destructive prediction of ABR of tomato juice.

Non-destructive physical tests are recent trends for quality evaluation of fruits and vegetables. Information on post-harvest variations in electrical resistance, gloss and weight are needed to develop new instruments for this purpose. Surface electrical resistance, surface gloss and weight of eggplant (Solanum melongena L.) fruits stored for 0–96 h at 20°C temperature and 80–84% relative humidity were measured using a galvanometer, spectral radiometer and a precision electronic balance, respectively. Relationships of surface electrical resistance with gloss and weight loss during storage were also investigated. The surface electrical resistance increased quadratically with increase in storage period and with decrease in both weight and gloss index of eggplant during storage.

Changes in surface stiffness, mass, volume and density of fresh as well as stored eggplants were studied. Storage period was varied between 0 and 168 h at 15–30 °C temperature and 90% relative humidity. Mass and volume were measured using standard methods and density was computed from them. Surface stiffness was determined using force–deformation curve obtained on uniaxial compression testing machine. Surface stiffness and volume of eggplant decreased nonlinearly till certain time of storage whereas mass decreased linearly throughout the storage period; and the density showed a reverse trend. Rate of reduction of these properties was observed maximum at 25 °C storage temperature. The storage period of 96 and 120 h were found to be critical for the eggplant stored at 30 and 20–25 °C, respectively, after which it may start rotting and may not be good enough to use them for vegetable purposes. Eggplant stored at 15 °C did not show any such sign of detoriation in the ranges of variables studied.

Surface gloss and weight loss are two important parameters to judge the freshness of eggplant. Data were collected in order to develop some quick and reliable instrumental methods to determine these. Surface gloss and weight loss of eggplant stored for 0–96 h at 80–84% relative humidity and 20°C temperature were determined using a computerized spectral radiometer and a precision electronic balance, respectively. The surface gloss was quantified in terms of gloss index, and a relationship between weight and gloss index during storage of eggplant was established. Gloss index and weight both decreased quadratically with storage period. Major changes were observed in the first 48 h of storage. Weight and gloss index of eggplant during storage were found to be correlated linearly.