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Effects of Shrimp Waste Types and Their Cooking on Properties of Extracted Astaxanthin and Its Characteristics in Liposomes

This study was aimed to evaluate the effects of shrimp waste types (fresh head, cooked head, fresh shell and cooked shell) and of cooking these wastes on the properties of astaxanthin. The astaxanthin was subject to liposomal encapsulation and its characteristics were determined. Astaxanthin was extracted from fresh and cooked (90°C for 15 min) materials, and then yield, astaxanthin content, antioxidant activities (DPPH and ABTS scavenging assays) and fatty acid profiles were determined. Phospholipid was used at various concentrations (2, 3 and 4 % w/v) to prepare astaxanthin-loaded liposomes, which were further evaluated for particle size, zeta potential, antioxidant activity (DPPH scavenging assays) and outer structure by confocal laser scanning microscope. The results showed that fresh shrimp heads gave the highest percent yield (30.49 mg extract/g raw material), but the highest astaxanthin content was found in fresh shrimp shells (14.65 mg/g). Shrimp heads and shrimp shells, both fresh and cooked, were significantly different (p<0.05) in terms of their antioxidant activity (based on DPPH and ABTS scavenging assays). Three fatty acids, palmitic acid, oleic acid and linoleic acid were most abundant and found in all samples. However, extract from fresh shrimp shells showed the highest EPA and DHA content of 10.48 % and 11.62 %, respectively. Astaxanthin-loaded liposomes derived were different in size in that the higher concentration, the larger liposomes produced. Liposomes prepared from 4% (w/v) phospholipid at 50 amplitude gave the highest %DPPH scavenging activity of 79.23.

Introduction
Approximately 6-8 million tons of crustacean waste is generated annually worldwide, based on a recent FAO report [1]. In Thailand, Pacific white shrimp (Litopenaeus vannamei) is the most common species produced, with an estimated production of 263,000 tons each year [2]. Depending on the processing method, 45-60 % of the shrimp becomes by-products (primarily heads and shells) [3]. These materials may not be useful as food products, but they do contain valuable nutrients and other compounds, including chitin, protein, lipid, and carotenoid pigments [4,5,6,7].
Astaxanthin is of increasing interest as an antioxidant, as it exhibits antioxidant activity 100-times higher than α-tocopherol, and 10-times higher than other carotenoids such as lutein, canthazanthin, zeaxanthin and β-carotene [9]. Astaxanthin has been linked to a reduced risk of cancers, diabetes, metabolic syndrome, chronic inflammatory diseases and cardiovascular diseases in humans [10].
Besides astaxanthin, lipids are also found in shrimp by-products. [11] indicated that the hepatopancreas of shrimp are rich in PUFAs (polyunsaturated fatty acids). [12] reported that Northern shrimp (Pandelus borealis Kreyer) by-products are a source of omega-3 polyunsaturated fatty acids. Because of their antioxidant properties, both astaxanthin and polyunsaturated fatty acids (in particular, eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)) may be beneficial for human health such as reducing cardiovascular risk, cancer and anti-inflammation [13]. To our knowledge, few studies have been reported on the difference in properties of astaxanthin and in fatty acid profiles of astaxanthin extracted from fresh and cooked shrimp heads and shrimp shells. [14] reported that heat can lead to degradation and isomerization of astaxanthin. In addition, [15] examined the effects of cooking on astaxanthin with fatty acids extracted from Pacific white shrimp, and reported that astaxanthin monoesters with EPA and DHA had a lower thermal stability than those with saturated fatty acids. Currently, the application of astaxanthin in different food formulations is limited due to their easy degradation in the presence of heat, oxygen and light. Encapsulation technology is considered to be a way of solving these problems.
One encapsulation technique uses liposomes, which are spherical colloidal systems of a phospholipid bilayer with an aqueous internal core, and are commonly used to encase the active agents in pharmaceuticals, cosmetics, foods and nutrition supplements, as well as coatings. [16] showed that the liposome can improve stability of natural astaxanthin derived from white shrimp shells. Liposomes have been studied as delivery systems for improvement of the physical and chemical stabilization of protein hydrolysates from croaker byproduct [17]. [18] reported that liposome decreased the thermal oxidation of astaxanthin extracted from shrimp waste. In addition, [19] indicated that liposome made from phospholipid (phosphatidyl choline70%) at 2% (w/v) maintained the antioxidant activities of astaxanthin obtained from shrimp shell and the liposome showed a high a bioavailability by cellular uptake using cell culture.
The objectives of this study were to determine the properties of astaxanthin and fatty acid profiles found in astaxanthin of fresh and cooked shrimp heads and shrimp shells. In addition, creation of astaxanthin-loaded liposomes using ultrasonic atomizer was conducted and their properties were evaluated.

Extraction of Astaxanthin from Fresh Shrimp Heads and Shrimp Shells
Fresh shrimp heads and shrimp shells were extracted for astaxanthin using ethanol. In brief, the raw materials were mixed with ethanol (raw material:ethanol, 1:2 w/v) and filtrated through filter paper (Whatman No. 1). The extraction was repeated in triplicate. Solvent was removed with a rotary evaporator (under vacuum at 40°C, 175 MPa) and the resulting concentrate was analyzed for astaxanthin quantity using reverse phase High Performance Liquid Chromatography (HPLC) followed the method of [20]. The extracts were kept in the dark bottle at -18°C for further investigation.

Extraction of Astaxanthin from Cooked Shrimp Heads and Shrimp Shells
Fresh shrimp heads and shrimp shells were cooked at 90°C for 15 min. The cooked heads and shells were then further extracted for astaxanthin using the same procedure as for fresh materials as described above in 2.1.

The Yield of the Extract
The yield of the extract was calculated using the equation (1) Where w 0 and w 1 are weight of extract and raw material, respectively.

Analysis of Astaxanthin Content
The extract obtained from both fresh and cooked materials was determined for astaxanthin content by HPLC (Agilent Technologies, Santa Clara, CA, USA), UV/vis detector and C18 column (ZORBAX-Eclipse Plus, 150 mm x 4.6 mm). Samples (20 microliters) were eluted with a mobile phase consisting of 85% methanol, 5% acetonitrile, 5% dichloromethane, and 5% water at a flow rate of 1.0 ml/min and the eluate absorbance was measured at 480 nm. Astaxanthin was identified by its retention time against pure astaxanthin standard. The content was indicated as mg of astaxanthin per g of waste material [20].

Extraction of Lipid from the Extract
The extraction of lipids from astaxanthin extract was conducted using solvent according to [21]. The astaxanthin extract was mixed with chloroform: methanol: distilled water (2:1:2, v/v), was added. After extraction, the obtained lipid was kept for further analysis.

Analysis of Fatty Acids Profile
Fatty acids were analyzed by methylation method of [22]. The extracted lipid (25 mg) was derivatized into FAMEs (fatty acid methyl esters) using 0.5 M sodium methoxide in anhydrous methanol and acetyl chloride in anhydrous methanol. The resulting FAMEs were analyzed by gas chromatograph and Supelco 37 component FAME MIX was used as a standard. Fatty acid profiles were determined using an Agilent 7820A gas chromatograph equipped with FID detector. Separation was performed with an Agilent HP-88 column with split injection (40:1) and helium at a constant flow of 1.2 mL/min. Detector temperature was 260°C and injector temperature was 250°C. The temperature profile of the oven was 170°C which then increased by 5°C /min to 240°C and then held at 240°C for 45 min. Identification was based on comparison of the retention times with standards. Relative percentages of the identified fatty acids were calculated.

2,2-Diphenyl-1-picrylhydrazyl)DPPH ( Radical Scavenging Activity
DPPH radical scavenging activity of the extracts was measured following the method of [23]. A 0.2 mM solution of DPPH in ethanol was mixed with 2 mL of sample solution at different concentrations (10, 25, 50 µg/ml). The solution was incubated for 30 min in the dark. The absorbance of samples was measured at 517 nm using a 96-well micro-plate (PowerWave XS2, BioTek, Winooski, VT, USA). The %DPPH scavenging effect was found using the following equation (2): Where A 0 , A b and A are the absorbance of DPPH solution without the sample, the sample without DPPH solution and the test sample mixed with DPPH solution, respectively.

ABTS2,2'-azino-bis(3 ethylbenzothiazoline-6-sulphonicacid (Radical Scavenging
Activity. ABTS radical scavenging activity was measured using the method of [24]. The working solution was prepared by combining 20 mL of 7 mmol/L ABTS·+ with 352 µl of a 140 mmol/L potassium persulphate solution. This mixture was allowed to react for 12-16 h at room temperature in darkness. Various concentrations of samples (100 µL) were allowed to react with 100 µL ABTS⋅+ working solution. Absorbance at 734 nm of samples and control was measured in a 96-well microplate in the dark using a Power Wave XS2 (BioTek, Winooski, VT, USA). The %ABTS scavenging effect was determined by the following equation (3): Where A 0 and A t are absorbance of control (the ethanol and ABTS with a working solution) and test sample, respectively.

Preparation of Astaxanthin-loaded Liposome
Liposomes were prepared following the method of [25]. Briefly, phospholipid was dissolved in methanol (2, 3 and 4 % w/v), then astaxanthin (2% w/v) was added in solution and evaporated using evaporator to obtain a film. The dried film was dissolved in methanol and evaporated, then dissolved with 50 ml distilled water, giving a homogeneous suspension of phospholipid. Liposomes were produced using ultrasonic atomizer at an amplitude of 50 and 65 for 15 min. The liposomes were determined for DPPH and ABTS activity as described above.

Sizes and Zeta Potentials of Liposomes
The particle size and zeta potential of the liposomes were acquired by the dynamic light scattering technique using a Zetasizer Nano ZS model (Malvern Instruments, Worcestershire, UK). The liposomes were diluted with distilled water 10 times prior to determination. Measurements were made at least three times, from which a mean diameters ( D43) value±S.D. was calculated.

Confocal Microscopy
The liposomes was added with Nile red (0.1% v/v) and stirred for 1 hr at room temperature. The samples were transferred onto a concave microscopy slide and covered with a coverslip. Images were taken using a confocal laser-scanning microscope (OLYMPUS FV10i-DOC (Tokyo, Japan)) with a 639 magnification oil immersion objective at 543 nm.

Statistical Analysis
One-way analysis of variance (ANOVA) was used to compare treatments. Differences between means were evaluated based on confidence intervals using the Duncan test, with a significance level of p < 0.05. Table 1 shows yields of extract and astaxanthin content from shrimp heads and shells. The yields of extract from fresh shrimp heads, cooked shrimp heads, fresh shrimp shells and cooked shrimp shells were 30.49, 29.50, 15.33, 13.61 mg/g raw material, respectively, while astaxanthin content was 3.64, 2.38, 14.65 and 11.76 mg/g of crude extract, respectively. It was found that shrimp heads gave a higher yield but lower astaxanthin content than shrimp shells. This might be explained by the fact that shrimp heads contain more lipid, which normally come from the hepatopancreas, than the shells [26]. The results are in agreement with [4] who found that the extract from shrimp heads had higher yield but less astaxanthin than shrimp shells. [27] also mentioned that more astaxanthin was found in shrimp shells than other carotenoids. When comparing fresh and cooked material, fresh shrimp shells had the highest astaxanthin content among treatments (p <0.05). Heat affects the degradation of astaxanthin; this can be shown by decrease in astaxanthin from fresh shrimp shells (14.65 mg/g of crude extract) to cooked shrimp shell (11.76 mg/g of crude extract), a reduction of 19.73%. According to a study by [15] showed that thermal processing (microwave, boiling and frying) decreased the amount of astaxanthin compared to fresh material (Pacific white shrimp).   Table 2 shows a summary of polyunsaturated fatty acids (PUFAs), monounsaturated fatty acids (MUFAs) and saturated fatty acids (SFAs) from shrimp waste extracts. The results showed that SFAs were found in a range of 29.78 -32.35% of all fatty acids, whereas MUFAs comprised 14.56 % to 17.07 % and PUFAs comprised 43.04 % to 46.14 %. Linoleic acid, oleic acid and palmitic acid were the three main fatty acids found in the extract, and shrimp heads contained higher amounts of these than shrimp shells. These are major fatty acids found in triglycerides of organisms that can reduce cholesterol and LDL, which cause fatty deposits in the blood vessels [28]. However, the highest EPA and DHA was found in fresh shrimp shells (10.48 and 11.62 respectively). Both have powerful anti-inflammatory functions within the body [29] and also have antioxidant properties [30]. [31] reported that the EPA and DHA content in shrimp waste was 6.71 % and 9.85 %, respectively.

2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid)(ABTS) Radical Scavenging Activity
DPPH and ABTS scavenging assays are frequently used to determine primary antioxidant. The DPPH antioxidant assay relies on the characteristics of DPPH, a stable free radical that contains an odd electron, while the ABTS radical cation is stable for several minutes at room temperature and reacts immediately and quantitatively with several antioxidants over a wide pH range [32].
The antioxidant activity of the four different samples is shown in Table 3. Percent scavenging of DPPH and ABTS were similar; there was very small significant difference (p<0.05) of % scavenging between fresh shrimp shell and fresh shrimp head but cooked shrimp heads showed markedly lower activity (p<0.05). More astaxanthin was found in shrimp shells, (Table 1) while shrimp heads had higher total fat content than shrimp shells by approximately three times (Table 1). Therefore both astaxanthin and some fatty acids, especially EPA and DHA, might contribute to overall antioxidant activity. This is supported by a previous report of [30], which indicated that both EPA and DHA had antioxidant properties. Moreover, astaxanthin contains long, conjugated double bonds which act as antioxitants by scavenging radicals and by quenching singlet oxygen. According to the report of [26], they also found high total lipid in both the cephalothorax (10.5% d.w.) and exoskeleton (3.78% d.w.).

The Physical and Chemical Properties of Astaxanthin-loaded Liposome
Zeta potential reflects the difference in electric potential between a substance containing insoluble, suspended particles (colloid) and the layer of fluid attached to those particles. The measurement of zeta potential is commonly used to predict colloidal system stability [33]. Colloids with high zeta potential (either negative or positive) are more stable, while colloids with zeta potential near zero are more likely to coagulate or flocculate [34]. The results showed that zeta potential of the astaxanthin-loaded liposomes was in the range of -17.05 to -35.75 mV (Table 4). Particles with zeta potential value more negative than -30 mV or more positive than 30 mV have relatively high repulsive interaction and are considered to be stable [35].
Phospholipids contain up to 70% of phosphatidylcholine; the electrostatic charge of phosphatidylcholine is neutral. Therefore, when the amount of phospholipid is increased, the charge will be more neutral. The results are in agreement with [36], who studied the effect of phosphatidylcholine from sunflower oil (50%, 65%, 75% and 90%), and found that the zeta potential reached nearly zero with an increase of the phosphatidylcholine.
Results of the particle size study showed that astaxanthin-loaded liposomes had a diameter ranging from 98.32 to 114.33 nm, as shown in Table 4. As the phospholipid content increased, the size of liposomes significantly increased (p> 0.05) as was also reported by [37]. The phospholipids are an important part of the formation of liposomes; as the amount of phospholipids increases, the particle size increased.
The antioxidant activity of astaxanthin extract and astaxanthin-loaded liposomes is reflected by the percentage of scavenging of DPPH (Table 4). It was found that the percentage of scavenging of DPPH of the astaxanthin extract was 79.36, while the percentage of scavenging of DPPH of the astaxanthin-loaded liposomes was in the range of 68.31 to 79.23. When observing the antioxidant efficacy of astaxanthin after storage in liposomes, it was found that astaxanthin still retains antioxidant efficiency close to that of astaxanthin before storage. Moreover, the amplitude used in generating liposomes did not significantly affect antioxidant activity.
Zeta potential is the potential difference between the dispersion medium and the stationary layer of fluid attached to the dispersed particle. The measurement of zeta potential is commonly used to predict colloidal system stability [33]. While, the colloids with high zeta potential (negative or positive) are electrically stabilized, on the other hand, colloids with low zeta potentials tend to coagulate or flocculate [34]. The results showed that zeta potential of the astaxanthin-loaded liposome was in range -17.05 to -35.75 mV (Table 4). Values are mean ± standard deviation of three different experimental results . Means within columns that share letter, are significantly different (p ˂ 0.05).

Microstructure
The microstructure of the astaxanthin-loaded liposomes was examined by confocal microscopy. The astaxanthin extract can be dyed with Nile red, which appears red as shown in Figure 1. It was found that the liposome particles were spherical shape by forming of phospholipid in liposome. Phospholipids are known as amphipathic, which consists of two parts: polar or water soluble and non-polar or fat soluble [38]. Therefore, when added to water, the water-soluble part of the phospholipid interacts with the water and the oil-like part avoids the water. Afterward, it arrange to form bilayer, which then curls into liposome [39]. The bilayer of liposomes was filled with molecules of astaxanthin that are oil-like and can be encapsulated in the bilayer of the liposome thus the results showed the red part in particle of liposome.

Conclusion
Extract obtained from fresh shrimp shells yielded the highest astaxanthin, EPA and DHA content compared to other treatments, and can contribute to enhanced antioxidant properties. Our results indicated that cooking slightly affected the astaxanthin content and antioxidant activity in fresh shrimp shells but in shrimp heads. In terms of application, astaxanthin-loaded liposomes prepared with a higher concentration of phospholipid generally had a larger particle size and zeta potential. However, all liposomes had spherical shape and were effective in terms of their antioxidant properties. The results of this study could be applied in various food products.


provenance: AgriculturalAndFoodSciences,2019-2020-Agricultural And Food Sciences-2019.jsonl.gz.gz

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MASTITIS , SOMATIC CELL COUNT AND MILK QUALITY : AN OVERVIEW

Mastitis is the economically most important disease in lactating cows and the prevalence under any management condition is considerably high. It causes economic losses due to reduction of both quantity and quality of milk. The groups of microorganisms causing mastitis are categorized as bacteria, fungi, mycoplasma and nocardia. Among the several cow side tests to trace intra-mammary infections (IMI) at early stage, i.e.sub-clinical mastitis (SCM), California Mastitis Test (CMT) is commonly used in which somatic cell count (SCC) is indirectly taken into account. The SCC of milk is an indicator of mammary infections because SCC positively correlates with the severity of infection. The SCC of >200,000 cells/ml is considered to be an indication of IMI. However, SCC in the milk can also vary with some other factors such as breed, age of the cow, stage of lactation, body condition score, etc. A few studies have shown that high SCC in milk affect the composition, organoleptic properties and keeping quality of raw milk and heat treated milk, yoghurts and cheese. One could argue that low SCC milk (sub-clinical mastitis) will not have a significant effect on product quality. But it should be emphasized that the natural infection occurs with various types of microorganisms that can precipitate product defects despite the low SCC. Also, attention must be paid to the bulk tank somatic cell count (BTSCC) rather than individual animal SCC. The quality of raw milk collected from different parts of the country is reported to be low with high bacteria counts mainly due to unhygienic milking and field practices. Milk quality directly influences the income of the small scale milk producers which inturn affects the sustainable dairy production. In Sri Lanka the majority of dairy farmers are small scale producers and they practice minimum milk hygiene practices compared to medium and large scale producers. Therefore, it is essential to make them aware of hygienic milking practices and implement milk quality based payments (MQBP) with added premium and penalties for the existing milk price, with the objective of encouraging clean milk production.

Milk is a complex food with high nutritive value and milk-derived products are one of the main sources of food for the world population. Simultaneously with the continuous growth of the human population of the world, the demand for the food also rapidly increases. About 50% of the world's total milk production is consumed in the form of fresh dairy products and this share will continue to increase to 52% over the next ten years due to rising milk consumption in developing countries. Developing countries consume 68% of fresh dairy products which is expected to increase up to73% over the nextdecade (OECD/FAO, 2018). To meet the increasing demand and to gain the sustainable profit from dairy farms, continuous improvements are being carried out on average farm size and average yield of a cow (Vliegher et al., 2012). However, in a global perspective, the land scarcity is a major constraint for expansion of farm size. As a result, farms tend to be deviated from conventional free range or semiintensive management to more intensive management where farm mechanisation has also been initiated. Several studies have shown that the intensive management is more prone to diseases. Mastitis is the most economically important disease in lactating cows (Tilman et al., 2002) and under any management system the prevalent rate is around 40-50% either in the form of clinical or sub clinical mastitis (SCM). Mastitis is defined as an inflammation of the mammary gland together with physical, chemical and microbiological changes, is characterised by an increase in the number of somatic cells in the milk and by pathological changes in the mammary tissue (International Dairy Federation, 1987). Mastitis has been classified in different ways and one way of classification has been done as clinical and sub-clinical, which is based on the severity of the disease (Alemu et al., 2013). It has also been classified as environmental mastitis and contagious mastitis, furthermore each group has been classified as clinical, subclinical and chronic (Kudi et al., 2009). Even though the clinical mastitis could be easily diagnosed by appearance of clinical signs or abnormalities in milk, the sub-clinical form needs more accurate diagnostic tools (Fragkou et al., 2014). It has been reported that the sub-clinical form is more prevalent (15-40%) than clinical form in any management system (Kudi et al., 2009). Identification of sub-clinical mastitis can be achieved by subjective tests, such as Californian Mastitis Test (CMT) or by the more accurate direct somatic cell count (SCC). Even though direct SCC gives more accurate insight into the severity of the infection, more sophisticated methods are costly while conventional methods are laborious. The SCC varies with many external and internal factors associated with the cow. Many studies have evaluated the relationship between SCC, raw milk quality and processed dairy products. Therefore, the objective of this review is to critically evaluate the studies conducted in relation to mastitis, SCC, and their relationship to milk quality and processed dairy products.

Aetiology and pathogenesis of mastitis
According to the pathogens involved, mastitis has been categorized into four types: bacterial mastitis, mycotic/fungal/algal mastitis, mycoplasmal mastitis and Nocardial mastitis. Bacteria is the main causal pathogen among these groups and around 150 bacterial species have been isolated from infected bovine udders (Shaheen et al., 2016). The bacterial pathogens have been divided into two categories based on the cellular and molecular morphology: Gram-negative species such as Escherichia coli and Klebsiella pneumoniae, and Gram-positive species such as Streptococcus agalactiae, Streptococcus uberis and Staphylococcus aureus ( on the Arruda et al., 2013). Further, based mode of transmission, mastitis can be classified as contagious and environmental mastitis (Alemu et al., 2013). Contagious mastitis is caused by the spread of pathogens from infected to uninfected udder (Smith and Hogan, 2001). Environmental mastitis is caused by the contamination of teat ends from environmental pathogens present in manure, dirt, mud, pools of standing water, feed stuffs and bedding materials (Smith and Hogan, 2008). The bacterial species such as Staphylococcus aureus, Streptococcus agalactiae, Mycoplasma bovis and other mycoplasma species are considered to be contagious type, while Streptococcus uberis, Streptococcus dysgalactiae, Escherichia coli and Klebsiella spp are of environmental origin (Shaheen et al.,2016). The contagious pathogens are the main reason for SCM because they could grow on skin and the teat canal. Environmental pathogens are normally harboured for a short period of infection, with streptococci and coliforms causing 30 and 10 days of infections, respectively. Environmental pathogens mostly cause clinical mastitis and are therefore less likely than subclinical mastitis to become a herd problem (Smith and Hogan, 2008). Non-infectious mastitis can also be seen, caused by trauma or injuries to mammary gland (Smith and Hogan, 2001).
The udder possesses its own anatomical structures and immune mechanisms to prevent and overcome infections. The anatomical structure of teats acts as a physical barrier for invading of pathogens into the teat canal. Teat skin, teat sphincter muscle and keratin plug are included in the first line of defence (Capuco et al., 1992;Lacy-Hulbert and Hillerton, 1995). Keratin layer is secreted by the cells which are lining the teat canal and this substance has a bacteriocidal effect (Lacy-Hulbert and Hillerton, 1995). However, keratin plug disappears before few days of calving and during milking the teat duct is dilated. Therefore, pathogens have a chance to enter into the teat canal and further, abrasions and cracks on teat skin facilitate the action of pathogens (Lacy-Hulbert and Hillerton, 1995). Pathogens may enter into the teat canal within one to two hours after milking when the teat canal is kept open. Bacterial fixation occurs by attaching and colonizing in new tissues (Neijenhuis et al., 2001). Bacteria initially damage the tissues lining the large milk collecting ducts and cisterns and produce virulent factors, which can damage the milk secreting cells. Those damaged cells produce leukocytes attracting substances and therefore, leukocytes are recruited from blood into milk. Those leukocytes have the ability to engulf and destroy bacteria, but if bacteria are not destroyed they continue to multiply and affect entire smaller ducts and alveolar areas (Zhao and Lacasse, 2008)

Somatic cell count (SCC) in milk as an indicator of mastitis
The SCC is an important tool to predict the severity of the intra -mammary infection (IMI). Being a component of milk, SSC can be used to assess the milk quality, monitor herd health for mastitis and to decide milk quality based payment. The milk somatic cells include 75% leucocytes (i.e. neutrophils, macrophages and lymphocytes) and 25% epithelial cells and percentage of leucocytes will vary with infections in mammary tissue and various other factors (Sharma et al.2011). Erythrocytes can be found at concentrations ranging from 0 to 1.51×106/ml (Paape and Weinland, 1988). During the inflammatory period, somatic cells rapidly increase in number. The SCC varies depending on the presence, type and virulence factors of the pathogens (Nolan, 2017). It can also vary with other factors such as age, stage of lactation, parity, production level of the cows and environmental factors (Table 1). Cow milk SCC of >200,000 cells/ml indicates mastitis (International Dairy Federation, 1997;Hillerton, 1999). The SCC is the most common method to identify the IMI more accurately in many dairying countries. Sharma et al.(2011) and Bharti et al. (2017) reported that there was a positive correlation between SCC and parity, which is attributed to epithelial damage and prevailing pathogen with repeated infections. Also, Sharma et al.(2011) and Chegini et al.(2016) reported that SCC is high in the late lactation than the early lactation which has been explained as being due to the dilation of the teat canal. A seasonal variation in SCC has been observed, being higher in cows calved in summer than that of winter (Bharti et al., 2017, andBaul et al., 2011).
The diagnosis of mastitis varies from conventional physical examination to application of modern nano technology based techniques. A comprehensive review on diagnosis of mastitis from laboratory to farm has been published by Ashraf and Imran (2018). Figure 1 illustrates an overview of mastitis diagnostic tests applied in the laboratory and the field.   (2018) Among the direct and indirect techniques that are available for diagnosis of mastitis, indirect methods such as the California Mastitis Test (CMT), Sodium Lauryl Sulphate Test (SLST), Surf Field Mastitis Test (SFMT) and White Side Test (WST) can be used as cow side tests under field conditions (Sharma et al., 2011). The CMT is extensively applied all over the world despite the fact that it is very subjective. In CMT, a reagent containing mainly a detergent is used to coagulate the DNA present in the somatic cell nuclei. On the visual appearance of the gel formation, a CMT score is given and SCC can be indirectly assumed through the given score (Whyte et al., 2005). Table 2 shows the association of CMT score, SCC, and the somatic cell score (SCS).
Accuracy of SCC with mastitis causing pathogens and the threshold level of SCC for mastitis detection is very important since there can be false positive identifications. Pamela and Reniemnn (2002) reported that the sensitivity to detect mastitis at SCC 200,000 cells/ml is varied between 73-89% and when threshold value is increased to 250,000 cells/ml, positive prediction value for subclinical mastitis is also increased. Based on the mastitis causing pathogens, the SCC varies, and contagious pathogens such as Streptococcus agalactiae and Staphylococcus aureus generally cause greater S C C elevation than environmental pathogens (Bharti et al., 2017). Table 3 shows the SCC in milk for different isolated pathogens.  (2002) >5,000,000

Quality of milk in Sri Lanka
In Sri Lanka, the quality of milk is far below the standards of most dairying countries. According to Silva et al. (2016) around 20% of milk collected to milk collecting centres has to be discarded. Several studies that have been carried out in different locations of the country showed exceptionally higher total bacterial counts both in raw milk and also in some p r o c e s s e d m i l k ( D e s h a p r i y a e t a l . , 2 0 0 7 , Abeygunawardena et al.,2017, Sanotharan andDeshapriya, 2018). Abeygunawardena et al. (2017) reported that the poor microbial quality of raw milk in studied areas of Kurunegala District was attributed to the inefficient cleaning and disinfection of udder and utensils coupled with poor concern and negligence of farmers towards appropriate hygienic practices. A higher total viable count and Coliform count have been recorded even in bulk containers (Ranasinghe et al., 2017). Vairamuthu et al. (2010) stated that milk quality of Jaffna district has been drastically affected by the following practices during milking; washing the udder and hands with only water without a detergent, wiping the udder after washing only using hand, and the milking of infected and healthy cows at the same time. They have also found that the total aerobic bacteria and 5 3 coliform counts were 22 x 10 and 47 x 10 CFU, respectively and these values are higher than the acceptable levels. Sanotharan and Deshapriya (2018) reported that the unhygienic milking practices, usage of plastic utensils in milking and time duration between milking to chilling affect the keeping quality of the milk in Ampara District. According to Rahularaj et al. (2019) most of the medium and small scale dairy farmers in Sri Lanka practice machine milking with improper cleaning procedure, which increases the prevalence of the subclinical mastitis and directly affects the milk quality. The high prevalence of subclinical mastitis is a major contributor for poor milk quality (Rahularaj et al., 2019, Gunawardena et al., 2014. The milk collection system is a strong contributor to poor milk quality in Sri Lanka. The number of bacteria remaining in raw milk reaching the processing factory from the small-hold farmers showed a positive trend with the milk holding time in transportation (Weerasinghe et al., 2017). Field practices such as mixing of milk from different chilling centres and long period of storage were identified as major contributing factors for microbial load and acidity level in milk collected in different areas of the country. Weerasinghe et al. (2017) also concluded that 400,000 800,000 6 1 quality of milk is better in the Central Province where the ambient temperature is comparatively low. A dairy value chain study carried out in the Uva Province of Sri Lanka clearly showed that the milk quality directly influences the income of the small scale milk producers, which inturn affects the sustainable dairy production at small scale level. Therefore, the study emphasized the need of milk quality improvement (Wijethilka et al., 2017;Wijethilaka, 2018).

SCC and milk quality
The lacteal secretion, practically free from colostrums, obtained by the complete milking of one or more healthy cows, contains not less than 8.25% of milk solid-non-fat (SNF) and not less than 3.25% milk fat. It is also affected by many animal related and environmental factors (Nobrega and Langoni, 2011). Typical bovine milk contains 87% water and 13% solid as shown in Table 4. Mastitis causes reduction in quantity and quality of milk. Some components in milk such as fat, lactose and protein are decreased while somatic cells, whey protein, free fatty acid and enzymes are increased due to the inflammation (Pyorala, 2003). Table 5 shows the changes in milk components and milk volume due to mastitis. Sharma et al. (2011) reported that the reduction of milk components during mastitis is caused by the reduction of synthesis due to the cellular damages and elevation of some components due to leakage from blood as a result of pathological changes in the underlying tissues. The extent of changes in milk composition is specific for the mastitis causing pathogen. The elevation of free fatty acid level, proteolytic and lipolytic enzymes, and sodium and chloride ions, can cause drastic changes in keeping quality of milk. Table 6 shows the relationships between different SCC ranges and the changes in milk constituents. Coulona et al. (2002) stated that some mastitis causing pathogens alter only specific components of milk and some other pathogens do not alter the milk components. As an example Corynebacterium bovis does not alter the milk composition. Streptococcus dysgalactiae and E. coli significantly increase the protease enzymes (peptone and plasmin) in milk but do not affect fat and protein content.  Ma et al. (2000) reported that protein and fat percentages are higher in mastitis milk than in normal milk. High SCC (849,000 cells/ml) in milk mainly affects the flavour of the milk. During the milk storage and processing, somatic cells release proteases and lipases that react with proteins and fat leading to bitterness and rancidity in milk (Irma et al., 2013). Also the lipases act on the fat globule membrane thereby exposing the milk triglycerides to further degradation by milk lipoprotein lipase. Increased lipolysis leads to increased free fatty acid (FFA) in the milk. Therefore, high FFA in milk leads to the development of rancidity and off flavour during storage (Santos et al., 2003b;Irma et al., 2013). Further, during storage of infected fresh milk in cold condition, casein/true protein ratio is reduced due to the activity of a plasmin enzyme which causes lysis of the major protein, casein.
Lactose concentration is low in infected milk which is a result of the secretary cell damage. Mastitis pathogens severely affect the tight junctions of the secretary cells therefore, low secretion of lactose and changes in osmotic pressure cause low level of water transfer for milk synthesis, which causes low yield in infected cows (Nobrega and Langoni, 2011;Bruckmaier et al., 2004). Ogola et al. (2007) stated that there can be changes in minerals in milk due to mastitis, sodium and chlorine concentrations are increased in infected milk because of the leakage from ruptured mammary cells but calcium concentration is at low level because calcium is incorporated with casein micelles and decreases in casein reduce the calcium concentration. However, changes in major constituents are more prominent and it can vary in a pathogen specific manner as summarised in Table 7.

SCC and Dairy Products
The quality of milk products mainly depends on the composition and quality of the raw milk. High SCC will influence the dairy product quality by affecting keeping quality, flavour, and the structure of the product (Ogola et al., 2007; ). Ma et al., 2000 The impact of S C C on dairy products, including pasteurized or Ultra High Temperature (UHT) milk, yoghurt and cheese are presented in the following paragraphs.

High SCC and heat treated milk quality
Fresh milk is subjected to various levels of heat treatment with the objectives of eliminating milk borne pathogens and extending keeping quality. However, depending on the temperature applied and holding time the effect of heat treatment on milk is varied. Most of t h e n o v e l h e a t t r e a t m e n t m e t h o d s s u c h a s pasteurization, UHT treatment and sterilization can be a p p l i e d t o f r e s h m i l k t o e l i m i n a t e v i a b l e microorganisms, but still the activity of heat stable enzymes remains. The presence of exogenous enzymes is high when there is high SCC in milk. Ma et al. (2000) have observed a higher Acid Degree Value (ADV), an indication of high lipolysis activity and casein hydrolysis leading to reduction in CN/TP ratio in o pasteurised (74C /34S) milk with high SCC (849,000 cells/ml, 2.5% fat) during storage at 5°C for 21 days. Also they have detected poor organoleptic attributes such as bitterness and rancidity that consisted with proteolysis and lipolysis in high SCC milk. Santos et al. (2003a) have also detected reduction in casein percentage in total protein (CN/TP) during the storage time and this reduction is higher in high SCC (376,000 cells/ml) than low SCC (26,000 cells/ml) pasteurized milk stored at 6°C.
Three main parameters such as bacteria in milk, proteolysis and lipolysis are responsible for the off flavour development and reduced shelf life (Santos et al., 2003b In ; Ma et al., 2000). pasteurized unpreserved milk, psychotropic bacterial count (PBC) was 3 increased >10 cfu/ml at 5°C storage on 22 days for high SCC (1,113,000 cells/ml) but PBC was increased 3 >10 cfu/ml at 5°C storage on 26 days for low SCC (26,000 cells/ml) et al., . Plasmin is a (Santos 2003a) proteolytic enzyme which hydrolyses β-casein and αcasein and when this enzyme is elevated in milk even after SCC has decreased, its activity remains ( et Leitner al., et al., antos et al., 2003aLeitner al., et al., antos et al., ). 2006Bugaud 2001; S Plasmin and plasminogen are heat resistant and there fore, the activity is not affected by the High Temperature Short Time (HTST) pasteurized treatment and by UHT treatment. Therefore, during storage of pasteurized and UHT milk, plasmin is still in active form leading to further proteolysis ( et al., Newstead 2006;Prado 2006). Alichanidis (1986) et al., et al. found that inactivation of plasmin was higher in lower temperature (85˚C or below) than the higher temperature (130 or 143˚C) heat treatment and they suggested the reasonas being that in lower temperature, enzyme protein is gradually unfolded and becomes partially denatured. Thereafter, it will be hydrolysed by remaining enzymes in active form, but in high temperature, enzymes quickly unfold to inactive form and thereafter at normal temperature those inactive enzymes gradually refold to active form. Therefore, even though milk is subjected to high temperature heat treatment, enzymes remain active throughout the storage period.

Effect of high SCC on Yoghurt
Yoghurt is a fermented product which includes well known set, blended, and strained yoghurts. A limited number of research show that high SCC had little impact on the properties of the unstrained yoghurt. When yoghurt is produced from high SCC milk, there are no changes in pH, titratable acidity, fat and protein during 30 days of storage at 5°C. Yoghurt produced from milk with low SCC (400,000 cells/ml) could be stored at 5°C for 30 days without any organoleptic changes, but consistency of yoghurt prepared using milk with high SCC (>400,000 cells/ml) was affected on day 20 and the taste was decreased after day 30 (Oliveira et al., 2002). Fernandes et al. (2007) reported that the viscosity and free fatty acids (FFA) in the stirred yoghurt prepared from high SCC (1,943,000 cells/ml) milk was higher than the low SCC (147,000 cell/ml) yoghurt during storage on days 10, 20 and 30. The viscosity, proteolysis and lipolysis were increased and pH was decreased in cold stored yoghurt which was made from milk of SCC 398,000 cells/ml than from milk of 95,000 cells/ml. High FFA level was found in yoghurt made from above 1,150,000 cells/ml (Hachana and Paape, 2012). When yoghurt is produced with high SCC milk (400,000 cells/ml) the yoghurt culture activity is reduced by 35%. But if the milk has been boiled for 2 min or heated at 90°C for 20 min somatic cells will be completely inactivated. However, if the cell count is above 400,000 cells/ml the growth of the yoghurt culture organisms will be inhibited even though the heat treatments are given (Tamime and Robinson, 2004).

Mastitis on Cheese quality
When high SCC milk is used to produce cheese, low cheese yield, inefficiency in yield, improper texture and poor overall organoleptic properties can be seen (Talukder and Ahmed, 2017). High SCC promotes the retention of more moisture in cheese and depending on the type of cheese off-flavour development can be seen (Bobbo et al., 2017). Further, lipolysis and proteolysis can be seen in most types of cheese leading to reduced curd firmness, loss of fat and protein in whey (Talukder and Ahmed, 2017) and influence the rennet coagulation resulting low yield of poor quality cheese (Pirisi et al., 1996).
Similarly, Mazal et al. (2007) have produced Prato cheese from high SCC milk (>600,000 cells/ml) and low SCC milk (<200 cells/ml) and they detected significantly higher total protein and non-protein nitrogen, lower true protein and casein concentrations, and higher proteolysis during ripening, resulting in higher whey protein concentration. Klei et al. (1998) reported that cottage cheese 3 made from high SCC milk (872×10 cell/ml) had higher proteolytic activity resulting in loss of more protein in whey and wash water, higher moisture content in the curd, lower lactose content and lower yield, when c o m p a r e d t o c h e e s e m a d e f r o m l o w S C C 3 (83×10 cell/ml) milk from same Holstein cows whose teats were inoculated experimentally with 1000 cfu of Strep. agalactiae.

Conclusion
The severity of mastitis, intensity of udder damage and effect on milk quality depend on many animal related and environmental factors. In terms of minimising the losses, dry cow management, early detection of sub-clinically infected animals, and application of hygienic milking practices are of utmost importance. Early diagnosis of sub-clinical mastitis can minimize the economic losses due to cost of treatment, milk volume loss, premature culling and milk rejection due to poor hygienic quality parameters at milk reception. Most importantly, indiscriminate use of antibiotics in lactating cows as dry and lactating cow therapies can be minimized if the occurrence of new mastitis cases and spread of existing cases are controlled. Thus, many dairying countries are deviating from more intensive management to semi-intensive/free grazing systems with an aim of improved animal welfare, with genetic improvement for disease resistance, climate smart dairy farming, nature loving dairy farming, use of herbal drugs, etc. Although there are various tests available at laboratory level and as cow side tests the cost per cow is a major concern. SCC is one of the most important and reliable indicators of IMI that can be used to detect SCM, but it is expensive and cumbersome than more conventional way of counting. Therefore, more reliable and cost effective methods must be developed at an affordable cost for small scale farmers. When mammary tissue is damaged from infections, milk fat, lactose and casein concentrations are decreased but total protein concentration is elevated. Milk from infected udder contains an elevated microbial population, somatic cells, and higher concentration of exogenous enzymes. They exert a synergistic deleterious effect on both raw milk and processed dairy products. However, there are only a limited number of studies that have been carried out to show the effect of SCC on processed dairy products. In many studies, experimental inoculation of lactating udder with a specific pathogen showed very high SCC milk and when this milk was used to produce pasteurised milk, yoghurt or cheese those products have shown extremely deleterious effects. Therefore, it could be argued that low SCC milk (sub-clinical mastitis) will not have a significant effect on product quality. But it should be emphasized that the natural infection occurs with various types of microorganisms that can precipitate product defects despite the low SCC. Attention must be paid to the bulk tank somatic cell count (BTSCC) rather than individual animal SCC. In Sri Lanka the majority of dairy farmers are small scale producers and they use minimum milk hygiene practices compared to medium and large scale producers. Therefore, it is essential to make them aware of hygienic milking practices and implement milk quality based payments (MQBP) with added premium and penalties for the existing milk price with the objective to encourage clean milk production. Moreover, there must be institutional emphasis towards research and development, and to disseminate knowledge on dairy science and technology, if Sri Lanka is to be self-sufficient in milk and to have a sustainable dairy production.
A c k n o w l e d g e m e n t : A u t h o r s w i s h t o acknowledge the National Research Council of Sri Lanka (NRC2015-87) for financially supporting a graduate student.


extfieldsofstudy: Mathematics Medicine

text:
Accuracy and Reliability of Infrared Analyzers for Measuring Human Milk Macronutrients in a Milk Bank Setting

ABSTRACT Background Infrared (IR) analysis is an emerging technology that may be a useful tool for milk banks to manage the nutrient variability in donor human milk. Objective To evaluate the accuracy, reliability, and comparability of commercial infrared analyzers for measuring human milk macronutrients in a milk bank setting. Methods Three nonprofit milk banks received blinded test kits of human milk that had been assessed using reference methods. Four infrared instruments were used to measure macronutrients as follows: 1 filtered mid-IR, 2 Fourier-transformed full-spectra mid-IR, and 1 near-IR. Twenty-five unique samples were read concurrently for the accuracy arm. An identical sample was read daily for 1 mo for the reliability arm. Results Values for R2 describing relationships with reference methods for total fat, crude protein, and lactose, were as follows: filtered mid-IR, 0.98, 0.94, and 0.48; Fourier-transformed full-spectra mid-IR, 0.97, 0.93, and 0.36 for instrument 1 and 0.98, 0.98, and 0.31 for instrument 2; and near-IR 0.93, 0.93, and 0.12. There was no significant difference between instruments for crude protein and total fat measurements. There were significant differences in carbohydrate measurements between instruments. For 1 mo of daily measurements in the reliability arm, CVs for filtered mid-IR were ≤4.6%, for Fourier-transformed full spectra mid-IR were ≤1.7%, and for near-IR were ≤5.1%. Conclusions Infrared analysis is an accurate and reliable method for measuring crude protein and total fat in a milk bank setting. Carbohydrate measurements are less accurate and are significantly different between instruments, which will likely lead to differences in derived calorie values.

Introduction
There is significant variability in the macronutrient content of human milk between women at the same stage of lactation, with fat often reported as the most variable macronutrient (1)(2)(3). While macronutrient variability is of limited concern with ad libitum feeding of term infants, it may have a significant impact on preterm infants who are fed enterally at prescribed rates and are at risk for poor growth (4). The American Academy of Pediatrics and the Canadian Pediatric Society recommend that preterm infants who do not have access to their mother's own milk receive pasteurized donor human milk (DHM) from a milk bank due to its protective effect against necrotizing enterocolitis (NEC) (5)(6)(7). Milk banks screen donors serologically and for lifestyle risk factors, pool milk between multiple donors, pasteurize milk, and conduct postpasteurization microbiological tests before dispensing DHM to neonatal intensive care units (NICUs) (8). Three small studies suggest that the fat content of DHM can also be highly variable (3,9,10), which may contribute to the poor growth observed in preterm infants fed DHM (7,11,12).
Knowing the macronutrient content of a donor's milk could improve the ability of milk banks to strategically combine donors to reach nutrient goals for DHM going to vulnerable infants in the NICU. Infrared (IR) analyzers are tools that have been used in the dairy industry to measure the macronutrient content of bovine milk (13). Some milk banks within the Human Milk Banking Association of North America (HMBANA) have adapted IR analyzers for use with human milk. Recently, the US FDA approved the first IR human milk macronutrient test system as a medical device (14). HMBANA milk banks operate as food manufacturers, a role that differs operationally and regulatorily from clinical entities that operate medical devices.
There is a growing body of research that suggests that, with appropriate sample handling, IR analyzers are accurate and reliable for measuring fat and protein in human milk (15)(16)(17)(18)(19)(20)(21)(22)(23); however, the majority of these studies were conducted in laboratory or clinical settings. Therefore, the purpose of this study was to 1) evaluate the accuracy of commercially available IR analyzers for measuring macronutrients in DHM in a milk bank setting; 2) compare results between a variety of IR technologies used at multiple milk banks; and 3) evaluate the reliability of commercially available IR analyzers for measuring macronutrients over 30 d in a milk bank setting.

Methods
This method validation study was classified as non-human subject research and provided an exempt status by the Institutional Review Board at the University of North Carolina Greensboro (UNCG). It was also approved by the HMBANA Research Committee.

Test kit preparation
Human milk test kits were prepared in the laboratory at the University of North Carolina Greensboro (UNCG). De-identified raw human milk used to prepare the kits was received from 3 HMBANA milk banks (NorthernStar Mothers Milk Bank, Calgary, Alberta; Northwest Mothers Milk Bank, Portland, OR; and Mothers' Milk Bank North Texas, Fort Worth, TX) whose donors consent to having their milk used for research purposes. The milk was from 12 unique, approved donors and had been classified as research milk due to various deferral requirements (e.g., donor use of medications). Test kit samples were prepared by thawing milk in a warming oven and shaking water baths, and pooling milk from 1 to 2 donors to reach volumes ranging from 200 to 1800 mL, with higher volumes needed for samples used in the reliability arm. Samples that contained milk from 2 donors used different combinations of donor milks, with the goal of creating a wide range of nutrients within the test kits. Each sample was continuously stirred with a magnet during the process of preparing test kit aliquots to ensure consistency. The test kits consisted of 10 unique calibration samples, with macronutrient values provided to the milk bank for instrument calibration; 25 unique, blinded samples for the accuracy arm of the study; and 30 identical, blinded samples for the reliability arm of the study. All test kits contained the same samples for calibration and the accuracy arm. Because IR instruments use up the sample in the process of analysis and samples cannot be remeasured, large sample volumes were required to create 30 d of identical samples for the reliability arm; therefore, samples for the reliability arm of the study were identical within a milk bank, but different between milk banks. Each sample in the test kit contained sufficient volume to be measured in duplicate. Completed test kits were frozen and shipped overnight on dry ice to participating milk banks and to reference labs. Due to volume limitations, only a subset of the 25 unique test kit samples in the accuracy arm were analyzed by reference methods: crude protein and nonprotein nitrogen (n = 20), total fat (n = 20), and lactose (n = 25).

Milk bank setting 1.
The NorthernStar Mothers Milk Bank (Calgary, Alberta, Canada) has been operating since 2012 and processes approximately 200,000 oz (5,914 L) of DHM annually. Two human milk test kits were sent to the NorthernStar milk bank for testing on a near-IR instrument (Near) (Unity SpectraStar XL, Unity Scientific) and on a filtered mid-IR instrument (FiltMid) (Miris HMA Human Milk Analyzer, Miris). Sample handling processes are summarized in Table 1.

Milk bank setting 2.
The Mothers' Milk Bank of North Texas has been operating since September 2004 and processes approximately 600,000 oz (17,742 L) of DHM annually. One human milk test kit was sent to the North Texas milk bank for testing on a Fourier-transformed full spectra mid-IR instrument (FTMid1) (MilkoScan FT120, FOSS). Due to loss of study calibration samples, calibration was done with in-house calibration samples created by the North Texas milk bank and analyzed by the USDA Federal Milk Market. Sample handling processes are summarized in Table 1.

Milk bank setting 3.
Northwest Mothers Milk Bank has been operating since 2013 and processes approximately 375,000 oz (11,089 L) of DHM annually. One human milk test kit was sent to the Northwest milk bank for testing on a Fourier-transformed full spectra mid-IR instrument (FTMid2) (LactoScope FTA; Perten Instruments). Additionally, Perten Instruments set up a custom channel on the LactoScope to estimate lactose using the calibration curve data, as IR technology does not distinguish between lactose and indigestible carbohydrates. Sample handling processes are summarized in Table 1.

Measurement
Reference methods were used to measure the macronutrients in the test kits as follows. Total nitrogen and nonprotein nitrogen (NPN) were measured by Eurofins using the Kjeldahl method (AOAC 991.20 and AOAC 991.21, respectively) to assess the protein in human milk. Total nitrogen was converted to Crude Protein using a protein conversion factor for milk foods of 6.38 (24,25). True protein was calculated for reference samples as (crude protein − measured NPN). Total fat was measured by the USDA Federal Milk Market using the Mojonnier ether extraction method. Lactose was measured in triplicate at UNCG using AOAC method 2006.06 adapted to run in a 96-well plate. This method uses the enzymes β-galactosidase, galactose mutarose, and βgalactosidase dehydrogenase (K-LACGAR, Megazyme International) to convert lactose to β-d-galactose, which oxides NAD+ to NADH. This enzymatic approach has been reported as accurate with HPLC  (24).

Data analysis
Accuracy for IR instruments was defined based on information published in the Miris HMA Human Milk Analyzer User Manual since this device has been approved for clinical use by the FDA: total fat ±12% of reference methods; crude protein, true protein, and carbohydrates ± 15% of reference methods (31). Coefficients of determination (R 2 ) were calculated to assess relationships with reference methods and analyzer results were plotted as percentage differences from reference methods. Descriptive statistics on macronutrient measurements were computed by analyzer type and differences between analyzers were evaluated using an ANOVA with a Tukey's honest significant difference test for multiple comparisons. Intra-assay CVs were computed to assess the reliability of instruments over 1 mo of replicate measures. Regression analysis was used to probe for significant changes over time. All analysis was conducted with SAS Enterprise Edition 9.4 (SAS Corporation).

Assessment of accuracy to reference methods
According to the reference methods used, the study samples contained the following ranges of macronutrients: total fat 2.52-4.11 g/dL (n = 20), crude protein 1.01-1.96 g/dL (n = 20), true protein 0.70-1.57 g/dL (n = 20), and lactose 5.09-6.79 g/dL(n = 25). Scatter plots of percentage differences between IR measurements and reference methods are presented in Figure 1. There was a high degree of accuracy (±15%) for crude protein measurements across all analyzers, with a small number of samples falling slightly outside the range with the filtered mid-IR (3/20, 15%) and near-IR instruments (1/20, 5%  for fat, suggesting the fat loss may have occurred in kit preparation. When this sample was excluded, the R 2 value for fat was 0.98 on FiltMid.

Comparison of results between analyzers
We did not observe a significant difference between the crude protein or total fat value obtained with different infrared instruments (P > 0.05). There was a significant difference in the carbohydrate measurements obtained between infrared instruments (P < 0.0001) ( Table 2).

Assessment of reliability over 1 mo
Macronutrients measured daily over 1 mo are plotted by IR instrument in Figure 2. The only significant (P < 0.05) time-related trends that we observed were a decline in crude protein in the Fourier-transformed full-spectra mid-IR instrument (LactoScope) (slope = −0.0008 g/d; −0.06% daily change from reference value) and a decline in lactose values in the Near instrument (slope = −0.0147 g/day; −0.22% daily change from reference value). These temporal changes were very small, resulting in approximately 2-6% total change over the course of 30 d. The intra-assay CVs for 1 mo of daily measurements for crude protein, fat, and carbohydrates, respectively, were as follows: FiltMid, 4.2%, 4.6%, and 0.7%; FTMid1, 1.2%, 0.4%, and 0.3%; FTMid2, 0.9%, 1.7%, and 0.8%; Near, 5.1%, 3.0%, and 2.2%.

Discussion
We observed high levels of accuracy in measuring total fat and crude protein in raw human milk across 3 different milk banks using a variety of commercially available infrared technologies, including devices developed specifically for human milk (Miris HMA), and devices developed for the dairy industry (MilkoScan, LactoScope, SpectraStar) and adapted by milk banks to measure human milk. Our findings are in agreement with others that have reported accuracy in measuring total fat and crude protein using near-IR (16,18,21), filtered mid-IR (15,(18)(19)(20)23), and full-spectra mid-IR instruments (17,32), when devices have been calibrated to human milk. Limited studies have been conducted in a milk bank setting (19,23,32,33), and few studies have compared multiple types of infrared technology (18).
IR analyzers can only estimate true protein values using crude protein measurements. The average nonprotein nitrogen composition of our reference samples was 28% (range 20-34%). We found that a 20% reduction in crude protein was appropriate for the filtered mid-IR instrument and that a 30% reduction was needed for the other instruments, suggesting that conversion factors to obtain accurate true protein values may differ by instrument. In contrast to our findings, a few studies have described poor accuracy when using IR technology to measure crude protein and fat in human milk (34)(35)(36). Existing research using infrared analyzers for measuring macronutrients in human milk differs with respect to sample thawing, warming, and homogenization methods, as well as instrument calibration, which may explain differing conclusions (37). We observed significant differences in the accuracy and comparability of carbohydrate measurements across devices. The Fouriertransformed full-spectra mid-IR devices mostly fell into ±15% of the reference values for lactose, while the near-IR and filtered mid-IR devices reported values that were 20-50% higher than reference lactose values. This is likely because, while IR technology measures total carbohydrates and cannot differentiate between lactose and HMOs, the full-spectra instrument calibration equations developed by the milk banks attempts to derive lactose values from total carbohydrate measurements based on known lactose values of the calibration samples. None of the instruments in our study showed strong agreement with reference methods for lactose (R 2 < 0.5). Others have reported low accuracy in measuring lactose in human milk with infrared analysis (15,17,18,32,34).
During approximately 1 month of daily use, we found all IR devices provided consistent results, with small, but statistically significant, temporal changes in some components (in the range of 0.06% to 0.22%); FIGURE 2 Reliability of macronutrient measurements over 1 mo of daily use, by infrared instrument. Each milk bank received a different set of test samples, so macronutrient values between analyzers were not expected to be the same. FiltMid (Miris HMA), FTMid1 (MilkoScan), FTMid2, (LactoScope), and Near (SpectraStar). FiltMid, filtered midinfrared; FTMid, Fourier-transformed full-spectra midinfrared; Near, near infrared; ProCrude, crude protein.
however, these values are not likely to be clinically significant. The small temporal changes we did observe highlight the importance of monitoring instruments daily and recalibrating as needed to identify and respond to potential instrument drifts.
In the current regulatory environment, milk banks operate as food manufacturers, and thus they are subject to the Code of Federal Regulation, Title 21, Food and Drugs (38). Among other things, this regulation requires milk banks to follow Good Manufacturing Practices (part 110) and to maintain clean and accurate equipment (part 110.40).
Our study provides evidence that a variety of infrared analyzers can be used in a milk bank setting to accurately measure crude protein and total fat. Use of these instruments may enable milk banks to strategically pool milk from different donors to reach protein and fat targets for DHM. Significant differences in the measurements and accuracy of lactose between devices may lead to differences in calorie calculations, which is an important area for future research given the nutritional vulnerability of infants receiving DHM.

Limitations
We used a small number of reference samples that did not include more extreme concentrations of fat and protein. This is an important area for future research, including testing cream products that have a higher percentage of total solids, which may impact IR accuracy. We defined accuracy based on thresholds for an instrument that has been approved as a clinical device by the FDA. Different levels of accuracy may be more appropriate for manufacturers of medical foods. There was one outlier for total fat (>30% below reference value) in the filtered mid-IR instrument; this sample was measured multiple times with similar results, suggesting that the error may have occurred during preparation of the test kits, highlighting how important drawing a representative sample is for generating meaningful results. We did not measure total carbohydrates, as we felt lactose was a better indicator of the energy available to an infant; therefore, instruments that measure total carbohydrates may have shown better performance results if they and been assessed against total carbohydrate reference values.

Conclusions
A variety of infrared instruments, including near-IR, filtered mid-IR, and full-spectra mid-IR, can accurately measure crude protein and total fat in a milk bank setting when instruments have been calibrated to human milk and when appropriate sample handling protocols are used. Infrared instruments may be useful tools to help milk banks determine how to combine milk from multiple donors to achieve target fat and protein amounts. Calculations to arrive at true protein measurements may differ between instruments. There are significant differences in carbohydrate measurements between instruments that may lead to differences in calorie values. Research is needed regarding the accuracy of IR devices to derive calorie values for human milk.


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FIELD ADAPTATION OF SWEET POTATO GENOTYPES ENRICHED OF β- CAROTENE, IN THE STATE OF GOIÁS ADAPTAÇÃO NO CAMPO DE GENÓTIPOS DE BATATA-DOCE ENRIQUECIDOS DE β-CAROTENO, NO ESTADO DE GOIÁS

Most sweet potato genotypes marketed in Brazil have white, yellow or cream pulp color with negligible carotenoid contents. The use of beta-carotene rich sweet potato materials may contribute to improve people welfare, especially those at critical nutritional conditions. The yield-related traits and marketable tuber quality of 10 beta-carotene biofortified (or not) sweet potato genotypes were assessed in a Brazilian Cerrado area. Differences for all traits were found, with some materials prevailing. However, four of them (CNPH 1190, CNPH 1206, CNPH 1210 and CNPH 1310) showed good adaptability. CNPH 1210 had the highest yield (52.21 ton ha), 4.28 times higher than the Brazilian sweet potato average yield. CNPH 1210 and CNPH 1310 had the highest tuber numbers and the most preferred mass class for consumers, and therefore, they furnished the best marketable genotypes. Nevertheless, the materials CNPH 1210 and CNPH 1310 (both orange-fleshed sweet potatoes) stood out for tuber market quality. Our results may stimulate organized civil society efforts to improve the production and consumption of beta-carotene-rich sweet potato materials in municipalities in the Brazilian Cerrado.

INTRODUCTION
Sweet potato (Ipomoea batatas L.) (Convolvulaceae) is the fourth most consumed vegetable in Brazil, and the sixth most popular and abundant vegetable in the world (MUSSOLINE; WILKIE, 2016). This plant has relatively low production cost, requires minimal investments in technology, and provides a high financial return. Sweet potato is mainly cultivated by small familiar farmers, such as those located at developing countries, without necessarily using genetically improved varieties (OLIVEIRA et al., 2008). Sweet potato is an important dietary component for populations with food limitation, due to its high nutritional values, including sugars, dietary fibers, vitamins and minerals (SILVA et al., 2010). The leaves have antioxidant activity, suppressing lowdensity lipoprotein oxidation (NAGAI et al., 2011).
Since 2006, Embrapa CNPH (National Center for Vegetable Research) researchers have selected carotenoid-rich (such as ß-carotene) sweet potato materials. This substance is a primary pigment molecule and provitamin A source (MELÉNDEZ-MARTÍNEZ et al., 2007) with high antioxidant capacity by eliminating free radicals, due to conjugated double bonds (FU et al., 2011). This research is part of the Biofortification Project of Embrapa-Biofort (Brazilian Biofortification Program) linked to two international food biofortification programs, the HaverstPlus and the AgroSalud. These programs aim at developing natural foods with nutrient quantities meeting the nutritional needs of the human body (LAURIE et al., 2015). The project also developed rice, beans, corn, cassava, pumpkin and wheat with higher nutrient contents. In 2010, Embrapa CNPH recommended the usage of orange-fleshed sweet potato (Beauregard) in Brazil (variety CNPH 1205, assessed in the present survey), normally used in the United States (VANESBROECK et al., 2008) and registered by the Brazilian Ministry of Agriculture, Livestock and Supply (MAPA, 2016).
In Brazil and Ghana, the most preferred sweet potato varieties have white, yellow or cream flesh (OFORI et al., 2009) with insignificant carotene levels compared to the orange-fleshed ones, with carotene values comparable to those of carrot, the most cited carotene food source (TAKAHATA et al., 1993). Nigerian consumers 724 Field adaptation of sweet potato… PEREIRA, A. I. A. et al. have the same preference (NWANKWO et al., 2014). In China, the four most common sweet potato materials have white, yellow, orange and purple flesh, with different chemical compositions (JUNG et al., 2014). The use of β-carotene enriched materials can help population nutrition, especially those in critical nutritional situation. The purpose of the present study was to compare yield traits and tuber quality of β-carotene biofortified (or not) sweet potato genotypes in a Cerrado Savanna-type environment of Brazil, at Goiás state.

MATERIAL AND METHODS
The experiment consisted of a completely randomized block design with four replications. The treatments were 10 sweet potato genotypes from Embrapa CNPH, kept in Gama, Distrito Federal, Brazil. Sweet potato genotypes are visually separated by their inner and outside color and leaf morphology (Table 1). . The soil, Red Yellow Dystrophic type, was collected before experiment installation at 0 to 0.20 m depth, and presented the following characteristics: pH in water of 6.01; Ca, Mg, K, H+Al of 0.2, 1.8, 0.43, and 5.8 cmol c dm -3 , respectively; P of 0.67 mg dm -3 ; organic matter of 22.2 g kg -1 ; Cu, Fe, Mn, and Zn of 4.3, 79.1, 28.3, and 4.1 mg dm -3 , respectively, and granulometry of 226.2, 209.8, and 564.0 g kg -1 of clay, silt and sand, respectively. Soil preparation consisted of forming 30 cm furrow, spaced 80 cm apart, by using a bedshaper coupled with a rotary hoe. These beds were separated in half each one, forming the furrows with the dimensions described. No plowing was required and only a rotary hoe was used to loose soil and weed elimination The experimentation was held out from November 2015 to April 2016, in a 600 m 2 experimental area, and the propagating material consisted of seed-stems (called seedlings) with six to eight internodes (about 30 centimeter). Each plot had five 4 m furrows, spaced 80 cm between them, and 33 cm between plants (three plants per linear meter). Plots were spaced by one meter.

Materials
The fertilization consisted of a 60-120-90 kg ha -1 of N, P 2 O 5 and K 2 O, respectively, formula with all the phosphorus applied at planting and the N and K 2 O in portions, half at planting time and half at coverage, when seedlings began to sprout (about four to five weeks after grafting). This fertilization formula meets the nutritional requirements of sweet potato types evaluated (biofortified or not) (PHILLIPS et al., 2005).
Seedlings were manually buried using a 40 cm plastic sharpened stick. The stem base was deposited into a hole with half of its length buried (30 cm) and the soil accommodated around the stem. Irrigation was held away by conventional overhead irrigation, and the main cultural treatments to developing sweet potatoes were taken.
The shoot fresh mass (ton ha -1 ) (SFM), shoot dry mass (ton ha -1 ) (SDM), final tuber numbers (n/ha) (FNT), yield (ton ha -1 ) (Y), fresh mass (kg) of five commercial tubers (FM5CR) and dry mass (kg) of five commercial tubers (DM5CR) were determined. Seedlings viability (%) (VIAB) was also measured by the ratio between seedlings planted and surviving plants at harvesting. After harvesting, all tubers were individually categorized according to their mass in seven classes: extra A (between 301 and 400 g), extra B (201 and 300 g), special (151 and 200 g), miscellaneous I (80 and 150 g), miscellaneous II (400 and 800 g), discarded I (below 80 g) and discarded II (above 800 g). This classification is used as standard for tuber commercialization in Brazil, although it is not officially registered.
All data were checked for analysis of variance assumptions. Normality was verified by the Lilliefors test and by visual symmetry of the histogram obtained with the software SAEG (System of Statistical and Genetic Analysis) (RIBEIRO JÚNIOR; MELO, 2008). All yield variables, seedlings viability, and categorization of sweet potato tubers as function of their weight followed normal distribution. After verification of the mean significance (or not) between materials, using ANOVA, sweet potato yield and quality means were compared using the Tukey test at 5% probability level.

DISCUSSION
In general, clear flesh sweet potato clones have higher shoot weight yield than β-caroteneenriched ones. Our results are similar to those reported in Umudike, Abia state, Nigeria (NWANKWO et al., 2014). Sweet potato tubers have undoubtedly higher added value for the food industry and in natura consumption, but shoot is important as food for domesticated animals. Sweet potato leaves and stems have high crude protein content and good digestibility for dairy or beef cattle, as fresh leaves and silage (GONÇALVES et al., 2011;VIANA et al., 2011). In Southeast Asia, sweet potato leaves are consumed as vegetables by the population (NAGAI et al., 2011). Tubers with pale yellow or white flesh are more suitable to manufacture flour or feeding domesticated animals, because they are less sweet than those with purple, reddish or orange flesh clones (MUSSOLINE; WILKIE, 2016).
The high viability of the biofortified genotype CNPH 1210 is important, since this study used manual planting system (seed-stems), what is more rustic, and therefore, more susceptible to plant establishment failures. This material can also be studied for clonal seedlings in tissue cultures similar to the potato seedling production system (Solanum tuberosum L.) (Solanaceae) (HOQUE et al., 1996). Besides, the adaptability and resistance of the CNPH 1210 seedlings should be better investigated because sweet potato planting and production system adopted in many countries worldwide is mechanized.
The yield obtained, 7.45 to 52.21 ton ha -1 for genotypes CNPH 1340 and CNPH 1210, 728 Field adaptation of sweet potato… PEREIRA, A. I. A. et al. respectively, differ from the Brazilian average (11.80 ton ha -1 ) (IBGE, 2016). The genotype CNPH 1340 had a yield similar to that in Nigeria (7 ton ha -1 ) (NWANKWO et al., 2014). The CNPH 1210 material reached four times the Brazilian mean yield, highlighting it as a promising material. Biofortified sweet potato varieties have been used for their productive potential, as the Beauregard cultivar, the main ß-carotene-enriched cultivar produced in the United States (PHILLIPS et al., 2005;VANESBROECK et al., 2008). This information differs from the report that carotenebiofortified genotypes had lower yield than nonbiofortified ones in Vale do Jequitinhonha, Minas Gerais state, Brazil (ANDRADE JUNIOR et al., 2009). This demonstrates the importance of considering the adaptation of ß-carotene-enriched sweet potato materials in other Brazilian regions to define a yield criterion for this harvest. However, the highest genotype CNPH 1210 yield can be an important criterion to farmers increasing their cultivation, supply this product to market, and consequently, the consumption of this material by the population. The tuber numbers can be used to predict the yield potential of a given genotype because a positive correlation between yield and tuber numbers (GASURA et al., 2008;MOTSA et al., 2015). However, the increase in tuber numbers decreases its dry matter content, since the plant may not obtain photoassimilates necessary for all tubers to gain mass. In such cases, the production of a few standard size tubers is preferred instead of many low mass tubers.
In Brazil, for example, no official commercial standard has been established for sweet potato, but the existing classification system considers the demands of large consumer markets (Rio de Janeiro and São Paulo) with tuber mass as a reference. In general, Brazilian consumers prefer smooth and elongated sweet potato tubers, and do not appreciate very large or very small ones. The average preference indicates 12 to 16 cm long, 5 to 8 cm in diameter, and 200 to 400 g of tuber fresh mass. At purchase, the visual aspects influence selecting this product, and the decision on buying fruits and vegetables is based on their appearance (ABBOTT et al., 2015). The materials CNPH 1205, CNPH 1210, CNPH 1310, and CNPH 1362 had high tuber yield classified as miscellaneous and discard. However, these materials can be used for industrial processing because they also present nutritional characteristics of tubers of the commercially desirable classes (CARDOSO et al., 2005). Clones with higher dry mass (such as the non-biofortified genotypes CNPH 1206 and CNPH 1190) have higher sale value for industrial purposes (QUEIROGA et al., 2007).
The Brazilian consumer preference by sweet potatoes with pale flesh and white, pink or purple skin (Filgueira, 2013) has been changed due to the nutritional advantages of ß-carotene-enriched sweet tubers, a substance which benefits humans as a vitamin A precursor (MAIANI et al., 2009). Thus, the consumption of these last sweet potatoes should be encouraged, especially as food for people at nutrition risk in Brazil and other developing countries (SILVA et al., 2010). South African companies, private organizations and human nutrition, public sectors have invested in boosting ßcarotene-enriched sweet potato consumption (LAURIE et al., 2015). This confirms a typical characteristic of sweet potatoes breeding programs in Brazil as found in other tropical regions in the world (VILLAREAL; JO, 1983): the existence of a vast germplasm bank what facilitates finding materials meeting different requirements.

CONCLUSIONS
The yield and qualitative parameters of ßcarotene-enriched (or not) sweet potato genotypes strongly differed from each other.
The non-biofortified genotype CNPH 1206 (white-fleshed) presented the highest shoot fresh and dry mass yield and the CNPH 1310 and CNPH 1210 (both orange-fleshed) the highest tuber number and yield, respectively. CNPH 1210 also showed high tuber numbers with fresh mass classified with highest value in the Brazilian marketplace.
In pragmatic terms, familiar-based farmers can profit from the cultivation of ß-carotene rich, sweet potato materials because this plant requires management with a depressed degree of technology. Our results may stimulate efforts to improving the production and consumption of ß-carotene rich sweet potato materials in more Brazilian regions, such as those where Brazilian Cerrado Savanna-type environments predominates.