Dairy Technology Research Papers - Academia.edu (original) (raw)

The growth of six probiotic commercial strains of lactobacilli was assessed in reconstituted dried whey and buttermilk supplemented with yeast extract, meat peptone, soy peptone, tryptone or casein acid hydrolysate at 0.3%, 0.6% or 1%.... more

The growth of six probiotic commercial strains of lactobacilli was assessed in reconstituted dried whey and buttermilk supplemented with yeast extract, meat peptone, soy peptone, tryptone or casein acid hydrolysate at 0.3%, 0.6% or 1%. The addition of 1% glucose was also tested. Growth and acidification kinetics were determined at 37°C using MRS broth and a commercial culture medium as references. The suitability of whey and buttermilk as cryoprotectants at –20°C and –70°C was also assessed. Whey and buttermilk with 0.3% yeast extract were chosen for the growth of probiotic lactobacilli, since no satisfactory growth was observed without an external nitrogen source, whereas glucose did not improve the growth of any of the strains assayed. In general, buttermilk performed as satisfactorily as the reference media. The effectiveness of these media as cryoprotectants was strain dependent: skimmed milk and whey were the most suitable ones, especially for long-term storage at –20°C. However, at –70°C, no significant differences were observed between the culture media assessed. The use of whey or buttermilk as culture media for the production of probiotic lactic acid bacteria and for their cryopreservation implies a novel use of these low-cost products, offering an alternative way of utilizing the by-products of the dairy industry, helping to minimize their negative impact on the environment.

Dairy farming plays a vital role in the social and economic livelihood of the farmer households and cooperatives in the Cagayan Valley. For the adoption of new technologies such as greening technology in dairy production, profiling of the... more

Dairy farming plays a vital role in the social and economic livelihood of the farmer households and cooperatives in the Cagayan Valley. For the adoption of new technologies such as greening technology in dairy production, profiling of the dairy farm is an important factor in developing the assessment of the viability of the green tech to be adopted by the farmers as a means to increase their productivity and efficiency in farming. By considering this aspect, the study was undertaken in the Cagayan Valley and the respondents were purposively selected. There were four cooperatives that represented the region, while 10 farmer households were also randomly selected. The data was collected using a predesigned interview schedule on-farm/site. Key informant interviews (KII) and focus group discussion (FGD) will be the means of gathering relevant information. The collected data was analysed using basic descriptive statistical methods such as frequency, percentage, proportions, average, and rating. The results indicate that the majority of the dairy farmers in the Cagayan Valley belonged to the aged group, with an average age of 54 and above, with a degree in college, and a high income of up to P15,001-above/monthly, which represents the large and medium-sized families. The majority of dairy farmers had at least 5 years of experience using green technology, and 60% of them had both cattle and carabao as dairy farm animals. The adoption rate of green technology using vermicomposting and using solar panels by both categories of respondents reveals that there is a potential market expansion for the implementation of green technology for the dairy farming industry and for further improvement of the socio-economic status of the farmers and their stakeholders, which may lead to their embracing green tech culture. Adequate research and a contribution from the NGO’s and government in this sector are essential to improve the living conditions of the farmers in Cagayan Valley.

Sucrose was successfully replaced with sweetener blends for the preparation of lassi. Optimisation of the levels of sweeteners added individually or in blends, viz. binary, tertiary and quaternary and finally selection of the best blend... more

Sucrose was successfully replaced with sweetener blends for the preparation of lassi. Optimisation of the levels of sweeteners added individually or in blends, viz. binary, tertiary and quaternary and finally selection of the best blend among them was based on organoleptic assessment. Binary blend aspartame × acesulfame-k scored the highest when compared with the best optimised single sweetener aspartame, tertiary and quaternary blend in lassi and had nonsignificant differences with control in all sensory attributes. It showed maximum synergy in sweetness intensity in comparison to tertiary and quaternary blends. Use of binary blend resulted in 38% reduction of usage level when compared with single sweetener aspartame.

Automatic Milking Systems (AMS) milk cows any time without the need for a human worker to be present. Cows choose when to be milked and detailed data is recorded by the robot which can be accessed remotely by computer or mobile device... more

Automatic Milking Systems (AMS) milk cows any time without the need for a human worker to be present. Cows choose when to be milked and detailed data is recorded by the robot which can be accessed remotely by computer or mobile device meaning farmers can check the health and performance of their herd from a distance. It is claimed that robotic milking improves the working conditions and lifestyle of the dairy farmer, as well as having economic advantages and benefits for cow health and welfare. This paper focuses on the relationship between AMS and the role of the stockperson. Although AMS reduces the need for labour in the milking parlour and in theory creates freedom and flexibility for the farmer, in practice farmers found their work routines changed rather than lessened. Ultimately, the role of the stockperson is still vital in maintaining and improving cow health and welfare when compared to conventional milking routines.

"Excel spreadsheet Build-Heat-Exchanger.xls predicts the microbial spoilage rate, the % nutrient retention, the F value, the Biological index B*, and the Chemical index C*, received by a liquid food after flowing through a heat... more

"Excel spreadsheet Build-Heat-Exchanger.xls predicts the microbial spoilage rate, the % nutrient retention, the F value, the Biological index B*, and the Chemical index C*, received by a liquid food after flowing through a heat exchanger.
The program can also be used to calculate the exact residence time in the heat exchanger holding tube, required to give a liquid food a specified F value. Or to find the best residence times and temperatures to get a particular lower microbial or enzymatic spoilage rate, combined with an optimal % nutrient retention.
A correction factor for residence time distribution is included in the program.
Build-Heat-Exchanger.xls also shows the effects of a reduced food flow in the heat exchanger on the F value, on the microbial spoilage rate, and on the % nutrient retention of a heated liquid food.
A worked example is included in the spreadsheet, showing how to use Build-Heat-Exchanger.xls."

The influence of different levels of inulin on the quality of fat-free yogurt production was investigated. Inulin was added to milk containing 0.1% of milk fat to give inulin levels of 1, 2 and 3%. The experimental yogurts were compared... more

The influence of different levels of inulin on the quality of fat-free yogurt production was investigated. Inulin was added to milk containing 0.1% of milk fat to give inulin levels of 1, 2 and 3%. The experimental yogurts were compared with control yogurt produced from whole milk. The total solids content of milk was standardized to 14% by adding skim milk powder to the experimental yogurt. The chemical composition, pH, titratable acidity, whey separation, consistency, acetaldehyde and volatile fatty acidity contents were determined in the experimental yogurts after 1, 7 and 15 days. Sensory properties of the yogurts were evaluated during storage. The addition of inulin at more than 1% increased whey separation and consistency. Acetaldehyde, pH and titratable acidity were not influenced by addition of inulin. Tyrosine and volatile fatty acidity levels were negatively affected by inulin addition. With respect to the organoleptic quality of yogurt, inulin addition caused a decrease in organoleptic scores: the control yogurt had the highest score, and the lowest score was obtained in yogurt samples containing 3% of inulin. Overall, the yogurt containing 1% of inulin was similar in quality characteristics to control yogurt made with whole milk.

... on Chemical, Biochemical and Nlicrobiological Characteristics of a Traditional Dairy Product in Mediterrean Region: Kes Seval Sevgi Kirdar 1\/Lilk and Dairy Technology Programme, Department of Food Processing, Vocational Higher... more

... on Chemical, Biochemical and Nlicrobiological Characteristics of a Traditional Dairy Product in Mediterrean Region: Kes Seval Sevgi Kirdar 1\/Lilk and Dairy Technology Programme, Department of Food Processing, Vocational Higher Education School, Mehmet Akif Ersoy ...

Soy ice cream is a delicious and nutritious frozen product. Seven varieties of soybean were evaluated for their suitability in the preparation of soy ice cream. Significant differences (p < 0.05) were found between the moisture, protein,... more

Soy ice cream is a delicious and nutritious frozen product. Seven varieties of soybean were evaluated for their suitability in the preparation of soy ice cream. Significant differences (p < 0.05) were found between the moisture, protein, fat and ash contents of ice cream mixes prepared from different soybean varieties. The viscosity of the ice cream mix increased, while specific gravity decreased, after ageing and freezing of the mix. Significant differences (P < 0.05) were observed in the over-run and melt down time of ice cream prepared from different soybean varieties. Soy ice cream prepared from variety PK-472 was rated organoleptically superior t0 other varieties.

Two experimental relations about the effect of the homogenizing pressure P, one on the average fat globule diameter dvs [i.e. 0.6 • log10(P) = C1 - log10(dVS)], and the other on the sedimentation parameter H [i.e. 1.2 • P = C2 -... more

Two experimental relations about the effect of the homogenizing pressure P, one on the average fat globule diameter dvs [i.e. 0.6 • log10(P) = C1 - log10(dVS)], and the other on the sedimentation parameter H [i.e. 1.2 • P = C2 - log10(H)], presented in Walstra et al (2006, p. 285), together with Stokes’ Law v ~ (dvs)^2, lead to a series of practical rules on how to change the homogenizing pressure P in order to increase the creaming time t, to reduce the average fat globule diameter dvs, to reduce the % fat q creamed each day, to reduce the sedimentation parameter H, to increase the total surface area A of all fat globules, and to reduce the fat globule creaming velocity v.
Also a rule is present about the effect of the homogenizing pressure P on the product temperature T.
For a particular homogenizer, and a particular milk fat content (fat % ≤ 20 mass%), these rules are:

  1. P-new = P-old * (t-new / t-old)^0.8333;
  2. t-new = t-old * (P-new / P-old)^1.2;
  3. P-new = P-old * (d-vs,old / d-vs,new)^1.6667;
  4. d-vs,new = d-vs,old * (P-old / P-new)^0.6;
  5. P-new = P-old * (q-old / q-new)^0.8333;
  6. q-new = q-old * (P-old / P-new)^1.2;
  7. P-new = P-old * (H-old / H-new)^0.8333;
  8. H-new = H-old * (P-old / P-new)^1.2;
  9. P-new = P-old * (A-new / A-old)^1.6667;
  10. A-new = A-old * (P-new / P-old)^0.6;
  11. P-new = P-old * (v-old / v-new)^0.8333;
  12. v-new = v-old * (P-old / P-new)^1.2;
  13. ΔT = 0.025 * P;
  14. T-new = T-before + 0.025 * P;
    This Excel spreadsheet HOMCALC 2.0.xls enables rapid calculations with each of the equations above, and this file includes worked examples on each of the “rules”.
    A Help-file at the end of this document explains the theoretical basis of all equations.

Livestock is an integral part of India’s agricultural economy and plays a multifaceted role in providing livelihood support to the rural population. High genetic resources in India provide great opportunities of employment and income.... more

Livestock is an integral part of India’s agricultural economy and plays a multifaceted role in providing livelihood support to the rural population. High genetic resources in India provide great opportunities of employment and income. Small dairy farmers are the backbone of India’s milk production and play important role in positioned highest milk production. Dairy farming in India is an important way for farmers to increase their earnings and access to more nutritious food for their families. Organic dairy farming and integrated farming system supplement all other interventions in enhancing the returns to farmers.

Automatic milking systems (AMS), or milking robots, are becoming widely accepted as a milking technology that reduces labour and increases milk yield. However, reported amount of labour saved, changes in milk yield, and milk quality when... more

Automatic milking systems (AMS), or milking robots, are becoming widely accepted as a milking technology that reduces labour and increases milk yield. However, reported amount of labour saved, changes in milk yield, and milk quality when transitioning to AMS vary widely. The purpose of this study was to document the impact of adopting AMS on farms with regards to reported changes in milking labour management, milk production, milk quality, and participation in dairy herd improvement (DHI) programmes. A survey was conducted across Canada over the phone, online, and in-person. In total, 530 AMS farms were contacted between May 2014 and the end of June 2015. A total of 217 AMS producers participated in the General Survey (Part 1), resulting in a 41% response rate, and 69 of the respondents completed the more detailed follow-up questions (Part 2). On average, after adopting AMS, the number of employees (full-and part-time non-family labour combined) decreased from 2.5 to 2.0, whereas time devoted to milking-related activities decreased by 62% (from 5.2 to 2.0 h/day). Median milking frequency was 3.0 milkings/day and robots were occupied on average 77% of the day. Producers went to fetch cows a median of 2 times/day, with a median of 3 fetch cows or 4% of the herd per robot/day. Farms had a median of 2.5 failed or incomplete milkings/robot per day. Producers reported an increase in milk yield, but little effect on milk quality. Mean milk yield on AMS farms was 32.6 kg/cow day. Median bulk tank somatic cell count was 180 000 cells/ml. Median milk fat on AMS farms was 4.0% and median milk protein was 3.3%. At the time of the survey, 67% of producers were current participants of a DHI programme. Half of the producers who were not DHI participants had stopped participation after adopting AMS. Overall, this study characterized impacts of adopting AMS and may be a useful guide for making this transition.

Practical in Animal Science is the crucial in broadening the students knowledge in side of practice in addition to the theoretical session. This practical session may include the farm management, routine activities in farm, feed... more

Practical in Animal Science is the crucial in broadening the students knowledge in side of practice in addition to the theoretical session. This practical session may include the farm management, routine activities in farm, feed production and etc. This paper will talk about swine production, poultry production, fish farm, and also forage production.

Time-temperature data, collected during pasteurization or sterilization of a food product, can be converted to the F-value (or F0-value), received by the heated product. An F-value is an indication for the safety of the heated food, and... more

Time-temperature data, collected during pasteurization or sterilization of a food product, can be converted to the F-value (or F0-value), received by the heated product.
An F-value is an indication for the safety of the heated food, and for its shelflife.
In the past, calculation of the F-value from food time-temperature data, required tedious work with lethality tables. Excel computer program F-SPOIL.xls converts such time-temperature data (with equal time intervals) directly to lethality factors, and calculates the F-value, the microbial spoilage rate, or the % nutrient retention of the heated food.
4 Worked Examples, attached to the spreadsheet, step-by-step show how to use F-SPOIL.xls: both for liquid foods (Examples 1 and 2) and for solid foods (Examples 4A+B).
The time-temperature input of Worked Example 3 (“Validation”) was taken from a heating process in the literature. Both the lethality factors and the F-value, calculated by F-SPOIL.xls, were exactly equal to those in the literature, calculated with lethality tables. A brief explanation of the concept “lethality factor”, the equation how to calculate it, and a lethality factor example calculation, are included in Worked Example 3.