Factors Associated with Negative Energy Balance and Its Effect on Behavior and Production Performance of Dairy Cows: A Review


INTRODUCTION

Production of optimum milk quantity and quality, with proper udder health and body condition maintenance of dairy animals, is highly desired at any livestock farm (Kumari et al. 2019; Singh et al. 2020a; Singh, 2021). Improved milk yield, quality, and health status of dairy animals are beneficial for every dairy owner (Kansal et al. 2020; Singh et al. 2020b). However, there are many challenges in the successful maintenance of these aspects by the dairy animals (Bhakat et al. 2017a). These challenges include the rising cost of feedstuffs, their availability, cost of health care, rapidly increased cost of labor, metabolic disease treatment like mastitis, milk fever, multi-factorial disease as lameness, employed devices for decision making and to combat against odd weather stress and timely insemination facilities (Caja et al. 2016) at the farm premise. These challenges permanently adhere to a dairy owner. In order to achieve good results, he has to continuously strive for the best practices (Kumari et al. 2020). Studies suggest that adoption of suitable management practices at the farm may help in improving herd health and production performance in terms of both quality and quantity (Kumari et al. 2020; Singh et al. 2020c). In addition to the above-mentioned challenges, one of the major challenges is to manage NEBL in dairy animals during transition and initial lactation period (Berry et al. 2007; Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). The transition and initial lactation phase of dairy animals are remarked with pronounced NEBL (Berry et al. 2007; Butler, 2009). DMI during these phases is comparatively less than other production phases (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). There is a dramatic change in the physiological status of dairy animals when they shift from a non-lactating phase (late dry period) to a lactating phase (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). This physiological shift imposes production stress on the animals when they enter into a production stage (Berry et al. 2007; Butler, 2009). Tremendous shifts in the different hormonal levels have been observed in this period (Ospina et al. 2010; Chapinal et al. 2012). A decrease in DMI implies poor nutrient availability to the animals (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b) which leads to depletion of body reserves of the animals to meet the physiological stress experienced by animals under these phases. Increased NEBL leads to several other productions, reproduction, and health problems (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). Remarkably increased serum NEFA, BHBA, BUN levels are observed during NEBL in dairy animals (Ospina et al. 2010; Chapinal et al. 2012). Timely corrective management strategies before the onset of the production stage of animals are studied to have beneficial effects on the animals (Caja et al. 2016). A management strategy that encourages a reduction in elevated NEFA, BHBA, BUN levels in serum by improved DMI is highly advisable (Spiers et al. 2004; Ospina et al. 2010; Chapinal et al. 2012; McArt et al. 2013). India and several countries around the world are experiencing a high gap between the availability and demand of certain feedstuffs. Published data reveals that India on average is presently facing a deficit of 35% green fodders and 26% dry fodder residues and 41% deficit of different feed ingredients for concentrate mixture (ICAR-DARE-Annual-Report, 2013). The reason behind this issue may be due to the rapid increase in the population of livestock, reduced land availability for fodder cultivation, increased demand for food items by rising human populations which puts competition for resources. With this constraint also, the nutrients available for animals should be assimilated into their body to meet the requirements for different production and other bodily activities. Recent studies suggest that proper nutritional management condition during the dry period onwards reduces the adverse impact of NEBL to a considerable level (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). Following this, optimized behavioral and production performance of dairy animals may be achieved (Drackley and Cardoso, 2014; Van Hoeij et al. 2018; Singh et al. 2020b). Reviews that summarize knowledge based on the latest findings to reduce negative energy balance for improved behavior and production performances of dairy animals are very scanty. This formed the basis of the framing of this review. This manuscript summarizes the knowledge based on the latest findings to reduce negative energy balance for improved behavior and production performances of dairy animals.

 

Methodology for this review

A cohesive and rigorous study of the latest and existing literature has been performed for the drafting of this manuscript. Most of the literature referred were not older than 2010 with an upper limit of 2021 for this manuscript. However, some important and older references were also studied and cited in this review. Most of the literature findings were done in the ICAR-National Library in Dairying of National Dairy Research Institute, Karnal. However, several online platforms such as research gate, google scholar, and publishing organizations such as elsevier, springer nature, sage publication, taylor and francis, willey online, Indian journals, etc. were utilized for studying and drafting this manuscript. This manuscript is sub-divided into an in-depth review of factors associated with NEBL and its effect on the behavioral and production performance of dairy animals. We have not focused on other aspects as reproduction, and other health parameters of dairy animals rather we have concentrated our review on factors associated with NEBL and its consequent effect on behavioral and production performance in dairy animals. However, we have indicated suggestions for other management factors such as housing, diet, and husbandry practices which need to be optimized for desired results.

 

Changes in the metabolic profile of dairy animals during the initial lactation period

Lipolysis rate gets increased than rate of lipogenesis in adipose tissue of animals and the uptake of lipid energy also gets elevated on the onset of lactation. Similarly, the glucose uptake by the animal body exceeds gluconeogenesis in liver of dairy animals. A steady increase in food intake, increased protein mobilization, mineral absorption and mobilization followed by increased capacity and process of digestion occurs in dairy animals. Furthermore, the milk synthesis occurs which causes more utilization of nutrient reserves and blood flow to the mammary system of dairy animals (Ingvartsen and Andersen, 2000; Dann et al. 2005; Berry et al. 2007; Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b; Singh et al. 2020f). The above-mentioned list of changes in metabolic profile of dairy animals is not exhaustive. Nevertheless, this list represents a major important physiological phenomenon for a dairy animal in its initial lactation period.

 

Negative energy balance in dairy animals

Late pregnancy to the initial three weeks for dairy animals has been recognized as one of the most important areas of interest for researchers of animal science. The transition period is commonly understood as the period of 3 weeks before and after calving period (Drackley and Cardoso, 2014) in dairy animals. There is a tremendous change in the hormonal control and the nutritional requirement of the animals during this period (Ospina et al. 2010; Chapinal et al. 2012; McArt et al. 2013). However, this period has been observed with a reduction in DMI by 10-30% in dairy animals (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). During the initial lactation stage, the milk yield and its compositional change occur rapidly for which nutrient requirement by the animals is also elevated (Butler, 2009; Drackley and Cardoso, 2014; Singh et al. 2020b). However, due to depressed DMI during this phase there becomes a gap in the supply and demand of available nutrients and energy levels in the dairy animals (Dann et al. 2005). This situation is termed as a negative energy balance in dairy animals (Dann et al. 2005; Drackley and Cardoso, 2014). NEBL conditions in animals are observed more during the transition and initial 2 months of dairy cows. There is the practical importance of studying negative energy balance of dairy animals to put corrective measures on required time for the animals (Butler, 2009; Drackley and Cardoso, 2014). During prepartum period, the cutoff values for the NEFA ≥0.3 to 0.5 mEq/L and BHBA ≥0.6 to 0.8 mmol/L were taken to indicate adverse performance effects. However, during postpartum period, on the other hand, the cutoff values for NEFA ≥0.7 to 1.0 mEq/L and BHBA 1.0 to 1.4 mmol/L concentrations reflected negative results in different studies (Wankhade et al. 2017). Higher concentrations of both NEFA and BHBA are associated with negative performances in dairy cows. More NEFA concentrations indicate that more body reserves are metabolized in the animals’ body. Higher BHBA levels, on the other hand, reflect more risk of ketosis in dairy cows. Hormones such as insulin-like growth factor (IGF), insulin, oestradiol, growth hormone, cortisol levels were studied by Fenwick et al. (2008). Higher levels of insulin mIU/mL (0.22±0.058 vs. 0.13±0.019), oestradiol pg/mL (2.2±0.33 vs. 1.6±0.24), growth hormone ng/mL (18±8.0 vs. 9±0.7), cortisol nmol/L (13±5.7 vs. 5±1.6) were observed in cows with mild NEBL than in severe NEBL. Fenwick et al. (2008) found that significantly lower IGF-I ng/mL (11±1.1 vs. 51±8.4) and glucose mM (2.7±0.15 vs. 4.1±0.13) in severe NEBL than mild NEBL. Whereas, dairy cows suffering from severe NEBL had significantly higher NEFA and BHBA levels. Moreover, the results of this study suggested that increased IGF may suppress embryo development which may lead to high embryonic mortality in dairy cows.

 

Assessment of energy balance in dairy animals

Different methods of accessing energy status of dairy animals in terms of plasma NEFA, BHBA, glucose, urea, total protein, slaughtered weight, ultrasound techniques, etc. as their concentration changes with change in energy status of dairy animals as proposed by different studies. However, some practical problems exist with these methods. These methods are more applicable for laboratory conditions and can not be easily used in field conditions and they are non-economic as well but they have their respective advantages too. Nevertheless, body condition score (BCS) method can be easily followed and utilized under field conditions (Ospina et al. 2010; Chapinal et al. 2012; Singh and Kumari, 2019). BCS method predicts the relative body fatness of dairy animals based on fat deposition over specific body parts and it has different scales (Singh et al. 2020b). In recent research, Xu et al. (2018) showed that transition period energy balance could be estimated by milk metabolites analysis which may have a role in cell regenerations. They suggested that energy balance estimation may require information on complex net energy consumed from different feed sources, which may be complex and often require a lot of facilities. However, milk constituent estimations may serve for the estimation of energy balance. On other hand, some studies revealed that milk metabolites may be secreted by myo-epithelial cells, damaged SCC, or even from blood (Linzell and Peaker, 1971). Xu et al. (2018) remarked from their study that both the milk constituents and milk metabolites may be utilized for the estimation of energy balance of individual cows. In particular, estimation of glycine, choline, carnitine, and fat yield had been identified as the most important parameters. This methodology had 53% to 88% predicting ability. In addition to it, they also indicated that these metabolites may have a relation with cell renewal.

 

Factors for regulation of DMI in dairy animals

There exists a complex synergism among different factors that control feed intake and so is for DMI by the animals (Butler, 2009; Drackley and Cardoso, 2014). These factors include hormonal changes, metabolites, physiological challenges, internal stimulus, digestive system, and environmental stressors around dairy animals (Ospina et al. 2010; Chapinal et al. 2012; McArt et al. 2013). The above-mentioned factors have their different importance in the regulation of energy balance of dairy animals.

 

Role of blood constituents and metabolites

The last two decades have witnessed an increased interest in the study of blood metabolites which reflects energy balance in dairy animals (Seifi et al. 2007; Singh et al. 2020b; Singh et al. 2020f; Singh et al. 2020g). These metabolites include particularly NEFA, BHBA, and BUN levels in blood serum or plasma (Chapinal et al. 2012). Latest studies suggest that NEFA levels get elevated gradually 2 to 3 weeks before calving till the first month of lactation (Cavestany et al. 2005; LeBlanc et al. 2005; Ospina et al. 2010; Chapinal et al. 2012). Max levels of NEFA are seen during or near calving days (Cavestany et al. 2005; LeBlanc et al. 2005; Ospina et al. 2010; Chapinal et al. 2012). However, under improper management, this NEBL may prolong up to several months leading to adverse production and health performance in dairy animals (Ospina et al. 2010; Chapinal et al. 2012; Singh et al. 2020b; Singh et al. 2020h). Hence, the energy levels during the drying off period in dairy animals form an important management period (Singh, 2019; Singh et al. 2020b). NEFA shows the level of fat mobilization from body reserves as adipose tissues in an attempt to fill the energy gap during NEBL (Ospina et al. 2010; Chapinal et al. 2012; Singh et al. 2020b; Singh et al. 2020f). Researches have shown that elevated NEFA levels are also corroborated with increased risk of fatty liver, displaced abomasum, ketosis, poor udder health status, and reproductive problems in dairy animals (Ospina et al. 2010; Chapinal et al. 2012; Singh et al. 2020b; Singh et al. 2020i). A similar trend of elevated levels of BHBA is observed during transition period than other lactation cycle days of dairy animals (Cavestany et al. 2005; LeBlanc et al. 2005; Ospina et al. 2010; Chapinal et al. 2012). However, postpartum BHBA levels have been reported higher than prepartum days (Cavestany et al. 2005; Seifi et al. 2007) which might be due to the more energy demands of dairy animals with the initiation of production period (Seifi et al. 2007). BUN levels are reported to be lower during the dry period than the lactation period (Seifi et al. 2007; Singh et al. 2020b). The reason behind this phenomenon may be due to increased intake of food by the animals (Cavestany et al. 2005; Seifi et al. 2007). The highest levels of BUN were observed on near to a month of the initial lactation period (Cavestany et al. 2005; Seifi et al. 2007). Protein metabolism is increased during initiation of the lactation period which is reflected by elevated BUN levels in dairy animals (Ingvartsen and Andersen, 2000; Buttchereit et al. 2010). Hence elevated DMI will be helpful to express optimum BUN levels in dairy animals (Ingvartsen and Andersen, 2000; Dann et al. 2005; Berry et al. 2007; Butler, 2009; Buttchereit et al. 2010; Drackley and Cardoso, 2014; Singh et al. 2020b; Singh et al. 2020f). Glucose is considered the primary metabolic driver in animal organs for growth, production, and reproduction in animals (Cavestany et al. 2005; Seifi et al. 2007). Serum glucose levels are depressed during NEBL condition as seen particularly 3 weeks before and after parturition (Seifi et al. 2007; Ingvartsen and Andersen, 2000; Buttchereit et al. 2010). In addition to above mentioned blood metabolite and constituent levels, some studies (Seifi et al. 2007; Nowroozi-Asl et al. 2016) shown that during the transition period blood triglyceride, cholesterol, total protein, and albumin levels decrease near calving and again starts elevating with an increase of days in milk. However, aspartate aminotransferase levels increased with progress of days near calving and lactation period in dairy animals.

 

Hormonal control of DMI

Hormonal control of DMI has been review to the extent of providing basic understanding however, the below-provided list does not highlight reproductive hormones. Stress hormones partially, corticotrophin-releasing hormone is secreted by the paraventricular nuclei of the hypothalamic centers in the brain (Ingvartsen and Andersen, 2000; Buttchereit et al. 2010; Nowroozi-Asl et al. 2016). This mechanism is found to have a minor mediatory effect on feed intake (Ingvartsen and Andersen, 2000). Leptin hormone is released mainly from adipose cells and is directly correlated with adipose content in animals’ bodies (McCann et al. 1992; Maffei et al. 1995; Ingvartsen and Andersen, 2000). Leptin levels are found to increase during pregnancy in animals and gradually decrease near calving period (Chien et al. 1997; Kawai et al. 1997; Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016). Leptin has been associated with appetite regulation and also has a role in drawing nutrients from the maternal system to the fetus for growth and development of organs (Yamada et al. 2003; Nowroozi-Asl et al. 2016). Leptin has a role in body weight regulation and fat deposition in the adipose tissue in animal body (Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016). Ghrelin (GH) hormone has a great influence on the regulation of gastrointestinal activities, regulation of gastric and pancreatic secretion, cell growth; lipid metabolism, cardiovascular activities and immunity levels in animals are also affected by the action of ghrelin (Ingvartsen and Andersen, 2000; DeVriese et al. 2008; Börner et al. 2013; Nowroozi-Asl et al. 2016). Thyroid hormones have a role in energy metabolism (Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016). Increased insulin levels have been shown to decrease feed intake and hence lower DMI (Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016) in animals. There has been a positive correlation of insulin levels with DMI in dairy animals (Riedy et al. 1995; Ingvartsen and Andersen, 2000; Hosseini et al. 2015; Kawashima et al. 2016; Nowroozi-Asl et al. 2016; Li et al. 2017). In nutshell, it may be affirmed that elevated insulin levels may have long-term effect on DMI in dairy animals thereby affecting the whole metabolic and condition of body of animals (Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016). Elevated glucagon levels may have an indirect role in the depression of DMI in animals (Meeran et al. 1999; Ingvartsen and Andersen, 2000; Habegger et al. 2010; Li et al. 2017). Cholecystokinin (CCK) is secreted from the duodenum and jejunum of animal gut region and produces satiety signals in central nervous system in animal’s body (Riedy et al. 1995; Ingvartsen and Andersen, 2000). However, Somatostatin is released from both brain and gut of animals (Ingvartsen and Andersen, 2000; Stengel and Taché, 2013; Nowroozi-Asl et al. 2016). It has similar action of reducing feed intake in animals on elevated levels (Ingvartsen and Andersen, 2000; Nowroozi-Asl et al. 2016). An illustration of hormonal control on the regulation of DMI in dairy animals is presented in Figure 1.

 

Environmental factors associated with DMI

Climatic conditions and housing facilities

Several published data revealed that the earth’s mean temperature has increased by 0.2 ˚C per decade (IPCC, 2007) and is expected to rise by 2 to 5 ˚C by the year 2100 (IPCC, 2007; Das et al. 2016). Developing countries would be more at risk of increasing temperature as their economy is largely dependent upon agriculture (Silanikove and Koluman, 2015). Thermo-neutral zone for dairy animals has been suggested to be 16 ˚C to 25 ˚C (Das et al. 2016) to maintain their proper physiology. When air temperature goes beyond 30 ˚C, a sharp decline in DMI is noticed, and when the temperature raises up to 40 ˚C a depression of 40% DMI is observed (Hooda and Singh, 2010; Hamzaoui et al. 2012; Rhoads et al. 2013). As a result of which the dairy animals may suffer NEBL and correspondingly the body weight and body condition of animals may go down to unwanted levels (Lacetera et al. 1996; Das et al. 2016). In response to such climatic stress, an increase in the maintenance requirement of up to 30% of the animal may be observed (NRC, 2007). Additionally, the milk yield gets sharply lowered as a result of NEBL (Aggarwal and Singh, 2008; Upadhyay et al. 2009; Aggarwal and Upadhyay, 2013). Housing facilities that promote a comfortable thermal-humidity index (65-72) in addition to proper ventilation, animal comfort, lower microbial load, etc. should be given preference for dairy animals (Singh et al. 2020c). Studies suggest that a temperature humidity index (THI) 78 from THI 68 leads to a reduction in DMI by 21% and consequently milk loss of 9.6% (Bouraoui et al. 2002). More severe DMI and milk losses can be observed under higher THI. Furthermore, the tropical climate offers a harsh environment for dairy animals (Singh et al. 2020c) hence housing modifications such as roof thatched or insulated (Sahu et al. 2019; Singh et al. 2020c) for improved thermal comfort (Sahu et al. 2019; Singh et al. 2020c), soft bedding such as sand and composted bedding should be adopted to achieve improved results in terms of more DMI, water intake, and milk yield (Singh et al. 2020c; Singh et al. 2020d; Singh et al. 2020e).

 

Diet regime for dairy cows

Management practice that may lower the blood NEFA near calving would be effective to decrease the risk for production loss and health problems (Ospina et al. 2010; Chapinal et al. 2011; Janovick et al. 2011; Chapinal et al. 2012). The suggested cut-off value of NEFA was ≥0.5 mEq/L for predicting a reduction in milk yield and other health problems (Chapinal et al. 2011). Dry matter intake and serum NEFA concentrations normally have an inverse relationship (Overton and Waldron, 2004; Drackley et al. 2005; Singh et al. 2020b). A dry period diet is one of the critical factors which have far-reaching effects on lactation and other health parameters (Drackley et al. 2005; Berry et al. 2007; Singh et al. 2020b). A feeding regimen that offers high forage diet during far off dry period and a comparatively energy denser diet during close up dry period is suitable feeding management practice to reduce NEBL and consequently improved milk performance, udder health status, and body condition of dairy cows (Drackley et al. 2005; Chapinal et al. 2011; Chapinal et al. 2012; Singh et al. 2020b). This type of feeding regime encourages more DMI during the transition period (Beever, 2006; Berry et al. 2007; Butler, 2009; Roche et al. 2013; Drackley and Cardoso, 2014; Roche et al. 2016; Singh et al. 2020b). In an interesting study (Senturk et al. 2015), it was found that tannin containing herbal supplementation (Chebracho tannin) during transition period may have protective effects in dairy cows from ketosis and NEBL as showed by lower BHBA levels. In addition, improvement in gut health was observed in a supplemented group in terms of improved stool score and fecal structure without having negative effects on feed intake.

 

Figure 1 Hormonal control of regulation of DMI in dairy animals

 

In an investigation (Garcia et al. 2011) , it was concluded that 250 g/cow/d protected fatty acid supplementation during the transition period may increase milk yield but it may have adverse effects on BHBA and NEFA levels indicating more NEBL. On the other hand, 300 mL propylene glycol supplementation in another group on an alternate day basis for 30 days postpartum may have Hepato protective effect.

 

Husbandry practices

A positive emotional state of the animal leads to better animal welfare (Green and Mellor, 2011; Mellor, 2012) whereas prolonged stress conditions in animals may lead to anhedonia (Yalcin et al. 2014; Rizvi et al. 2016; Lecorps et al. 2019). The latter condition has a drastic negative impact on animal health and production performance of dairy animals (Lecorps et al. 2019). In order to eliminate such negative emotional problems in dairy animals, expert and gentle handling of animals should be encouraged at the farm for desired results (Novak et al. 2016; Lecorps et al. 2019). Micro-behavior expressions have practical utility to judge and predict the emotional state of animals (Weary et al. 2017). Motivational stimulus which changes the emotional state of animals includes thirst, hunger, drive for energy-dense food, pain, sensations, sleep and body temperature of animals (Denton et al. 2009; Mellor, 2012). However, external stimulus, especially the handling process has a great influence on animal behavior in terms of positive or negative emotion (Green and Mellor, 2011).

 

Energy balance and production performance of dairy animals

High-producing dairy animals have been developed by a continuous selection of superior germplasm to meet high demand for dairy products (Capper et al. 2009; Caja et al. 2016). However, the high-producing animals are more prone to NEBL. Several studies (Berry et al. 2007; Buttchereit et al. 2010; Buttchereit et al. 2011; Drackley and Cardoso, 2014; Singh et al. 2020b; Singh et al. 2020f) explained that DMI has a high influence on energy balance of dairy animals. Improved DMI has shown reduced NEBL in dairy animals (Singh et al. 2020b; Singh et al. 2020f). However, over and under-conditioned body conditions of dairy animals should be avoided (Heuer et al. 2001; Reist et al. 2002; Singh et al. 2015; Singh et al. 2020b) and management practices should be driven to achieve the optimum range of BCS (Paul et al. 2018; Singh et al. 2020b). Improved energy balance in dairy animals has shown significantly increased milk yield (Roche, 2007; Buttchereit et al. 2010; Buttchereit et al. 2011; Drackley and Cardoso, 2014; Singh et al. 2020b; Singh et al. 2020f). Improved body conditions have shown improved milk flow for dairy animals (Ryan et al. 2003; Reis et al. 2012; Mohammed et al. 2015; Singh et al. 2015; Singh et al. 2020b). Transition period is remarked with lowered immunity status of animals and more NEBL elevated the risk of intramammary infections (Reis et al. 2012; Bhakat et al. 2017a; Singh et al. 2020b). As a result of severe immune-suppression of the mammary system of dairy animals, poor udder health status in terms of increased somatic cell count (SCC), more modified California mastitis test values, elevated pH, and electrical conductivity (EC) in the milk samples of animals are observed (Batavani et al. 2007; Buttchereit et al. 2011; Gumen et al. 2011; Malek dos Reis et al. 2011; Bharti et al. 2015; Boas et al. 2017; Bhakat et al. 2017b; Smith et al. 2017; Alhussien and Dang, 2018; Singh et al. 2020b). Primiparous animals are more at the risk of udder health and reproductive problems as they do not have a fully grown mammary system and proper energy and nutrients are required for the proliferation and maturation of alveolar ducts to make them able to produce quality milk (Bachman and Schairer, 2003; Pezeshki et al. 2007). Several studies (Busato et al. 2002; Lake et al. 2006; Singh et al. 2020b) suggest that animals under reduced NEBL showed no changes in milk composition. Restriction of energy supply to the dairy cows during the transition period leads to lower down the energy balance which is reflected by significantly lower body weight and BCS among other production-related parameters (Janovick et al. 2011; Contreras et al. 2016; Esposito et al. 2020). In a recent study (Esposito et al. 2020) it was speculated that the degree of BCS loss may be independent of milk production levels. They found similar DMI among the restricted and non energy restricted diet groups. They proposed that BCS loss is independent of milk production level upon energy intake than DMI. Furthermore, they remarked that intensity and span of lipid mobilization may affect milk fat% in NEBL (Knegsel et al. 2007; Mann et al. 2015; Esposito et al. 2020). Higher fat:protein ratio has been associated with restricted energy supply as revealed by higher NEFA levels than in the case of unrestricted diet (Mann et al. 2015; Esposito et al. 2020). Cholesterol levels have been suggested to be an indicator for the energy and health status of dairy cows during the transition period (Quiroz-Rocha et al. 2009; Esposito et al. 2020). In addition, it was suggested that cholesterol concentrations may be a reliable prediction of NEBL and health status of cows (Kim and Suh, 2003; Sepulveda-Varas et al. 2015). In their study Esposito et al. (2020), a significant and positive correlation between total cholesterol levels and body temperature was observed. From here, it may be assumed that relationship of different body part’s temperatures with total cholesterol levels may be explored further for more understanding about management of cows from entering into lower cholesterol levels. Esposito et al. (2020) inferred from their study that restricted energy intake during transition cow adversely affects NEFA levels, energy balance, immune response, and poor reproductive health.

 

Energy balance and behaviors in dairy animals

Under grazing conditions, dairy cows were shown to show lower grazing activities during the first week of initial lactation (Chilibroste et al. 2007; Chilibroste et al. 2012). Primiparous cows were found to have more difficulty in fulfilling their DMI through grazing during the first 3 months of lactation period. Gilmore et al. (2011) found that there was no diet effect on cows for oestrus behaviors that included sniffing, attempting mount on other cows, sexual active group participation by oestrus cows, and also on standing mounting conditions. Itle et al. (2015) Investigated that primiparous cows had more standing bouts and shorter average standing bout durations than multiparous cows during the transition period under ketosis conditions. However, cows are found to show more and longer-standing bouts (Jensen, 2012) expressing distress on the day of calving. Moreover, in a review Von Keyserlingk and Weary (2010) stated that standing patterns in dairy animals depend upon the condition of feed, its delivery pattern, and milking. In a recent finding Kaufman et al. (2016) investigated that during the transition period, the subclinical ketosis cows showed decreased lying time, increased frequency, and decreased lying bouts expressing discomfort in cows in NEBL. However, Steensels et al. (2012) suggested that lying behavior may be influenced by body weight of dairy animals. Kaufman et al. (2016) suggested that decreased lying time may also be attributed to more feeding time to cope with production needs. Maltz et al. (2013) reported that there was no difference in intake 24 h, eating and lying or standing ruminating time, drinking time, meal duration, and size for dairy animals under different groups in different energy balance during the early lactation period. However, some studies (Gencoglu et al. 2010; Singh et al. 2020b) found enhanced DMI under treatment group animals during transition period. NEBL cows showed decreased visits and meals, steps, and motion index per day during the transition period (Van Hoeij et al. 2018). However, good metabolic profiled cows showed improved DMI during tranition period (Van Hoeij et al. 2018; Singh et al. 2020b). Moore and Devries (2020) found that cows shift their feed selecting behavior against induced NEBL and its extent was associated with the intensity of NEBL. They found that long straw (10.2 cm screened) group cows budgeted more time on eating than small straw (2.54 cm screened) group animals. In connection with this, researchers (Beauchemin and Yang, 2005; DeVries et al. 2008) found that cows alter their feed selection behavior for small or larger particles in order to maintain their rumen pH and the selection of long fibrous particles help them to cope up with adverse effects of low pH in rumen. DeVries et al. (2011) showed that cows may choose to have diet which may help in increasing their nutrient intake in response to NEBL. Azizi et al. (2009) remarked that cows with greater yields invested more time in eating, more daily DMI than lower producing cows. Some studies (Miller-Cushon and DeVries, 2017; Grant and Ferraretto, 2018) showed that feed selection and time is taken for eating one meal get improved when dairy cows are offered long fibrous fodder particles. This may help them in combating NEBL. Longer feed particle size, more neutral detergent fiber (NDF) content in fodder, and more roughage inclusion in diet lead to longer eating time in dairy cows (Soita et al. 2000; Yang and Beauchemin, 2006; Alamouti et al. 2014; Jiang et al. 2017). Furthermore, Jiang et al. (2018) remarked that the sorting activity of cows gets reduced concerning reduction in forage particle size. Higher milk fat % has been associated with less sorting against longer dietary particle size (DeVries et al. 2011; Fish and DeVries, 2012; Miller-Cushon and DeVries, 2017). Less sorting against small particles resulted in higher reticulo-rumen pH values than another comparable group, finally leading to higher fat %. It may be inferred from the above discussion that selection of fodder particles may be associated with altered feed selection behavior in response with cope with severe NEBL.

 

CONCLUSION

Different factors are attributed towards NEBL of dairy cows during different stages of animals especially during the transition and initial lactation period and also when the dairy animals are exposed to heat stress. The factors associated with reduced DMI leading to NEBL in dairy animals include hormonal control, diet, housing, husbandry practices. NEBL depresses milk yield and comfort behavior of dairy animals especially during the transition and dry period. Positive emotions of dairy animals during these phases are also anticipated to improve the production and behaviors of dairy animals. Increased forage diet with lower energy diet during far off dry period followed by comparatively denser diet during close up dry period improves metabolic profile thereby improving DMI, production, and behavior of dairy animals. Moreover, studies on the handling of animals during the transition phase on production and behavior in consequent lactation period will add up to the existing knowledge and help in a better understanding biological phenomenon in dairy animals during NEBL.

 

ACKNOWLEDGEMENT

Authors are thankful towards the library and other facilities provided by Director, ICAR-National Dairy Research Institute, Karnal for the completion of this study.

Aggarwal A. and Singh M. (2008). Changes in skin and rectal temperature in lactating buffaloes provided with showers and wallowing during hot-dry season. Trop. Anim. Health Prod. 40, 223-228.
Aggarwal A. and Upadhyay R. (2013). Heat Stress and Animal Productivity. Springer, New York, USA.
Alamouti A.A., Alikhani G.R., Ghorbani A.T. and Bagheri M. (2014). Response of early-lactation Holstein cows to partial replacement of neutral detergent soluble fibre for starch in diets varying in forage particle size. Livest. Sci. 160, 60-68.
Alhussien M.N. and Dang A.K. (2018). Milk somatic cells, factors influencing their release, future prospects and practical utility in dairy animals: An overview. Vet. World. 11, 562-577.
Azizi O., Kaufmann O. and Hasselmann L. (2009). Relationship between feeding behavior and feed intake of dairy cows depending on their parity and milk yield. Livest. Sci. 122, 156-161.
Bachman K.C. and Schairer M.L. (2003). Invited review: Bovine studies on optimal lengths of dry periods. J. Dairy Sci. 86, 3027-3037.
Batavani R.A., Asri S. and Naebzadeh H. (2007). The effect of Subclinical mastitis on milk composition in dairy cows. Iranian J. Vet. Res. 8(3), 205-211.
Beauchemin K.A. and Yang W.Z. (2005). Effects of physically effective fiber on intake, chewing activity, and ruminal acidosis for dairy cows fed diets based on corn silage. J. Dairy Sci. 88, 2117-2129.
Beever D.E. (2006). The impact of controlled nutrition during the dry period on dairy cow health, fertility and performance. Anim. Reprod. Sci. 96, 212-226.
Berry D.P., Macdonald K.A., Stafford K., Matthews L. and Roche J.R. (2007). Associations between body condition score, body weight and somatic cell count and clinical mastitis in seasonally calving dairy cattle. J. Dairy Sci. 90, 637-648.
Bhakat C., Chatterjee A., Mandal D.K., Karunakaran M., Mandal A., Garai S. and Dutta T.K. (2017a). Milking management practices and IMI in Jersey crossbred cows in changing scenario. Indian J. Anim. Sci. 87(4), 95-100.
Bhakat C., Chatterjee A., Mandal A., Mandal D.K., Karunakaran M. and Dutta T.K. (2017b). Effect of cleanliness and hygiene on occurrence of mastitis in crossbred cows in WB. Life Sci. Int. Res. J. 4(1), 10-14.
Bharti P., Bhakat C., Ghosh M.K., Dutta T.K. and Das R. (2015). Relationship among intramammary infection and raw milk parameters in Jersey crossbred cows under hot-humid climate. J. Anim. Res. 5(2), 317-320.
Boas D.F.V., Filho A.E.V., Pereira M.A., Junior L.C.R. and Faro L.E. (2017). Association between electrical conductivity and milk production traits in dairy Gyr cows. J. Appl. Anim. Res. 45, 227-233.
Börner S., Derno M., Hacke S., Kautzsch U., Schäff C., Thanthan S., Kuwayama H., Hammon H.M., Röntgen M., Weikard R., Kühn C., Tuchscherer A. and Kuhla B. (2013). Plasma ghrelin is positively associated with body fat, liver fat and milk fat content but not with feed intake of dairy cows after parturition. J. Endocrinol. 216(2), 217-229.
Bouraoui R., Lahmar M., Majdoub A., Djemali M. and Belyea R. (2002). The relationship of temperature-humidity index with milk production of dairy cows in a Mediterranean climate. Anim. Res. 51(6), 479-491.
Busato A., Faissler D., Kupfer U. and Blum J.W. (2002). Body condition scores in dairy cows: Associations with metabolic and endocrine changes in healthy dairy cows. J. Vet. Med. A. 49(9), 455-460.
Butler W.R. (2009). Energy balance relationships with follicular development, ovulation and fertility in postpartum dairy cows. Livest. Prod. Sci. 83, 211-218.
Buttchereit N., Stamer E., Junge W. and Thaller G. (2010). Evaluation of five lactation curve models fitted for fat-protein ratio of milk and daily energy balance. J. Dairy Sci. 93, 1702-1712.
Buttchereit N., Stamer E., Junge W. and Thaller G. (2011). Short communication: Genetic relationships among daily energy balance, feed intake, body condition score, and fat to protein ratio of milk in dairy cows. J. Dairy Sci. 94, 1586-1591.
Caja G., Castro-Costa A. and Knight C.H. (2016). Engineering to support wellbeing of dairy animals. J. Dairy Res. 83, 136-147.
Capper J.L., Cady R.A. and Bauman D.E. (2009). The environmental impact of dairy production: 1944 compared with 2007. J. Anim. Sci. 87, 2160-2167.
Cavestany D., Blanch J.E., Kulcsar M., Uriarte G., Chilibroste P., Meikle A., Febel H., Ferraris A. and Krall E. (2005). Studies of the transition cow under a pasture-based milk production system: metabolic profiles. J. Vet. Med. A. 52, 1-7.
Chapinal N., Carson M., Duffield T.F., Capel M., Godden S., Overton M., Santos J.E. and LeBlanc S.J. (2011). The association of serum metabolites with clinical disease during the transition period. J. Dairy Sci. 94(10), 4897-4903.
Chapinal N., Carson M.E., LeBlanc S.J., Leslie K.E., Godden S., Capel M., Santos J.E., Overton M.W. and Duffield T.F. (2012). The association of serum metabolites in the transition period with milk production and early-lactation reproductive performance. J. Dairy Sci. 95(3), 1301-1309.
Chien E.K., Hara M., Rouard M., Yano H., Philippe M., Polonsky K.S. andBell G.I. (1997). Increase in serum leptin and uterine leptin receptormessengerRNAlevels during pregnancy in rats. Biochem. Biophys. Res. Commun. 2237, 476-480.
Chilibroste P., Soca P., Mattiauda D.A., Bentancur O. and Robinson P.H. (2007). Short term fasting as a tool to design effective grazing strategies for lactating dairy cattle: a review. Australian J. Agric. Res. 47, 1075-1084.
Chilibrostea P., Mattiaudaa D.A., Bentancurb O., Socaa P. andMeiklec A. (2012). Effect of herbage allowance on grazing behavior and productive performance of early lactation primiparous Holstein cows. Anim. Feed Sci. Technol. 173, 201- 209.
Contreras G., Thelen K., Schmidt S.E., Strieder-Barboza C., Preseault C.L., Raphael W., Kiupel M., Caron J. and Lock A.L. (2016). Adipose tissue remodeling in late-lactation dairy cows during feed-restriction-induced negative energy balance. J. Dairy Sci. 99(12), 10009-10021.
Dann H.M., Morin D.E., Bollero G.A., Murphy M.R. and Drackley J.K. (2005). Prepartum intake, postpartum induction of ketosis, and periparturient disorders affect the metabolic status of dairy cows. J. Dairy Sci. 88(9), 3249-3264.
Das R., Sailo L., Verma N., Bharti P., Saikia J., Imtiwati I. and Kumar R. (2016). Impact of heat stress on health and performance of dairy animals: A review. Vet. World. 9(3), 260-268.
Denton D.A., McKinley M.J., Farrell M. and Egan G.F. (2009). The role of primordial emotions in the evolutionary origin of consciousness. Conscious. Cogn. 18, 500-514.
DeVries T.J., Dohme F. and Beauchemin K.A. (2008). Repeated ruminal acidosis challenges in lactating dairy cows at high and low risk for developing acidosis: Feed sorting. J. Dairy Sci. 91, 3958-3967.
DeVries T.J., Holtshausen L., Oba M. and Beauchemin K.A. (2011). Effect of parity and stage of lactation on feed sorting behavior of lactating dairy cows. J. Dairy Sci. 94, 4039-4045.
DeVriese C. and Delporte C. (2008). Ghrelin: A new peptide regulating growth hormone release and food intake. Int. J. Biochem. Cell. Biol. 40, 1420-1424.
Drackley J.K. and Cardoso F.C. (2014). Prepartum and postpartum nutritional management to optimize fertility in high-yielding dairy cows in confined TMR systems. Animal. 8(1), 5-14.
Drackley J.K., Dann H.M., Douglas G.N., Guretzky N.A.J., Litherland N.B., Underwood J.P. and Loor J.J. (2005). Physiological and pathological adaptations in dairy cows that may increase suseptibility to periparturient diseases and disorders. Italian J. Anim. Sci. 4(4), 323-344.
Esposito G., Raffrenato E., Lukamba S.D., Adnane M., Irons P.C., Cormican P., Tasara T. and Chapwanya A. (2020). Characterization of metabolic and inflammatory profiles of transition dairy cows fed an energy-restricted diet. J. Anim. Sci. 98(1), 1-15.
Fenwick M.A., Llewellyn S., Fitzpatrick R., Kenny D.A., Murphy J.J., Patton J. and Wathes D.C. (2008). Negative energy balance in dairy cows is associated with specific changes in IGF-binding protein expression in the oviduct. Reproduction. 135(1), 63-75.
Fish J.A. and DeVries T.J. (2012). Short communication: Varying dietary dry matter concentration through water addition: Effect on nutrient intake and sorting of dairy cows in late lactation. J. Dairy Sci. 95, 850-855.
Garcia A.M.B., Cardoso F.C., Diego X.T. and Gonzalez F.H.D. (2011). Metabolic evaluation of dairy cows submitted to three different strategies to decrease the effects of negative energy balance in early postpartum. Pesq. Vet. Bras. 31(1), 11-17.
Gencoglu H., Shaver R.D., Steinberg W., Ensink J., Ferraretto L.F., Bertics S.J., Lopes J.C. and Akins M.S. (2010). Effect of feedinga reduced-starch diet with or without amylase addition on lactation performance in dairy cows. J. Dairy Sci. 93, 723-732.
Gilmore H.S., Young F.J., Patterson D.C., Wylie A.R.G., Law R.A., Kilpatrick D.J., Elliott C.T. and Mayne C.S. (2011). An evaluation of the effect of altering nutrition and nutritional strategies in early lactation on reproductive performance and estrous behavior of high-yielding Holstein-Friesian dairy cows. J. Dairy Sci. 94, 3510-3526. 
Grant R.J. and Ferraretto L.F. (2018). Silage review: Silage feeding management: Silage characteristics and dairy cow feeding behavior. J. Dairy Sci. 101, 4111-4121.
Green T.C. and Mellor D.J. (2011). Extending ideas about animal welfare assessment to include ‘quality of life’ and related concepts. New Zealand Vet. J. 59, 263-271.
Gumen A., Keskin A., Yilmazbas-Mecitoglu G., Karakaya E. and Wiltbank M.C. (2011). Dry period management and optimization of post-partum reproductive management in dairy cattle. Reprod. Domest. Anim. 46(3), 11-17.
Habegger K.M., Heppner K.M., Geary N., Bartness T.J., DiMarchi R. and Tschöp M.H. (2010). The metabolic actions of glucagon revisited. Nat. Rev. Endocrinol. 6(12), 689-697.
Hamzaoui S., Salama A.A.K., Caja G., Albanell E., Flores C. and Such X. (2012). Milk production losses in early lactating dairy goats under heat stress. J. Dairy Sci. 95(2), 672-673.
Heuer C., Van Straalen W.M., Schukken Y.H., Dirkzwager A. and Noordhuizen T.M. (2001). Prediction of energy balance in high yielding dairy cows with test-day information. J. Dairy Sci. 84(2), 471-481.
Hooda O.K. and Singh S. (2010). Effect of thermal stress on feed intake, plasma enzymes and blood bio-chemicals in buffalo heifers. Indian J. Anim. Nutr. 27(2), 122-127.
Hosseini A., Tariq M.R., Trindade da Rosa F., Kesser J., Iqbal Z., Mora O., Sauerwein H., Drackley J.K., Trevisi E. and Loor J.J. (2015). Insulin sensitivity in adipose and skeletal muscle tissue of dairy cows in response to dietary energy level and 2,4-thiazolidinedione (TZD). PLoS One. 10(11), e0142633.
Ingvartsen K.L. and Andersen J.B. (2000). Integration of metabolism and intake regulation: A review focusing on periparturient animals. J. Dairy Sci. 83(7), 1573-1597.
IPCC (Inter Governmental Panel on Climate Change). (2007). Climate Change: Synthesis Report. Available at: https://archive.ipcc.ch/.
Itle A.J., Huzzey J.M., Weary D.M. and von Keyserlingk M.A.G. (2015). Clinical ketosis and standing behavior in transition cows. J. Dairy Sci. 98, 128-134.
Janovick N., Boisclair Y. and Drackley J.K. (2011). Prepartum dietary energy intake affects metabolism and health during the periparturient period in primiparous and multiparous Holstein cows. J. Dairy Sci. 94(3), 1385-1400.
Jensen M.B. (2012). Behaviour around the time of calving in dairycows. Appl. Anim. Behav. Sci. 139, 195-202.
Jiang F.G., Lin X.Y., Yan Z.G., Hu Z.Y., Liu G.M., Sun Y.D., Liu X.W. and Wang Z.H. (2017). Effect of dietary roughage level on chewing activity, ruminal pH, and saliva secretion in lactating Holstein cows. J. Dairy Sci. 100, 2660-2671.
Jiang F.G., Lin X.Y., Yan Z.G., Hu Z.Y., Wang Y. and Wang Z.H. (2018). Effect of forage source and particle size on feed sorting, milk production and nutrient digestibility in lactating dairy cows. J. Anim. Physiol. Anim. Nutr. 102, 1472-1481.
Kansal G., Yadav D.K., Singh A.K. and Rajput M.S. (2020). Advances in the management of bovine mastitis. Int. J. Adv. Agric. Sci. Technol. 7(2), 10-22.
Kaufman E.I., LeBlanc S.J., McBride B.W., Duffield T.F. and DeVries T.J. (2016). Short communication: Association of lying behavior and subclinical ketosis in transition dairy cows. J. Dairy Sci. 99, 1-8.
Kawai M., Yamaguchi M., Murakami T., Shima K., Murata Y. and Kishi K. (1997). The placenta is not the main source of leptin production in pregnant rats: gestational profile of leptin in plasma and adipose tissues. Biochem. Biophys. Res. Commun. 240, 798-802.
Kawashima C., Munakata M., Shimizu T., Miyamoto A., Kida K. and Matsui M. (2016). Relationship between the degree of insulin resistance during late gestation and postpartum performance in dairy cows and factors that affect growth and metabolic status of their calves. J. Vet. Med. Sci. 78(5), 739-745.
Kim I.H. and Suh G.H. (2003). Effect of the amount of body condition loss from the dry to near calving periods on the subsequent body condition change, occurrence of postpartum diseases, metabolic parameters and reproductive performance in Holstein dairy cows. Theriogenology. 60, 1445-1456.
Knegsel A.T., Van den Brand H., Dijkstra J., van Straalen W.M., Heetkamp M.J., Tamminga S. and Kemp B. (2007). Dietary energy source in dairy cows in early lactation: energy partitioning and milk composition. J. Dairy Sci. 90(3), 1467-1476.
Kumari T., Bhakat C. and Singh A.K. (2020). Adoption of management practices by the farmers to control sub clinical mastitis in dairy animals. J. Entomol. Zool. Stud. 8(2), 924-927.
Kumari T., Bhakat C., Singh A.K., Sahu J., Mandal D.K. and Choudhary R.K. (2019). Low cost management practices to detect and control sub-clinical mastitis in dairy cattle. Int. J. Curr. Microbiol. Appl. Sci. 8(5), 1958-1964.
Lacetera N., Bernabucci U., Ronchi B. and Nardone A. (1996). Body condition score, metabolic status and milk production of early lactation dairy cows exposed to warm environment. Rivista Agric. Subtrop. Trop. 90(1), 43-55.
Lake S.L., Scholljegerdes E.J., Hallford D.M., Moss G.E., Rule D.C. and Hess B.W. (2006). Effects of body condition score at parturition and postpartum supplemental fat on metabolite and hormone concentrations of beef cows and their suckling calves. J. Anim. Sci. 84(4), 1038-1047.
LeBlanc S.J., Leslie K.E. and Duffield T.F. (2005). Metabolic predicators of displaced abomasum in dairy cattle. J. Dairy Sci. 88, 159-170.
Lecorps B., Ludwig B.R., von Keyserlingk M.A.G. and Weary D.M. (2019). Pain-Induced Pessimism and Anhedonia: Evidence from a novel probability-based judgment bias test. Front. Behav. 13, 54-63.
Li L., Cao Y., Xie Z. and Zhang Y. (2017). A high-concentrate diet induced milk fat decline via glucagon-mediated activation of AMP-activated protein kinase in dairy cows. Sci. Rep. 7, 44217-44229.
Linzell J.L. and Peaker M. (1971). Mechanism of milk secretion. Physiol. Rev. 51(3), 564-597.
Maffei M., Fei H., Lee G.H., Dani C., Leroy P., Zhang Y., Proenca R., Negrel R., Ailhaud G. and Friedman J.M. (1995). Increased expression in adipocytes of ob RNA in mice lesions of the hypothalamus and with mutations at the db locus. Proc. Natl. Acad. Sci. 92, 6957-6960.
Malek dos Reis C.B., Barreiro J.R., Moreno J.F., Porcinato M.A. and Santos M.V. (2011). Evaluation of somatic cell count thresholds to detect subclinical mastitis in Gyr cows. J. Dairy Sci. 94, 4406-4412.
Maltz E., Barbosa L.F., Bueno P., Scagion L., Kaniyamattam K., Greco L.F., De Vries A. and Santos J.E.P. (2013). Effect of feeding according to energy balance on performance, nutrient excretion, and feeding behavior of early lactation dairy cows. J. Dairy Sci. 96, 5249-5266.
Mann S., Yepes F.A., Overton T.R., Wakshlag J.J., Lock A.L., Ryan C.M. and Nydam D.V. (2015). Dry period plane of energy: Effects on feed intake, energy balance, milk production, and composition in transition dairy cows. J. Dairy Sci. 98(5), 3366-3382.
McArt J.A.A., Nydam D.V. and Oetzel G.R. (2013). Dry period and parturient predictors of early lactation hyperketonemia in dairy cattle. J. Dairy Sci. 96(1), 198-209.
McCann J.P., Bergman E.N. and Beermann D.H. (1992). Dynamic and static phases of severe dietary obesity in sheep: food intakes, endocrinology and carcass and organ chemical composition. J. Nutr. 122, 496-505.
Meeran K., O’Shea D., Edwards C.M., Turton M.D., Heath M.M., Gunn I., Abusnana S., Rossi M., Small C.J., Goldstone A.P., Taylor G.M., Sunter D., Steere J., Choi S.J., Ghatei M.A. and Bloom S.R. (1999). Repeated intracerebroventricular administration of glucagon-like peptide-1-(7-36) amide or exendin-(9-39) alters body weight in the rat. Endocrinology. 140, 244-250.
Mellor D.J. (2012). Animal emotions, behaviour and the promotion of positive welfare states. New Zealand Vet. J. 60, 1-8.
Miller-Cushon E.K. and DeVries T.J. (2017). Associations between feed push-up frequency, feeding and lying behavior and milk yield composition of dairy cows. J. Dairy Sci. 100, 2213–2218.
Mohammed M.A.B., Al-Shami S.A. and Al-Eknah M.M. (2015). Body condition scores at calving and their association with dairy cow performance and health in semiarid environment under two cooling systems. Italian J. Anim. Sci. 14(1), 77-85.
Moore S.M. and DeVries T.J. (2020). Effect of diet-induced negative energy balance on the feeding behavior of dairy cows. J. Dairy Sci. 103(8), 7288-7301.
Novak J., Stojanovski K., Melotti L., Reichlin T., Palme R. and Würbel H. (2016). Effects of stereotypic behaviour and chronic mild stress on judgement bias in laboratory mice. Appl. Anim. Behav. Sci. 174, 162-172.
Nowroozi-Asl A., Aarabi N. and Rowshan-Ghasrodashti A. (2016). Ghrelin and its correlation with leptin, energy related metabolites and thyroidal hormones in dairy cows in transitional period. Polish J. Vet. Sci. 19(1), 197-204.
NRC. (2007). Nutrient Requirements of Small Ruminants, Sheep, Goats, Cervids, and New World Camelids. National Academy Press, Washington, D.C., USA.
Ospina P.A., Nydam D.V., Stokol T. and Overton T.R. (2010). Associations of elevated nonesterified fatty acids and β-hydroxybutyrate concentrations with early lactation reproductive performance and milk production in transition dairy cattle in the northeastern United States. J. Dairy Sci. 93(4), 1596-1603.
Overton T.R. and Waldron M.R. (2004). Nutritional management of transition dairy cows: Strategies to optimize metabolic health. J. Dairy Sci. 87, 105-119.
Paul A., Bhakat C., Mandal D.K., Mandal A., Mohammad A., Chatterjee A. and Rai S. (2018). Influence of udder hygiene management on milk characteristics in Jersey cross-bred cows at lower Gangetic region. Int. J. Curr. Microbiol. Appl. Sci. 7(8), 1264-1272.
Pezeshki A., Mehrzad J., Ghorbani G.R., Rahmani H.R., Collier R.J. and Burvenich C. (2007). Effects of short dry periods on performance and metabolic status in holstein dairy cows. J. Dairy Sci. 90(12), 5531-5541.
Quiroz-Rocha G.F., LeBlanc S., Duffield T., Wood D., Leslie K.E. and Jacobs R.M. (2009). Evaluation of prepartum serum cholesterol and fatty acids concentrations as predictors of postpartum retention of the placenta in dairy cows. J. Am. Vet. Med. Assoc. 234, 790-793.
Reis M.M., Cooke R.F., Ranches J. and Vasconcelos J.L.M. (2012). Effects of calcium salts of polyunsaturated fatty acids on productive and reproductive parameters of lactating Holstein cows. J. Dairy Sci. 95(12), 7039-7050.
Reist M., Erdin D., von Euw D., Tschuemperlin K., Leuenberger H., Chilliard Y., Hammon H.M., Morel C., Philipona C., Zbinden Y., Kuenzi N. and Blum J.W. (2002). Estimation of energy balance at the individual and herd level using blood and milk traits in high-yielding dairy cows. J. Dairy Sci. 85(12), 3314-3327.
Rhoads R.P., Baumgard L.H., Suagee J.K. and Sanders S.R. (2013). Nutritional interventions to alleviate the negative consequences of heat stress. Adv. Nutr. 4(3), 267-276.
Riedy C.A., Chavez M. and Woods S.C. (1995). Central insulin enhances sensitivity to cholecystokinin. Physiol. Behav. 58, 755-760.
Rizvi S.J., Pizzagalli D.A., Sproule B.A. and Kennedy S.H. (2016). Assessing anhedonia in depression: potentials and pitfalls. Neurosci. Biobehav. Rev. 65, 21-35.
Roche J.R. (2007). Milk production responses to pre- and post-calving dry matter intake in grazing dairy cows. Livest. Sci. 110, 12-24.
Roche J.R., Heiser A., Mitchell M.D., Crookenden M.A., Walker C.G., Kay J.K. and Meier S. (2016). Strategies to gain body condition score in pasture-based dairy cows during late lactation and the far-off non-lactating period and their interaction with close-up dry matter intake. J. Dairy Sci. 100(3), 1720-1738.
Roche J.R., Macdonald K.A., Schütz K.E., Matthews L.R., Verkerk G.A., Meier S. and Webster J.R. (2013). Calving body condition score affects indicators of health in grazing dairy cows. J. Dairy Sci. 96(9), 5811-5825.
Ryan G., Murphy J., Crosse S. and Rath M. (2003). The effect of precalving diet on post-calving cow performance. Livest. Prod. Sci. 79(1), 61-71.
Sahu D., Mandal D.K., Dar A.H., Podder M. and Gupta A. (2019). Modification in housing system affects the behavior and welfare of dairy Jersey crossbred cows in different seasons. Biol. Rhythm Res. 52(9), 1303-1312.
Seifi H.A., Gorji-Dooz M., Mohri M., Dalir-Naghadeh B. and Farzaneh N. (2007). Variations of energy-related biochemical metabolites during transition period in dairy cows. Comp. Clin. Pathol. 16, 253-258.
Senturk S., Cihan H., Kasap S., Mecitoglu Z. and Temizel M. (2015). Effects on negative energy balance of tannin in dairy cattle. Uludağ Üniv. Vet. Fak. Derg. 34, 1-7.
Sepúlveda-Varas P., Weary D.M., Noro M. and von Keyserlingk M.A.G. (2015). Transition diseases in grazing dairy cows are related to serum cholesterol and other analytes. PLoS One. 10, e0122317.
Silanikove N. and Koluman N.D. (2015). Impact of climate change on the dairy industry in temperate zones: Predications on the overall negative impact and on the positive role of dairy goats in adaptation to earth warming. Small Rumin. Res. 123, 27-34.
Singh A.K. (2019). Influence of alteration of management practice on performances of dairy cows at lower Gangetic region. MS Thesis. National Dairy Research Institute, Karnal, India.
Singh A.K. and Kumari T. (2019). Assesment of energy reserves in dairy animals through body condition scoring. Indian Dairyman. 10(5), 74-79.
Singh A.K., Bhakat C., Yadav D.K., Kumari T., Mandal D.K., Rajput M.S. and Bhatt N. (2020a). Effect of pre and postpartum Alphatocopherol supplementation on body measurements and its relationship with body condition, milk yield, and udder health of Jersey crossbred cows at tropical lower Gangetic region. J. Entomol. Zool. Stud. 8(1), 1499-1502.
Singh A.K., Bhakat C., Mandal D.K., Mandal A., Rai S., Chatterjee A. and Ghosh M.K. (2020b). Effect of reducing energy intake during dry period on milk production, udder health and body condition score of Jersey crossbred cows at tropical lower Gangetic region. Trop. Anim. Health Prod. 52, 1759-1767.
Singh A.K., Yadav D.K., Bhatt N., Sriranga K.R. and Roy S. (2020c). Housing management for dairy animals under Indian tropical type of climatic conditions-a review. Vet. Res. Int. 8(2), 94-99.
Singh A.K., Bhakat C., Yadav D.K., Kansal G. and Rajput M.S. (2020d). Importance of measuring water intake in dairy animals:a review. Int. J. Adv. Agric. Sci. Technol. 7(2), 23-30.
Singh A.K., Kumari T., Rajput M.S., Baishya A., Bhatt N. and Roy S. (2020e). Review on effect of bedding material on production, reproduction and health of dairy animals. Int. J. Livest. Res. 10, 11-20.
Singh A.K., Bhakat C., Kumari T., Mandal D.K., Chatterjee A. and Dutta T.K. (2020f). Influence of alteration of dry period feeding management on body weight and body measurements of Jersey crossbred cows at lower Gangetic region. J. Anim. Res. 10(1), 137-141.
Singh A.K., Bhakat C., Mohhamad A., Chatterjee A., Karunakaran M. and Ghosh M.K. (2020g). Economic analysis of pre and postpartum alphatocopherol supplementation for milk performance and dry matter ıntake of dairy cows in tropical region. Int. J. Livest. Res. 10(10), 137-143.
Singh A.K., Bhakat C., Mandal D.K. and Chatterjee A. (2020h). Effect of pre and postpartum alpha-tocopherol supplementation on body condition and some udder health parameters of Jersey crossbred cows at tropical lower Gangetic region. J. Anim. Res. 10(5), 697-703.
Singh A.K., Bhakat C., Chatterjee A. and Karunakaran M. (2020i). Influence of alteration in far-off period feeding management on water intake, water and dry matter efficiency, relative immunoglobulin level in dairy cows at tropical climate. J. Anim. Res. 10(5), 741-749.
Singh A.K. (2021). Advancements in management practices from far-off dry period to initial lactation period for improved production, reproduction, and health performances in dairy animals: A review. Int. J. Livest. Res. 11(3), 25-41.
Singh R., Randhawa S.N.S. and Randhawa C.S. (2015). Body condition score and its correlation with ultrasonographic back fat thickness in transition crossbred cows. Vet. World. 8(3), 290-294.
Smith G.L., Friggens N.C., Ashworth C.J. and Chagunda M.G.G. (2017). Association between body energy content in the dry period and post-calving production disease status in dairy cattle. Animal. 11(9), 1590-1598.
Soita H.W., Christensen D.A. and McKinnon J.J. (2000). Influence of particle size on the effectiveness of the fiber in barley silage. J. Dairy Sci. 83, 2295-2300.
Spiers D.E., Spain J.N., Sampson J.D. and Rhoads R.P. (2004). Use of physiological parameters to predict milk yield and feed intake in heat-stressed dairy cows. J. Therm. Biol. 29, 759-764.
Steensels M., Bahr C., Berckmans D., Halachmi I., Antler A. and Maltz E. (2012). Lying patterns of high producing healthy dairy cows after calving in commercial herds as affected by age, environmental conditions and production. Appl. Anim. Behav. Sci. 136(2), 88-95.
Stengel A. and Taché Y. (2013). Activation of somatostatin2 receptors in the brain and the periphery inducesoppo- site changes in circulating ghrelin levels: Functional implications. Front. Endocrinol. 3, 178-187.
Upadhyay R.C., Ashutosh A. and Singh S.V. (2009). Impact of climate change on reproductive functions of cattle and buffalo. Pp. 107-110 in Global Climate Change and Indian Agriculture. ICAR, New Delhi.
Van Hoeij R.J., Kok A., Bruckmaier R.M., Haskell M.J., Kemp B. and van Knegsel A.T.M. (2018). Relationship between metabolic status and behavior in dairy cows in week 4 of lactation. Animal. 13(3), 1-9.
Von Keyserlingk M.A.G. and Weary D.M. (2010). Feeding behaviour of dairy cattle: Measures and applications. Canadian J. Anim. Sci. 90, 303-309.
Wankhade P.R., Manimaran A., Kumaresan A., Jeyakumar S., Ramesha K.P., Sejian V., Rajendran D. and Varghese M.R. (2017). Metabolic and immunological changes in transition dairy cows: A review. Vet. World. 10(11), 1367-1377.
Weary D.M., Droege P. and Braithwaite V.A. (2017). Behavioral evidence of felt emotions: approaches, inferences, and refinements. Adv. Stud. Behav. 49, 27-48.
Xu W., Vervoort J., Saccenti E., van Hoeij R., Kemp B. and van Knegsel A. (2018). Milk metabolomics data reveal the energy balance of individual dairy cows in early lactation. Sci. Rep. 8(1), 15828-15836.
Yalcin I., Barthas F. and Barrot M. (2014). Emotional consequences of neuropathic pain: Insight from preclinical studies. Neurosci. Biobehav. Rev. 47, 154-164.
Yamada T., Kawakami S. and Nakanishi N. (2003). The relationship between plasma leptin concentrations and distribution of body fat in crossbred steers. Anim. Sci. J. 74, 95-100.
Yang W.Z. and Beauchemin K.A. (2006). Effects of physically effective fiber on chewing activity and ruminal pH of dairy cows fed diets based on barley silage. J. Dairy Sci. 89, 217-228.