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A Comprehensive Study on Starch Nanoparticle Potential as a Reinforcing Material in Bioplastic

Starch can be found in the stems, roots, fruits, and seeds of plants such as sweet potato, cassava, corn, potato, and many more. In addition to its original form, starch can be modified by reducing its size. Starch nanoparticles have a small size and large active surface area, making them suitable for use as fillers or as a reinforcing material in bioplastics. The aim of reinforcing material is to improve the characteristics of bioplastics. This literature study aims to provide in-depth information on the potential use of starch nanoparticles as a reinforcing material in bioplastic packaging. This study also reviews starch size reduction methods including acid hydrolysis, nanoprecipitation, milling, and others; characteristics of the nano-starch particle; and methods to produce bioplastic and its characteristics. The use of starch nanoparticles as a reinforcing material can increase tensile strength, reduce water vapor and oxygen permeability, and increase the biodegradability of bioplastics. However, the use of starch nanoparticles as a reinforcing material for bioplastic packaging still encounters obstacles in its commercialization efforts, due to high production costs and ineffectiveness.

Introduction
Conventional plastic made from petrochemicals has taken on significant importance in modern life [1][2][3][4][5]. The increasing use of plastic causes an increase in the amount of plastic waste, which has a bad impact, especially on the environment and ecosystem [5]. One alternative is to substitute plastic packagings for more environmentally friendly options, such as bioplastics [6][7][8] or green composites [9]. Bioplastic refers to plastics that are made from organic or bio-based materials, have the characteristics of being naturally biodegradable or biodegradable, are made of organic materials, or can be degraded naturally [10,11]. The bioplastic degradation process is carried out by natural microorganisms, such as bacteria, fungi, and algae. This process produces CO 2 gas, methane gas, water, and biomass without any toxic by-products [12,13].
However, in general, bioplastic products are brittle, have low melting temperatures, and have low mechanical strength [1,14,15]. Bioplastics are also prone to disintegration during storage or use, are not chemically resistant, and have high water and oxygen permeability [15,16]. Using reinforcing material or filler is one option to improve the properties of the bioplastic matrix. The purpose of reinforcing material is to improve the properties of the matrix, such as enhancing degradability [1,17], increasing mechanical properties [18], and decreasing oxygen and water vapor permeability [13,19].
The basic material commonly used for the manufacture of reinforcing materials in bioplastics is starch. Starch is a polysaccharide derivative compound in the form of granules and is used by plants as an energy source. Starch granules have a semi-crystalline structure and are composed of amylose and amylopectin, which are complex carbohydrate polymers [20][21][22]. Amylose has a straight chain, while amylopectin has a branched chain [23]. In its use, starch can be used in its original form or can be modified beforehand for better characteristics, or as desired [24,25]. In its application, starch with high amylose content will produce products with higher water absorption [26,27]. Starch with high amylose content will also produce a stiffer gel structure. The ratio of amylose and amylopectin affects texture, solubility, viscosity, stability, gelatinization, moisture retention, retrogradation, and syneresis. These criteria affect the application and characteristics of the resulting product [28,29]. Starch is often modified to increase its functional properties and application [30][31][32].
One starch modification method is to reduce the size of starch particles to nanosize, which can be referred to as starch nanoparticles. Starch nanoparticles have at least 1 particle with a size of less than 300 nm and have a high active surface area [33]. Starch nanoparticles are spherical particles of nanosize that have varying crystallinity, and can also be completely amorphous [34]. In addition to the form of starch nanoparticles, there are also starch nanocrystals. Starch nanocrystals can be interpreted as a crystalline plate resulting from the removal of amorphous regions by hydrolysis. Starch nanocrystals have higher crystallinity when compared to starch nanoparticles [35].
Nowadays, the interest in research on bioplastics and reinforcing materials to produce bioplastics with better characteristics has increased. Starch is a promising resource because it is cheap, biodegradable, and abundant; thus, starch is promising in bioplastics and in reinforcing material production. This literature study is expected to provide in-depth information on the potential use of starch nanoparticles as reinforcing materials in bioplastics.

Preparation of Starch Nanoparticles for Bioplastic Reinforcing Material
There are two types of starch nanoparticle manufacturing methods, namely, topdown and bottom-up [36,37]. The top-down method focuses on reducing the granule size from bulk to micro-to nanosize, for example, by acid hydrolysis, ultrasonication, homogenization, gamma irradiation, and many more [38][39][40][41]. The bottom-up method focuses on the formation of nano-sized starch molecules from atoms under controlled conditions according to the laws of thermodynamics, such as nanoprecipitation and selfassembly methods [42][43][44]. Top-down methods are simple, require less cost, and are suitable for both laboratory and industrial scales. However, top-down methods are less effective for sources that have an irregular shape and an extremely small size. Bottom-up methods demand more money but require short production time and can generate less destructed starch [45]. Figure 1 illustrates starch nanoparticle production method with top-down and bottom-up approaches.

Physical Method
Examples of treatments that include physical methods are milling [46,47], highpressure homogenization [48][49][50], ultrasonication [51,52], and gamma irradiation [53,54]. The advantage of the physical method is that there is no use of chemicals or solvents, making it more environmentally friendly and simple. The time required in this method is also relatively shorter. The disadvantage of mechanical treatment is that it can cause damage to the crystalline structure of starch granules.
The physical method tends to result in starch nanoparticles with low crystallinity because the use of energy is very large, so the crystalline structure becomes weak [55]. This does not apply to gamma irradiation, as fragmentation by free radicals that occurs through gamma irradiation happens in the amorphous region, resulting in starch nanoparticles with relatively high crystallinity. Although gamma irradiation uses free radicals to destroy the chemical bonds of starch granules and starch particles become smaller, the free radicals here are not dangerous. Because they are easily soluble in water, the resulting starch nanoparticles do not contain radical components [54]. On the other hand, other methods attack the crystalline region, thus resulting in starch nanoparticles with lower crystallinity.

Physical Method
Examples of treatments that include physical methods are milling [46,47], hig sure homogenization [48][49][50], ultrasonication [51,52], and gamma irradiation [53,5 advantage of the physical method is that there is no use of chemicals or solvents, m it more environmentally friendly and simple. The time required in this method relatively shorter. The disadvantage of mechanical treatment is that it can cause d to the crystalline structure of starch granules.
The physical method tends to result in starch nanoparticles with low cryst because the use of energy is very large, so the crystalline structure becomes we This does not apply to gamma irradiation, as fragmentation by free radicals that through gamma irradiation happens in the amorphous region, resulting in starch particles with relatively high crystallinity. Although gamma irradiation uses free r to destroy the chemical bonds of starch granules and starch particles become sma free radicals here are not dangerous. Because they are easily soluble in water, the re starch nanoparticles do not contain radical components [54]. On the other hand methods attack the crystalline region, thus resulting in starch nanoparticles with crystallinity.
Among the physical method for starch nanoparticle production, milling prod larger size of starch nanoparticle. During milling, the reduction in starch granule nosize is obtained from the weight and speed of the grinding ball that continues t and rotate. This movement will produce kinetic energy. This energy will be chann the sample, resulting in a reduction in the size sample [56]. It can be seen that corn processed by milling produces starch nanoparticles with a size of 245 nm [47], whi line with another study [57].
The ultrasonication method is considered effective in reducing the size of starc ing ultrasonication, energy is transferred to the starch through a cavitation process is a condition where the microbubbles burst and spread in the solution suspension form of sound waves. This process involves high speed and generates shear forc Among the physical method for starch nanoparticle production, milling produces a larger size of starch nanoparticle. During milling, the reduction in starch granules to nanosize is obtained from the weight and speed of the grinding ball that continues to move and rotate. This movement will produce kinetic energy. This energy will be channeled to the sample, resulting in a reduction in the size sample [56]. It can be seen that corn starch processed by milling produces starch nanoparticles with a size of 245 nm [47], which is in line with another study [57].
The ultrasonication method is considered effective in reducing the size of starch. During ultrasonication, energy is transferred to the starch through a cavitation process, which is a condition where the microbubbles burst and spread in the solution suspension in the form of sound waves. This process involves high speed and generates shear forces that can break the covalent bonds of starch; thus, the starch particle size decreases [58]. Several studies have reported that the ultrasonication method produced cassava starch nanoparticles (35-65 nm) [59] and waxy maize starch nanoparticles (37 nm) [60], whereas high-pressure homogenization can produce sago starch nanoparticles (28.514 nm) [61]. The high pressures produce shear forces that can break starch hydrogen bonds, resulting in a reduction in the size of starch into nanoparticles [62].

Chemical and Enzymatic Method
Examples of chemical production methods for starch nanoparticles are acid hydrolysis [36,63,64] and nanoprecipitation [65][66][67]. The enzymatic method can be performed through enzymatic hydrolysis [68][69][70]. Acid and enzymatic hydrolysis use the same mechanism, which is that the area that will be attacked first is the amorphous region, then the acid and enzyme will attack the more crystalline region at a slower rate [17,71,72]. In nanoprecipitation, the starch is gelatinized first, then precipitated using an antisolvent such as ethanol. At the time of precipitation, starch chains will be broken, resulting in starch with a smaller size [73].
Chemical and enzymatic methods mostly result in starch nanoparticles with high crystallinity [74,75]. The difference between acid and enzymatic hydrolysis is that acid hydrolysis uses acid as a hydrolyzing agent, such as sulfuric acid (H 2 SO 4 ) or chloride acid (HCl) [76], while enzymatic hydrolysis uses hydrolase enzyme, such as pullulanase [77]. Although acid hydrolysis can produce high crystallinity starch nanoparticles, the time required for the production is far longer than enzymatic hydrolysis and nanoprecipitation. Most researchers that use acid hydrolysis require at least 5 days for hydrolysis [17,63,78], while enzymatic hydrolysis and nanoprecipitation require less than 1 day [43,70,[79][80][81][82]. Potato starch nanoparticles which produce using hydrolysis have a higher crystallinity compared to enzymatic hydrolysis. Potato starch nanoparticles obtained by the enzymatic hydrolysis method have a crystallinity of 13.2% [80]. Meanwhile, potato starch nanoparticles obtained by acid hydrolysis and nanoprecipitation have a crystallinity of 42.2% and 44.1%, respectively [83].
Enzymatic hydrolysis tends to produce a higher yield of starch nanoparticle. A study showed potato starch nanoparticles with a manufacturing method using the pullulanase enzyme on elephant foot yam tuber starch, where the extraction yield obtained was 61.33% [84]. Another study also showed that the use of pullulanase enzymes in corn starch hydrolysis produced starch nanoparticles with a yield of 85% [79], while amadumbe starch nanoparticle produced through acid hydrolysis has a yield of 25% [85]. The differences in yield may be attributed to starch type in addition to hydrolysis type.
Regarding size, acid hydrolysis can produce starch nanoparticles with smaller sizes compared to nanoprecipitation. Putro et al. [86] have reported that the acid hydrolysis method produces potato starch nanoparticle with a smaller granule size than the nanoprecipitation method: 85.1 nm and 165.31 nm, respectively. This might be due to the native starch, with microparticle size being fragmented into smaller particles during acid hydrolysis; some of the amorphous parts were hydrolyzed into simple sugars, resulting in the formation of smaller nanoparticles. A previous study has reported that the granule size of starch nanoparticles also depends on amylose content and starch type; the smallest observed size of starch nanoparticles of potato, waxy maize, sweet potato, pea, tapioca, corn, and sweetcorn ranged from 15 to 50 nm, and the largest size observed was between 80 and 225 nm [82]. However, the size and the yield of the starch nanoparticles are influenced by the amylose content and starch crystallinity, where the starch with the low amylose content will produce starch nanoparticles with small size [73]. Waxy maize starch nanoparticles (1% amylose) produced through acid hydrolysis have a size of 47 nm, while high-amylose corn starch nanoparticles (70% amylose) produced with the same treatment have a size of 118 nm [87].

Combined Method
A combined method can be performed using two or more methods at one time of production. It is possible to combine chemical methods and chemical methods, physical methods, and physical methods, as well as chemical methods and physical methods. Examples of combined methods are the use of acid hydrolysis and ultrasonication, acid hydrolysis and precipitation, enzymatic hydrolysis and acid hydrolysis, and many more [88][89][90][91][92].
The use of the acid hydrolysis method with other methods, such as enzymatic hydrolysis, ultrasonication, and milling as a pre-treatment, can overcome the shortcomings of the acid hydrolysis method, namely, the long treatment time [83]. Such pre-treatment can increase the rate of hydrolysis because it means that the acid can reach and damage the amorphous region more quickly [73]. The study conducted by Zhou et al. [88] showed that the use of acid hydrolysis (hydrochloric acid vapor) combined with ultrasonication produces 80.5% waxy maize starch nanoparticles with the hydrolysis time of 1 h, whereas it usually takes more than 5 days for acid hydrolysis. Mango kernel nanoparticle starch produced by combining these two methods has a size of 24.4 nm with a yield of 24.4% [93]. Using the same method, procedure, and starch source, another study reported that the size of the mango kernel starch nanoparticle granule was 79 nm with a yield of 31.7% [94].
The use of ultrasonication before acid hydrolysis treatment can help acid molecules to reach the starch surface more quickly so that the required hydrolysis time is shorter [95]. The cavitation process that occurs during ultrasonication produces a shear force that has an impact on the damage to the starch surface. The extraction yield obtained is also higher with high crystallinity [35]. The production of starch nanoparticles using several methods is presented in Table 1.

Amylose Content
Amylose content in starch can be analyzed using the iodine-binding method. When amylose meets iodine, it produces a blue color, while amylopectin reacts with iodine to produce a red-purple color that is not too bright [102]. Minakawa et al. [59] reported that yam starch nanoparticles produced by ultrasonication have higher blue value than corn and cassava starch nanoparticles produced using the same method. Higher blue value indicates a higher amylose content in starch.
Potato starch nanoparticles obtained through the nanoprecipitation method had the highest amylose content (21.39%) compared to the acid hydrolysis method (4.79%) and the combined acid hydrolysis method with ultrasonication (3.08%) [83]. In starch nanoparticles from the acid hydrolysis method, amylose content decreased. This is because the amorphous areas in starch granules are very sensitive to acid, so the amorphous areas can be hydrolyzed and leave crystalline regions [102]. Starch crystallinity also has a relation with amylose and amylopectin. Starch crystallinity is attributed to the packing of double helixes formed by amylopectin side chains; thus, starch with higher amylopectin tends to have higher relative crystallinity [87].
Furthermore, LeCorre et al. [87] have reported that amylose content plays a role in determining the particle size of starch nanoparticles, where starch with low amylose content tends to produce starch nanoparticles with smaller particle sizes. This is because amylose is considered to be able to inhibit the hydrolysis process so that hydrolysis becomes slower and the resulting particle size becomes larger.

Granule Morphology Shape and Size
Granule morphology and the size of starch nanoparticles were analyzed using SEM (scanning electron microscopy), TEM (transmission electron microscopy), or FE-SEM (fieldemission scanning electron microscopy) [95]. Granule morphology shape and the sizes of starch nanoparticles from various starch sources and production methods are presented in Table 2. A previous study by Hernández-Jaimes et al. [103] reported that acid hydrolysis treatment caused changes in the shape and size of native starch granules and presented erosions and fractures on the granule surface. The longer the hydrolysis process, the higher the deformation on the surface. As the hydrolysis time increases, deeper surface erosion occurs, which eventually leads to the fragmentation of some starch granules. The presence of some small remnant granules after 15 days was observed. The number of nanoparticles increases with longer acid hydrolysis times.  Furthermore, Minakawa et al. [59] reported that ultrasonic treatment causes granule surfaces to crack and erode progressively, as observed by SEM. Some smaller particles are released with different morphology than their native starch granule. This result was in agreement with another study [60], which reported that the ultrasonication method reduces the granule size of waxy maize starch from 2-15 µm to 20-200 nm. The surface of the starch granules appears to be broken down and eroded progressively with increasing ultrasonication time.

Crystallinity
Crystallinity can be interpreted as a comparison between the mass of the crystalline region with the mass of starch nanoparticles as a whole [73]. Starch crystalline structure can be observed using XRD (X-ray diffractograms). The crystalline type of starch nanoparticle can be influenced by the variety or cultivars of the starch source. Banana starch from different cultivars shows different types of crystalline [108].
Starch crystallinity has a relationship with the double-helix structure of the amylopectin chain, so starches with high amylopectin content tend to have high crystallinity compared to starches with high amylose content [87]. Starch nanoparticles of waxy maize with the acid hydrolysis method have a crystallinity of 69%. Meanwhile, the ultrasonication production method obtained 0% crystallinity [34]. Tapioca starch has a crystallinity of 25.12%, which decreased to 12.53% after the nanoprecipitation process and decreased to 6.49% after the nanoprecipitation + ultrasonication process [81]. This is due to the ultrasonication and nanoprecipitation processes attacking the crystalline region; thus, these methods tend to produce starch nanoparticles with low crystallinity [59,81]. Meanwhile, acid and enzymatic hydrolysis attack the amorphous region first; hence, the starch nanoparticles produced from acid and enzymatic hydrolysis have higher crystallinity [79,96,103]. Plantain starch nanoparticles obtained from acid hydrolysis have a relative crystallinity of 90% [103]. The relative crystallinity and crystallinity patterns of starch nanoparticles from various starch sources and production methods are shown in Table 3.

Thermal Properties
Thermal characteristics can be analyzed using DSC (differential scanning calorimetry) and TGA (thermogravimetric analysis). The parameters observed include T o (onset temperature), T c (endset temperature), T p (peak temperature), T c −T o (melting temperature range), and ∆H (enthalpy change) [70]. Starch nanoparticles have lower thermal stability when compared to native starch. This is due to a decrease in the molecular weight of the starch nanoparticles [79]. The ultrasonication and nanoprecipitation processes can reduce the thermal stability of starch nanoparticles compared to native starch. Native tapioca starch has T o , T p , T c , and ∆H values of 57.07 • C, 66.33 • C, 73.73 • C, and 9.84 J/g, respectively. The nanoprecipitation + ultrasonication process reduces T o , T p , T c , and ∆H by 40.77 • C, 50.39 • C, 63.8 • C, and 1.99 J/g, respectively [81]. A lower enthalpy indicates a poorer starch molecular structure [29]. The thermal properties of starch nanoparticles from various starch sources and production methods are presented in Table 4. Table 4. Thermal properties of starch nanoparticles from various starch sources and production methods.

Starch Source
Method

Starch Source Method T o ( • C) T p ( • C) T c ( • C) T c −T o ( • C) AH (J/g) Ref.
High

Definition and Preparation of Bioplastic with Starch Nanoparticles as Reinforcing Material
Bioplastic refers to plastics that are made from biomass or are bio-based, plastics that have the characteristics of being biodegradable, or plastics made from biomass that can be degraded naturally [10,110]. Examples of bio-based bioplastic packaging are bio-PE and bio-PET [111]; examples of biodegradable bioplastic packaging are PBS (polybutylene succinate), PCL (polycaprolactone), and PVA (polyvinyl alcohol); examples of bioplastics that have bio-based and biodegradable properties are PLA (polylactic acid), PHA (polyhydroxyalkanoate), and packaging with a mixture of starch, cellulose, or lignin [112][113][114][115][116][117].
The methods commonly used for the manufacture of bioplastic packaging are solution casting [98,[118][119][120], injection molding [121,122], compression molding [123], and extrusion [124][125][126]. The casting method is very simple and inexpensive; thus, this method is suitable for use on a laboratory scale [127]. On the other hand, it also has drawbacks because it is not suitable for industrial scale [23]. In the manufacture of bioplastic packaging with a starch matrix, starch gelatinization is carried out first with or without a plasticizer. Subsequently, the mixture of starch and plasticizer was cooled to inhibit the gelatinization of the starch nanoparticle. The film solution is then poured into a mold and heated at a certain temperature and time. After cooling and molding, the film can be removed from the mold [98].
The injection molding method produces packaging with good characteristics with effective production costs, including in large-scale production. Before printing, the dough must first be made which is a mixture of matrix and plasticizer. The injection process is carried out using a piston injection molding machine [128]. The extrusion method is suitable for industrial-scale production and requires low production costs. However, the use of nanoparticles in the extrusion method can increase the tendency of nanoparticles to form aggregates; thus, extrusion may not be suitable for bioplastic manufacturing with a starch nanoparticle as the reinforcing material [16]. The steps in the production of bioplastic packaging using the extrusion method consist of mixing, extrusion, and die-cutting stages to obtain bioplastic samples with certain dimensions. The extrusion process is carried out using an extruder machine [124].

Characteristics of Bioplastic with Starch Nanoparticles as Reinforcing Material
This paper will discuss the mechanical properties, water vapor permeability, thermal properties, and biodegradability of bioplastic with various starch nanoparticles for reinforcement. All the literature used in discussing the characteristics below use casting as a bioplastic production method. A lot of researchers use the casting method because the casting method is the simplest and most inexpensive method, compared to other methods.
The characteristics of bioplastic with starch nanoparticle reinforcement will be influenced by filler concentration, filler-matrix interaction, and filler characteristics [129,130].

Mechanical Properties
Parameters tested include flexibility, strength, and stiffness of the bioplastic film. Mechanical characteristics can be analyzed using a TA (texture analyzer) [101] or using DMA (dynamic mechanical analysis) [131]. The effect of the use of reinforcing material on the strength of bioplastic packaging might be caused by the bond between the surface of the reinforcing material and the matrix, resulting in a stress distribution through the friction mechanism between the reinforcing material and the matrix to increase the strength of the bioplastic packaging [85]. The use of reinforcing materials causes the packaging structure to become denser and more compact, thus increasing the mechanical strength of bioplastics [109].
Piyada et al. [98] have reported a study on rice starch film with rice starch nanocrystals as a reinforcing material and and sorbitol as a plasticizer. As the reinforcing material composition increases, the flexibility of the bioplastic decreases, and the tensile strength increases. Bioplastic without reinforcing material has an elongation at a break of 53.46% and a tensile strength of 7.12 MPa. The use of 30% rice starch nanoparticle as a reinforcing material produces bioplastics with a flexibility of 2.48% and a tensile strength of 12.86 MPa. Another research [132] showed a similar trend, where the reinforcing material composition increased, the flexibility of the bioplastic decreased, and the tensile strength increased. Furthermore, addition of 10% starch nanoparticle as a reinforcing material decreased elongation at break from 1550% to 905% and increased tensile strength from 13.5 MPa to 19.9 MPa. The mechanical properties of bioplastics with various compositions are presented in Table 5.

Water Vapor Permeability
The interaction of the reinforcing material and the matrix in bioplastic packaging forms a strong bond so that the water and air entry paths in the matrix molecules become torturous. This makes it difficult for air and water vapor to penetrate through the packaging film [61]. With a higher concentration of reinforcing material, the structure inside the package will become denser and the pores in the package will be smaller, making it difficult for water and air vapor to penetrate the packaging wall. However, there is also a maximum concentration at which the reinforcing material can work optimally [95]. No data have been found regarding the optimal composition for the use of starch nanoparticles as a reinforcement in bioplastics. This might be due to the optimal concentration of starch nanoparticles being highly dependent on the type of matrix.
The use of reinforcing material is effective in reducing water vapor and oxygen permeability. Bioplastic with a polyurethane matrix (PU) and a reinforcing material of corn starch nanoparticles has a water vapor permeability (WVP) of 3.17% without the use of reinforcing material, which decreases to 0.92% with the use of 30% reinforcing material. Oxygen permeability also decreased from 27.5% with 0% reinforcing material to 6.7% with 30% reinforcing material [95]. A previous study [137] showed that the maximum reinforcing material concentration in the bioplastic composition was 20%, where the matrix used was carboxymethyl chitosan and the reinforcing material used was waxy maize starch nanoparticles with a glycerol plasticizer. When the starch nanocrystal content was higher than 30%, they aggregated and the phase separated in the matrix. The water vapor permeability of bioplastic with various compositions is presented in Table 6.

Thermal Properties
Analysis of the glass transition temperature can be carried out by using DSC (differential scanning calorimetry) [19], DMA (dynamic mechanical analysis) [85], or TGA (thermogravimetry analysis) [95]. The parameters tested include glass transition temperature (T g ), onset temperature (T o ), melting point (T m ), and enthalpy change (∆H) [95]. The mechanism of starch nanoparticles as a reinforcing material in increasing thermal stability involves the interaction between the reinforcing material and matrix, forming a barricade that can inhibit the transfer of heat and energy [141].
According to Hakke et al. [95], there is an increase in ∆H along with the addition of the reinforcing material used. The increasing ∆H is related to starch, with nanoparticle size having a wider active site to interact and bind to the packaging matrix, so it takes more energy to break the polymer structure. This theory is in line with another study on bioplastic with a waterborne polyurethane (WPU) matrix and a pea starch nanoparticle reinforcing material [133]. The enthalpy change in bioplastic with 0% reinforcing material is 2.34 J/g, which increases to 12.5 J/g with a 30% concentration of reinforcing material. However, these results differ from the study by Mukurumbira et al. [85], where along with the addition of reinforcing material concentration, there was a decrease in ∆H. Bioplastic with matrix potato starch, 10% amadumbe starch nanoparticle reinforcing material, and glycerol plasticizer had a ∆H of 0.91 J/g, while in the sample without reinforcing material, the observed ∆H was 14.32 J/g. This could be related to the effect of starch nanoparticles on hindering the lateral arrangements of starch chains and the crystallization of starch films [85]. The thermal properties of bioplastics with various compositions of DSC measurements are shown in Table 7.

Biodegradability
The biodegradability test was carried out to determine the time required for bioplastic packaging to decompose in the soil. Biodegradability causes a decrease in molecular weight, due to the activity of microorganisms, such as bacteria, microalgae, and fungi, resulting in molecular reduction [19]. This test can be performed by placing the film sample in a container filled with soil, then observing the decrease in the weight of the film sample along with the length of the test [142]. During the degradation process, relative humidity plays a role in determining the biodegradation rate. Higher relative humidity can increase the growth of microorganisms, causing a higher rate of degradation [106].
The use of starch nanoparticles as a reinforcing material is effective in increasing the biodegradability of bioplastic packaging. A previous study has reported that within 1 week, bioplastic with a starch mung bean matrix and glycerol plasticizer experienced a weight loss of 28.67%. When adding 1% mung bean starch nanoparticle reinforcing material, in the same period, there was a decrease in packaging weight of 83.46%, and when 2-10% reinforcing material was added, the packaging was 100% degraded [143]. The use of corn starch nanoparticle reinforcing material also increases the biodegradability of PCL packaging. With the use of 10% reinforcing material, the observed weight loss reached 17.6 mg/cm 2 , whereas without reinforcing material, the observed weight loss was 7 mg/cm 2 . Then, the observed weight loss was more than 2 times [19]. An increase in biodegradability is due to the use of starch nanoparticles causing a decrease in the molecular mass of the packaging polymer; hence, the degradation process by microorganisms takes place more quickly [19]. According to González Seligra et al. [106], the use of starch nanoparticles causes an increase in the film's moisture content, thereby creating a more suitable condition for the growth of microorganisms. This condition increases the chance of microorganism attack. During the degradation process, relative humidity plays a role in determining the biodegradation rate. Higher relative humidity can increase the growth of microorganisms, causing a higher rate of degradation [106]. The biodegradation rate of starch-based bioplastic depends on the hydrophilicity of the matrices. It is directly related to the water absorption; the higher the water absorption, the higher biodegradation [144,145]. The biodegradability of bioplastics with various compositions is shown in Table 8.

Opportunities and Challenges
Improving the properties of bioplastic polymers is a primary challenge of achieving sustainability in the food and packaging industry [146][147][148]. Starch nanoparticles can be utilized to make other kinds of packaging, including edible packaging, active packaging, and smart packaging, in addition to being a reinforcing material in bioplastic packaging.
The usage of starch nanoparticles in edible packaging is safe because they are nontoxic [103]. The use of starch nanoparticles in active packaging can maintain the stability of the bioactive compounds contained in the packaging because these compounds are volatile compounds that are sensitive to certain conditions [136]. Fonseca et al. [149] conducted a study related to the stability of the carvacrol compound mixed with potato starch nanofiber. They found that potato starch nanofibercan be a vehicle for carvacrol release in active packaging.
The use of starch nanoparticles as a reinforcing material as well as in the packaging field in general still finds many obstacles in its commercialization business. This is because production costs have not been effective. After all, the number of adaptations of this technology is still very low. On the other hand, reinforcing materials from inorganic materials have been widely applied, so that the production costs are cheaper and can produce bioplastic packaging with good characteristics. This causes the price of bioplastic packaging with reinforcing materials from starch nanoparticles to be expensive, and the option of using reinforcing materials from inorganic materials is preferred [16].

Conclusions
Research related to bioplastics as an alternative to conventional plastics is increasingly being carried out. This is based on the environmentally friendly nature of bioplastics. However, bioplastics still have limited characteristics, such as low mechanical strength and high water vapor permeability; hence, reinforcing the material's role becomes important. The use of starch nanoparticle as a reinforcing material in bioplastic decreases the elongation at break and water vapor permeability, and increases tensile strength and biodegradability. In general, starch nanoparticles also increase the thermal stability of bioplastics. The concentration of reinforcing material that exceeds the maximum threshold has an impact on increasing water vapor permeability and decreasing the mechanical and thermal characteristics of bioplastic packaging because starch nanoparticles at excessive concentrations tend to form aggregates.

Future Research
Starch nanoparticles have a great opportunity to be developed in the packaging field, mainly because of environmental interest. Although starch nanoparticles have many advantages as reinforcing materials, the utilization of starch nanoparticles on an industrial scale is still limited because adaptation to the use of starch nanoparticles as reinforcing materials in packaging is still low, causing production costs to be high and ineffective. Hence, continuous research about nano-reinforced bioplastic is needed.
In bioplastic processing, the dispersion and homogeneity of mixing bioplastic with starch nanoparticles as a reinforcing material are also interesting to study to produce high-quality bioplastic. The modification of starch nanoparticles can also be a promising option to make better bioplastic characteristics. There have been several studies on starch nanoparticle modification, but the number is still very limited, and thus further research needs to be developed.

Conflicts of Interest:
The authors declare no conflict of interest.


provenance: AgriculturalAndFoodSciences,2022-2022-Agricultural And Food Sciences-2022.jsonl.gz.gz

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PRM1 Gene Expression and Its Protein Abundance in Frozen-Thawed Spermatozoa as Potential Fertility Markers in Breeding Bulls

Functional genes and proteins in sperm play an essential role in bulls’ reproductive processes. They are more accurate in determining bull fertility than conventional semen quality tests. Protamine-1 (PRM1) is a gene or protein crucial for packaging and protecting sperm DNA until fertilization affects normal sperm function. This study analyzes the genes and proteins potential from PRM1 as fertility markers for different breeds of bulls utilized in the artificial insemination programs, expected to be an accurate tool in interpreting bull fertility in Indonesia. This study used Limousin, Holstein, and Ongole Grade bulls divided into two groups based on fertility, high-fertility (HF) and low fertility (LF). The semen quality assessment included progressive motility (computer-assisted semen analysis), viability (eosin-nigrosine), and plasma membrane integrity (HOS test). Sperm DNA fragmentation (SDF) was assessed using the acridine orange staining and the Halomax test. Sperm PRM deficiency was evaluated with the chromomycin A3 method. Moreover, PRM1 gene expression was measured using qRT-PCR, and the PRM1 protein abundance was measured with the enzyme immunoassay method. Semen quality values, relative expression of PRM1 gene, and quantity of PRM1 protein were significantly higher (p < 0.05) in HF bulls than in LF bulls. The SDF and PRM deficiency values in LF bulls were significantly higher (p < 0.05) than HF bulls. Additionally, PRM1 at the gene and protein levels correlated significantly (p < 0.01) with fertility. Therefore, PRM1 is a potential candidate for fertility markers in bulls in Indonesia.

Introduction
The artificial insemination (AI) program is a proven and successful reproductive technology in increasing population and livestock production [1]. The AI program for cattle uses frozen semen from different breeds of bulls produced at the AI center with specific standards [2]. Generally, sperm motility above 40% with spermatozoa concentration not less than 25 million per insemination dose is used for quality control of frozen semen in AI programs [3]. This quality standard should predict bull fertility and optimize AI success via a high percentage of pregnancy and calf births. Unfortunately, facts reveal that the success of AI is still comparatively low. Rosyada et al. [4] reported that the conception rate of several Holstein bulls was still classified as low fertility (LF), namely, 33.78% from >1000 AI data and 21.15% from <1000 AI data, even though the quality of frozen semen met the standards, including spermatozoa motility above 40%. Pardede et al. [5] also reported that the %CR of bulls in controlled breeding program centers was sub-optimal, at 63% from

Experimental Animals
The Indonesian National AI center produced the frozen semen used in this study. The frozen semen sample used in this study is a commercial product from the AI center, where every procedure, from the process of collecting fresh semen to producing it into frozen semen, including the management of bulls' maintenance, follows the operational standards of the AI center, which is supervised by a veterinarian and has complied with every principle of animal welfare. The semen was obtained from bulls at their sexual maturity and productive phase, at 4-5 years of age. This study used 18 bulls, including six Limousin, Holstein, and Ongole Grade bulls. Furthermore, each breed was grouped into two based on the fertility score, HF (n = 3) and LF (n = 3). The fertility score was based on each bull's first service %CR; %CR > 70% are categorized as HF bulls, and %CR < 70% Vet. Sci. 2022, 9,111 3 of 15 is classified as LF bulls [6]. The %CR data was obtained from AI data and pregnancy tests on cows for the last two years at the National Animal Health Information System (iSIKHNAS), Indonesia.
The iSIKHNAS is an animal health information system in all regions in Indonesia, including data on AI programs accompanied by pregnancy data. The results of the analysis carried out on iSIKHNAS data, the number of cows/heifers that were inseminated in each breed of bulls in the study were 143,010 (Limousin), 81,741 (Holstein), and 98,571 (Ongole Grade) cows/heifers. Meanwhile, the number of AI services for each breed of the bull in the study were 197,588 (Limousin), 106,034 (Holstein), and 136,686 (Ongole Grade) services. The percentage of pregnant cows/heifers from the first insemination service of the total AI services (%CR) was analyzed according to Pardede et al. [5].

Frozen Semen Quality
A total of 90 frozen semen straws (five straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used in this stage. First, the frozen semen was thawed in a water bath at 37 • C for 30 s, then put into a microtube for further observation. Next, the sperm's progressive motility (PM) parameters were analyzed using computer-assisted semen analysis. After that, 10 µL of thawed sperm were dropped onto a slide and covered with a coverslip. Finally, four fields were evaluated with a range of 50-250 sperm cells automatically counted using Sperm Vision (Minitube, Tiefenbach, Germany) [20].
Additionally, sperm viability was evaluated using eosin-nigrosine (0.825 g eosin Y, 5 g nigrosine, 0.375 g Na Citrate, and 100 mL aquadest) staining. First, the sperm viability was evaluated by making a smear on slides from a mixture of 10 µL semen and 10 µL eosin-nigrosine (1:1). Then, the slides were dried using a heating table, observed, and counted under a light microscope with 40× objective magnification. Two hundred sperm cells per slide were evaluated, with live sperm unstained and dead sperm with damaged membranes stained (reddish) [31]. Next, the integrity of the plasma membrane of sperm was evaluated using the HOS (hypoosmotic swelling) test method. Furthermore, 20 µL of semen was mixed into 300 µL of HOS solution (0.735 g Na citrate, 1351 g, and 100 mL aquadest) and incubated in a water bath at 37 • C for 30 min. Then, 10 µL of the mixture was dropped on a slide, covered with a coverslip, and observed under a light microscope with 40× objective magnification. Finally, 200 sperm cells per slide were counted, with a coiled tail indicating sperm of intact plasma membrane integrity [5,32].

Sperm DNA Fragmentation
Sperm DNA fragmentation (SDF) was assessed using acridine orange (AO) staining and the Halomax test. A total of 90 frozen semen straws (five straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used for AO staining. First, a smear was made 5-10 µL of semen on a slide, then fixed in Carnoy's solution (methanol: glacial acetic acid (3:1)) for 2 h. Next, the slides were stained in a new AO solution (10 mL of 1% acridine orange, 40 mL of 0.1 M citric acid, 2.5 mL Na 2 HPO 4 7H 2 O) for 5 min in a dark room. Next, a coverslip was placed on the slide after washing with distilled water. Finally, 500 sperm cells per slide were observed and counted under a fluorescent microscope using a 490 nm excitation filter and a 530 nm emission filter. The green fluorescence denoted the sperm with mature chromatin and intact DNA integrity, whereas sperm with fragmented DNA integrity was characterized by a reddish-orange fluorescence [33].
Moreover, according to the manufacturer's protocols, SDF was assessed using the Halomax test (Bos taurus, Halotech DNA SL, Madrid, Spain). A total of 90 frozen semen straws (five straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used for this test. First, 25 µL (15-20 × 10 6 sperm cells/mL) was mixed with 50 µL of liquid agarose in a microtube at 37 • C. A total of 1.5-2 µL of cell suspension was dropped into marked wells on a pre-cooled slide (4 • C), and a coverslip was placed. The slide was incubated in the refrigerator at 4 • C for 5 min. The coverslip was carefully removed from the slide at room temperature (22 • C), and a lysing solution was dripped on the slide horizontally for 5 min and later dried. Next, the slides were washed with distilled water for 5 min and re-dried. Finally, the slides were dehydrated with 70% and 90% ethanol solutions, respectively, for 2 min and dried. The staining process was done by dripping 5 µL of 0.01 mm propidium iodide dye for 5 min in a dark room. Five hundred sperm cells per slide were observed under a fluorescent microscope using a 510-560 nm excitation filter and a 590 nm emission filter. Sperm cells with the fragmented DNA were then denoted by large and dispersed spotty halos, whereas tiny, dense halos represented sperm as the unfragmented DNA [34].

Sperm PRM Deficiency Assay
Sperm PRM deficiency was evaluated using the Chromomycin A 3 (CMA 3 ) staining method. A total of 90 frozen semen straws (five straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used in this stage. Sperm PRM deficiency was assessed by smear preparations of 5-10 µL of semen on a slide, then fixed in Carnoy's solution (methanol: glacial acetic acid (3:1)) for five min at 4 • C. Then, the slides were stained in CMA 3 dye solution (0.25 mg/mL CMA 3 in McIlvane's buffer (pH 7.0) supplemented with 10 mM MgCl 2 ) for 20 min. Next, the slide was rinsed in McIlvane's buffer (pH 7.0) and air-dried. Finally, 500 sperm cells per slide were observed under a fluorescent microscope using a 470-490 nm excitation filter and a 510 nm emission filter. Sperm with deficient PRM (CMA3+ positive) was indicated by bright green fluorescence on the head, whereas dull green indicated sperm with intact PRM (CMA3−negative) [35].

PRM1 Gene Expression Analysis
A total of 144 frozen semen straws (eight straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used in this stage. Next, each frozen semen was thawed in a water bath for 30 s at 37 • C, washed three times with phosphatebuffered saline (PBS), and pelleted (about 25 × 10 6 sperm cells/mL) by centrifugation at 16,000× g for 15 min. After that, the total RNA was extracted using the TRI reagent, as recommended by the manufacturer (Zymo Research, Irvine, CA, USA). The NanoDropTM One/OneC Microvolume UV-Vis Spectrophotometer (Thermo Scientific, Marsiling Industrial Estate Rd 3, Singapore) determined the total RNA amount and purity (Thermo Scientific, Marsiling Industrial Estate Rd 3, Singapore). According to the manufacturer's protocols, the SensiFASTTM cDNA Synthesis Kit (Bioline Ltd., Memphis, TN, USA) was also used for cDNA synthesis. A total of 20 µL of cDNA obtained from this reaction was ready for RT-PCR. Next, the NanoDrop One/OneC Microvolume UV-Vis Spectrophotometer (Thermo Scientific, Marsiling Industrial Estate Rd 3, Singapore) was used to assess the total cDNA amount and purity. The quantitative real-time PCR (qPCR) was also used to determine the transcripts' quantity, and the reactions were performed using the SsoFastTM EvaGreen Supermix (Bio-Rad Lab, Hercules, CA, USA). The genes identified in this study were PRM1 (BC108207; forward: 5 -AGATACCGATGCTCCTCACC-3 and reverse: 5 -GCAGCACACTCTCCTCCTG-3 ) [22] with PPIA (XM_001252921.1; forward: 5 -ATGCTGGCCCCAACACAA-3 and reverse: 5 -CCCTCTTTCACCTTGCCAAA-3 ) as housekeeping gene [27]. The 2 −∆∆CT [36] was used to assess the relative expression levels of the PRM1 gene, which were normalized to the housekeeping gene PPIA expression.

PRM1 Protein Assay
A total of 108 frozen semen straws (six straws/bull) from six Limousin bulls, six Holstein bulls, and six Ongole Grade bulls were used. Each frozen sperm was thawed in a 37 • C water bath for 30 s, washed twice with PBS, and pelleted (about 25 × 10 6 sperm cells/mL) by centrifugation at 700× g for 15 min. The amount of PRM1 protein was then measured in sperm pellets using the enzyme immunoassay (EIA) technique, according to Vet. Sci. 2022, 9, 111 5 of 15 the manufacturer's protocols (Bovine PRM1, MyBioSource, Inc., San Diego, CA, USA) [20]. The prepared sperm pellets were briefly added to the appropriate wells.
Furthermore, the reaction wells were closed and hatched in an incubator (37 • C) for 90 min. After that, the EIA plate was washed twice, then 100 µL of antibody solution was added and covered with adhesive tape on each well. Next, the EIA plate was re-hatched in the incubator (37 • C) for 60 min and then washed thrice. A total enzyme solution, 100 µL, was poured into each well, closed, and re-hatched in the incubator (37 • C) for 30 min. Washing was repeated five times on the EIA plate; then, color reagent solution was added and hatched again in the incubator (37 • C) in the darkroom for 30 min. Finally, the color C reagent mixture mixed thoroughly in each well. The analysis was conducted using an EIA reader with a wavelength of 450 nm in 10 min.

Statistical Analysis
The fertility score (%CR) data for each bull breed were analyzed using Microsoft Excel (Microsoft Office Pro Plus 2019 Microsoft). The differences in the mean number of breeding, fertility score (%CR), semen quality parameters, SDF, PRM deficiency, the abundance of PRM1 protein, and relative expression of PRM1 mRNA in the FH and LF bulls were analyzed using the t-test method. The Pearson correlation analysis examined the overall association between the parameters evaluated and the bulls' percentage CR. A scatter plot matrix graph presented the relationship between %CR, PRM1 protein, and mRNA. The t-test method, Pearson correlation analysis, and scatter plot matrix were obtained using the Statistical Package for the Social Sciences (v.25.0, IBM, Armonk, NY, USA). The data were presented in the form of mean ± standard error.

Discussion
Fertile bulls are determined by the ability of a bull to produce sperm capable of fertilizing the oocytes [37] and have a new calf [38]. The fertility decline in bulls impacts cows' low conception level, resulting in low productivity and economic problems related to the livestock industry [38,39]. Chenoweth [40] and Parkinson [41] showed that fertility data and extensive progeny records in cattle prove the inability of superior bulls to produce a maximum %CR, even when the applicable standards are met by sperm motility and morphology, similar to our study's results. The semen used is produced from superior bulls that underwent the previous selection process with fertility scores that have not reached a good %CR category ( Table 1). The quality of post-thawing semen significantly resulted in PM showing a percentage exceeding 40%, quality control of frozen semen used for the AI program in each breed of bulls in the study (Table 1). This value meets the minimum PM requirements of frozen semen used for the AI program, according to the Indonesian National Standard [3] and Zewdie et al. [42]. However, the value exceeded the standard; it did not produce a maximum fertility score. Diskin [6] and Butler [43] reported that a good fertility score reached at least 70% of 100% of the first inseminated cows.
Similar results were previously reported [4], showing that the fertility score of several Holstein bulls in Indonesia was approximately 21-35%, including in the LF bulls category. This result contradicted Rosyada et al. [4], who reported no correlation between PM and %CR (fertility); however, they showed a close correlation between the two parameters (p < 0.01) ( Table 2). Moreover, it is undeniable that only the motile and progressive sperm can pass through the cervix and penetrate the cumulus and the zona pellucida for fertilization to occur [44].
In addition to PM, semen quality parameters such as viability and plasma membrane integrity showed a significant difference (p < 0.05) between HF and LF bulls (Table 1) associated with %CR (Table 2) in each breed. The outcomes of this study revealed a higher percentage value of viability and integrity of the plasma membrane than the previous research's average [4,5]; however, it has not yet reached the maximum fertility level. This result is comparable to a previously published report by Pardede et al. [5], who discovered that even though the percentage CR was less than 70%, semen quality remained a critical aspect of bull fertility. Again, however, the results of this study aligned with the previous findings that showed the inability of conventional semen quality assessment to facilitate the fertility of a bull.
Disturbances exist during the spermatogenesis process in bulls, impacting the molecular defects that affect the quality and production of sperm, consequently decreasing fertility and even causing infertility [9]. The molecular defects in uncompensated sperm and sex-steroid enzyme alteration influence sperm's capacity to fertilize the egg, contributing to the embryo's normal early development [45][46][47]. Additionally, the non-compensable factors, such as molecular defects in sperm, cannot be addressed by raising the number of sperm per insemination instead of compensable characteristics, which may be solved by increasing the number of sperm per insemination [48][49][50][51]. PRM, the primary protein packaging for sperm DNA, is a component in sperm that plays a crucial role in determining these uncompensated traits and is also associated with molecular defects in sperm [8,10,12,13,25,28]. Additionally, hypercondensation of sperm chromatin occurs, during the elongated spermatid phase of spermiogenesis, involving the replacement of histones by transient transition proteins [52], then replaced by at least 85% by PRM until maternal histones return them after fertilization [53].
Proper DNA protamination of sperm influences sperm chromatin dynamics in mammals [23]. Furthermore, disturbances in this process can affect the sperm maturation process in the epididymis, causing an impact on sperm dysfunction and male subfertility, including infertility [54]. Immature sperm contains more histone-packed chromatin regions more likely to display SDF than well-PRM sperm [55]. Our study evaluated SDF using AO staining and the Halomax test (Figure 1). Evenson [56] reported that sperm chromatin structure assay (SCSA) is the most stable SDF assessment method, whereas AO staining is the least sensitive method compared to other methods. The Halomax test is the simplest and easiest method of evaluating SDF, which is included in a kit combined with various cell dyes primarily used with light and fluorescence microscopy [56]. The instability of sperm chromatin packaging also causes SDF and dispersion, forming a large halo [57]. Garcia-Macias et al. [34] reported that evaluating SDF using the Halomax test is one among four fertility predictors. This study did not use SCSA because of its expensiveness. It is practically not affordable for application in the field and requires flow cytometry compared to the Halomax test method and AO staining.
The SDF assessment with AO staining showed a significant increase (p < 0.05) in LF bulls than in HF bulls (Figure 2A), with the threshold value reaching 3.27% in LF bulls. In a study finding, the Halomax test was used to evaluate SDF on LF bulls reporting threshold value substantially higher (p < 0.05) than on HF bulls (Figure 2A), with the value reaching 3.49% on LF bulls. Dogan et al. [13] reported that the Halomax test method showed a negative correlation with fertility in bulls, in low SDF bulls with LF. Our study also found that SDF percentage using both techniques was adversely linked (p < 0.001; p < 0.000) with %CR for each breed of bull (Table 2). However, previous studies reported the various effects of severe SDF, such as reduced fertility rates, poor embryo quality, and decreased pregnancy rates [58]. Cho et al. [59] and Boe-Hansen et al. [60] also reported early embryonic death and smaller fetal size due to severe SDF.
Several factors cause spermatozoa DNA fragmentation, such as hormones, age, infection, increased reactive oxygen species, chemical/toxic exposure, smoking, drugs, testicular hyperthermia, apoptosis, and protamine deficiency during spermatogenesis [51]. As previously discussed, the high SDF levels in sperm are related to the level of maturity of the sperm due to impaired protamination of the chromatin structure of sperm. However, Simon et al. [58] report showed a correlation of abnormal expression or low PRM content in sperm with SDF. Therefore, this study also evaluated the level of PRM deficiency indirectly using the CMA 3 method (Figure 1). The guanine-cytosine-specific fluorochromes from the CMA 3 assay competed with PRM binding sites on DNA, showing that chromatin packaging under PRM deficiency conditions will cause binding of chromomycin to DNA (CMA3+) [61]. In sperm with DNA chromatin packaging compacted and stabilized by PRM, arginine, which is rich in guanine-cytosine (CMA3−), abundant in PRM, would inhibit the dye CMA 3 [62,63]. However, using CMA 3 as an indirect assay of PRM content in sperm associated with SDF and fertility is widely used [64][65][66][67][68].
Our study's findings agreed with earlier research, where LF bulls in each bull breed exhibited a higher percentage of CMA3+ or PRM deficiency (p < 0.01) than HF bulls ( Figure 3A). A negative correlation (p < 0.000) shown between CMA3+ and the %CR in all breeds of bulls was used in this study (Table 2). In this study, the results of the indirect PRM assessment were also confirmed by identifying PRM1, both at the mRNA ( Figure 3B) and protein levels ( Figure 3C). PRM1 mRNA was highly expressed (p < 0.05) in HF bulls than in LF bulls in all bull breeds during this study ( Figure 3B). At the protein level, PRM1 protein was also seen to be significantly more abundant (p < 0.05) in HF bulls compared to LF bulls in all breeds of bulls ( Figure 3C). A positive correlation (p < 0.000; p < 0.009) ( Table 2) and linearity in the linear regression curve graph ( Figure 4) were also shown between mRNA expression and PRM1 protein abundance with %CR. Our results are similar to those reported in a previous study in Holstein bulls, showing transcription of PRM1 mRNA with low concentrations in LF bulls [12]. Additionally, Dogan et al. [13] reported that PRM1 was detected in low concentrations in bulls with LF rates with an increased SDF at the protein level.
The condition of PRM deficiency or aberrant protamination of sperm resulting in LF conditions or even infertility cases is associated with several plausible causes, including disruption of transcription, translation, and synthesis processes [69][70][71][72]. Recently, research has linked defective protein synthesis to abnormal mRNA retention, implying that abnormalities in PRM translation control may lead to PRM inadequacy in infertile males [73]. Additionally, it is reported that abnormal histone ratios resulting from the failure or complete failure of the protein remodeling process in sperm chromatin, in which PRM dominates 85% of the sperm nucleus protein, is a cause of PRM aberration that causes male infertility [74]. In other species, PRM haploinsufficiency in transgenic mice reportedly impacts changes or disruption of spermatogenesis and result in infertility [75]. However, unlike in mice and humans, where another variant of PRM, PRM2, must have a similar ratio as PRM1, and a ratio that deviates at the protein and mRNA levels, will impact infertility [76][77][78][79]. PRM1 in bulls is the only PRM variant that plays a direct role in the normal function of fertile sperm [12,13]. Ganguly et al. [27] and Pardede et al. [20] also proved that PRM1, both at the mRNA and protein levels, was the most critical PRM variant in normal sperm function in bulls.
Nevertheless, specifically, the regulation and mechanism of PRM1 in sperm remains not fully understood [29] necessary to be studied further. Steger et al. [80] stated that abnormal expression or decreased expression and concentration of PRM1 resulting from the abnormal function of transcriptional regulators, translation, or post-translational modifications affect PRM and various genes during spermatogenesis. Therefore, it is not surprising that PRM can be a "checkpoint" during spermiogenesis, and abnormal PRM expression will impact the rate of apoptosis [80]. Increased apoptosis affects poor semen quality associated with fertilization and pregnancy after IVF [81]. However, this study supports the hypotheses that have been reported so far regarding the importance of PRM1 in normal spermatozoa function and its relationship to fertility in bulls, especially bulls used for AI programs in Indonesia. As found in this study, PRM1 proved to be closely related to fertility, with bulls still classified as subfertile or LF, even though the semen quality was conventionally categorized as suitable for the AI program. Moreover, the combination of assessment with a gene or protein analysis approach with semen quality assessment, including SDF assessment, can be the best choice in determining the fertility of bulls.

Conclusions
In conclusion, inadequate or low sperm chromatin protamination at both mRNA and protein levels was associated with defects in sperm chromatin condensation, found with increased SDF, and coinciding with a decrease in the %CR (fertility score) in bulls. Therefore, considering that this research aimed to find candidate fertility markers that accurately determine bulls' fertility and can be used in the bull selection process, especially in Indonesia, PRM1 shows to be a promising candidate in terms of fertility markers. Furthermore, to the best of our knowledge, this is the first work in Indonesia to demonstrate correlations in the mRNA expression and protein content of sperm PRM1 from HF compared to LF bulls. Moreover, it is not only in one breed of cattle but also represents commodity groups of cattle breeds in Indonesia, such as exotic beef cattle (Limousin), dairy cattle (Holstein), and local cattle breeds (Ongole Grade).