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Dietary supplementation of powdered and encapsulated probiotic: In vivo study on relative carcass, giblet weight and intestinal morphometry of local duck

This research was aimed to evaluate the effect of dietary supplementation of either powdered or encapsulated probiotic on relative carcass, giblet weight and intestinal morphometry of local duck. One hundred twenty male day old duck (DOD) were distributed to 6 different dietary groups, included 2 probiotic forms of either powdered (T1) or encapsulated (T2) and 3 levels: 0% (L0), 0.2% (L1), 0.4% (L2). They were reared using pen cages for 42 days (6 weeks). Observed variables were relative carcass, giblet weight (gizzard, heart, liver) and intestinal morphometry (villus height, villus width, crypt depth). Data were analyzed by Nested of Completely Randomized Design ANOVA and if there was significant effect followed by Duncan’s Multiple Range Test (DMRT). The result showed that there was no significant effect (p > 0.05) of the form of either powdered or encapsulated probiotic on relative carcass, giblet weight, and intestinal morphometry. However, increasing level of probiotic have significant effect (p < 0.05) on relative carcass, villus height, and villus width, but did not significantly affect giblet weight and crypt depth. In conclusion, supplementation of either powdered or encapsulated probiotic has similar result, but it is suggested to use 0.4% of encapsulated probiotic (4 kg ton of feed) in local duck diet.

Introduction
Local duck serves animal protein source of human. Nowadays, food safety and healthy from livestock products are the success key for sustainable livestock production system. Dietary synthetic feed additive has been used as an effective means to improve productivity, but it was banned by Indonesian government regulation through Permentan No. 14/2017. This ban due to pathogenic contamination, bacterial resistant in the end product and an effort to create sustainable poultry farming. Moreover, the use of antibiotics causes residual veterinary drugs in an animal product like meat, milk, and eggs (Jeong, Kang, Lim, Kang, & Sung, 2010).
Probiotics proposed as an alternative natural growth promoter due to probiotic is non-pathogenic livemicroorganism which gives many health benefits to the host. Several studies have shown that the use of probiotics in the feed could improve the performances, population of micro flora, white blood cells, cholesterol content (Bansal & Bilaspuri, 2011;Natsir, Sjofjan, Widodo, Ardiansah, & Widyastuti, 2019). Using synthetic materials, such as butylated hydroxyanisole and butylated hydroxytoluene, which have been widely used in feed, was prohibited due to safety reason. Recent studies reported that using alter materials from bio-resources such as probiotic, prebiotic, phytobiotic were suggested. Antioxidant properties from Lactobacillus casei spp. (i.e. L. casei 114001) and Lactobacillus fermentum ME-3improved the ability to suppress oxidation of luminol, microsomal lipid peroxidation (consecutively was 43.0-65.8%, 57.9-89.5) and decreased of antioxidant capacity of blood plasma, liver and small intestines of animals elevated while malondialdehyde (MDA) content in blood plasma. The cultured-supernatant, intact cells, and intracellular cell-free extracts of Bifidobacterium animals were found to scavenge hydroxyl radicals and superoxide anion in vitro while enhancing the anti-oxidase activities of mice as in vivo treatment (Shen et al, 2011). Antioxidant which expressed by probiotics were reported can improve production performance of broiler. Dietary supplementation of Lactobacillus acidophilus D2/ CSL (CEST 4529) were reported increase body weight at 28 d, daily weight gain and decrease feed conversion ratio also daily feed intake of broiler (De Cesare et al., 2017).
Protecting probiotic from unsupported environmental condition in the inside of gastrointestinal tract of broiler was important to be observed. Because, not all of probiotic that given to broiler would be adsorbed by target organ (small intestines), this was caused the barrier from pH condition inside of GIT, acidic-bile, enzyme, and another environmental condition that reduced amount of probiotics before entering to the target organ. After that, it has reduced viability and quantity-loss of probiotics (Corona-Hernandez et al., 2013;Gbassi & Vandamme, 2012).
Encapsulation method is potentially method that can improve the viability and survivability of broiler. This method coated the probiotic to promote immune function and improve growth performances of the broiler. In this research, we use either without encapsulation or encapsulation technology to protect probiotics. Because encapsulation technology has been observed to be a protector for corematerial (either pro or prebiotic), this is an effective way to maintain viability, survivability and protect from environmental barriers inside, against pathogenic bacteria, enhance immune function and growth performances (Natsir et al., 2019;Ritzi, Abdelrahman, Mohnl, & Dalloul, 2014;Yazhini, Visha, Selvaraj, Vasanthakumar, & Chandran, 2018;Zhang et al., 2015). Supplementation of either powdered or encapsulated probiotic is expected to improve production performances. In this research, we would like to observe it then performed by relative carcass, giblet weight measurements and morphometric assay on the small intestine of local duck.

Local and time
This research was conducted within 2 months, during March-April 2017. Preparation for probiotic, either powder or encapsulated were conducted in Laboratory of Animal Feed and Nutrition, Faculty of Animal Science, University of Brawijaya. Testing TPC (Total Plate Count) was conducted in Laboratory of Microbiology, Faculty of Animal Science, University of Brawijaya. The in vivo test was conducted in Sumbersekar's Field Laboratory, Faculty of Animal Science, University of Brawijaya which located in Sumbersekar Village, Dau Sub-district, Malang Regency. The temperature ranged for 20-26 o C and its humidity ranged for 60-80%.

Birds
Birds used in this research were a hundred twenty local male day old duck (DOD). The average weight of DOD was 37,81 ± 7,03%. The DOD was obtained from Karangploso, Batu City.

Feed
The basal diet used consisted of corn, rice bran, meat bone meal, soybean meal, salt, grit, DL-methionine, lysine, salt, palm oil, and premix. The result of proximate analysis of feed content is shown in Table 1.

Probiotic
In this research, we used multistrain of powdered-probiotic, consist of Lactobacillus fermentum, Lacobacillus acidophilus, Bacilus spp) that was obtained from commercial probiotics from Animal Nutrition and Feed Laboratory, Faculty of Animal Science, University of Brawijaya. TPC (Total Plate Count) testing was performed, and the viability obtained from this probiotic powder was >10 6 cfu g -1 . The process of making probiotic powder using Sjofjan (2014). The encapsulated probiotic procedure is using the method (Natsir, Osfar, Ilham, & Siti, 2018). Materials which used were probiotics, gum arabic, whey protein, and BHT (Butylated Hydroxy Toluene). The process of preparing the probiotic encapsulation, including mixing of 75% gum arabic and 25% whey and 0.06% BHT. After that, liquid probiotics prepared through the fermenter tube and carried out optimization for 1 hour at 40 o C. Then mixing with encapsulant and mix for 3 hours at 37-40°C. Acta Scientiarum. Animal Sciences, v. 42, e47140, 2020

Housing
The cage used in this research is a cage of opened house; the research cages were 70 cm x 70 cm x 70 cm by 30 units each and separated. Then, the brooding cage used 2.5 m x 2.5 m to 3.5 m -3.5 m. Each unit is equipped with a 20 watts incandescent lamp which is used as a heater and lighting at the grower phase

Experimental Design
Method which used in this research was Nested of Completely Randomized Design (CRD) with two main factors, either form or level concentration of probiotic. Forms which used were powder (T1) and encapsulated (T2). Meanwhile, level concentration (L) which used were 0%, 0.2% and 0.4%. Each treatment consist of 5 replications, each replication consist of 4 birds. Treatment is given while the ages of duck were 2 weeks-6 weeks. Feed and drink were given ad libitum. The experimental method showed below: T1L0: basal feed + 0% powder probiotic T1L1: basal feed + 0.2% powder probiotic T1L2: basal feed + 0.4% powder probiotic T2L0: basal feed + 0% encapsulated probiotic T2L1: basal feed + 0.2% encapsulated probiotic T2L2: basal feed + 0.4% encapsulated probiotic

Variables
The variables observed in this research were relative carcass, giblet weight (gizzard, heart, and liver), intestinal morphometry (length villi, width villi, and depth crypth) in small part of ileum. The relative carcass (%) was determined by carcass as a percentage of live body weight (Falaki, Shams, Dastar, & Zrehdaran, 2010). The giblet weight was measured according to Yadav, Meenu, Maousami, and Karnam (2018). The morphometric measurements were performed using a microscope (Olympus) at an objective magnification of 4 times with the help of a video microscope (Video measuring gauge IV-560, for Company Limited) at 5 fields for each preparation.

Data analysis
Data were analyzed by Analysis of Variance (Anova) Nested of Completely Randomized Design (CRD). When significant effect appeared followed by Duncan's Multiple Range Test (DMRT).

Results and discussion
In this experiment, using form and level model (powdered and encapsulated) of probiotic and its response to relative carcass, giblet weight and intestinal morphometry showed on Table 2. and Table 3.

The effect of probiotic supplementation either powdered or encapsulated (form) on relative carcass
The effect of either powdered or encapsulated probiotic on relative carcass of local ducks were summarized in Table 2 and Table 3. The result of relative carcass showed that there was no significant effect (p > 0.05). While, level of either powder or encapsulated (Table 3) probiotics on relative carcass revealed that the treatments had significant (p < 0.05). Several studies explained that the relative carcass increased by increasing the protein content of basal feed. Supplementation probiotic bacteria could be enhanced the availability of protein. Similarly nutrient content such as metabolic energy, crude fiber and crude protein in the basal diet of the treatment seemed to be responsible for the divergent results. The feed containing higher crude fiber decreased carcass weight than feed with a lower crude fiber. The differences in quality of feed and growth rate seemed to contribute to the growth performance. In the previous study (Sarangi et al., 2016) reported that supplementation pre-probiotic had no significant effect on carcass of broilers. Furthermore, a non significant effect was found during supplementation Bacillus subtilis on carcass traits (Yadav et al., 2018). In collaborated with prebiotic on laying hen, Natsir et al. (2018) also reported that no effect on laying hen performances. Alkhalf, Alhaj, and Al-Homidan (2010) reported that higher level of the supplementation probiotic to broilers in the levels of 0.8 -1 g kg -1 was found to be better than control. Increasing levels of encapsulated probiotic could improve viability and stability, increase protection against pathogenic resulting in improving in nutrient utilization, gut environment, and growth performance (Natsir et al., 2018;Zhang et al., 2015).

The effect of probiotic supplementation either powdered or encapsulated (form) on giblet weight
The effects of either powder or encapsulated probiotic on gizzard weight of local ducks were summarized in Table 2. Statistical analysis of gizzard and heart weight showed there was no significant (p > 0.05) difference between experimental groups. This indicated that inclusion of probiotic and their combination did not stimulate the internal organ weight (Parsa et al., 2018). This finding was in line with (Shabani, Nosrati, Javandel, & Kioumarsi, 2012) that different level of probiotics had no statistically effect on gizzard weight. Similarly, Midilli et al. (2008) reported was no significant impact on gizzard relative weight during of probiotics and mannan-oligosaccharides in broiler chicks. A non-significant impact was observed by (Karaoglu & Durdag, 2005) that dietary probiotic Saccharomyces cerevisiae had no significant effect on gizzard weight, while the age of slaughter affected to the gizzard relative weight compared to control group. The factors affect gizzard weight are breed, genetics, age, sex, individual status and feed intake. Moreover, feeding poultry more than the requirement cause extra-digestion and it would affect the size of gizzard due to the thickening of the muscle, type of feed particle size (mash, crumble or pellet) affected giblet weights, smaller particle size decrease gizzard activity (Tuli, Sandhu, Kashyap, & Sharma, 2014). There was no significant difference observed by Sarangi et al. (2016) that dietary supplementation prebiotic, probiotic and symbiotic had no significant effect on liver weight of Cobb broilers. In contrast, Seifi et al. (2017) reported that addition pre-probiotics in diets comprising rice brand was increase the relative heart weight compared to the control (with no pre-probiotic). Increasing heart weight also found during supplemented Bacillus subtilis and Enterococcus faecium to broilers compared to the control group. Meanwhile, heart enlargement in broiler was affected by heat stress (Hatab, Elsayed, & Ibrahim, 2016;Khan et al., 2016). The divergent result might be influenced by strain, method of probiotic preparation, level of treatment, and basal composition (Zhang, Zhou, Ao, & Kim, 2012).
Supplementation of either powder or encapsulated probiotic on liver weight summarized in Table 2. The result demonstrated no significant (p>0.05) difference among the different experimental groups. Increasing level of probiotic did not significantly affect to liver weight due to the probiotic non-toxic or antinutritionfree. A presence of toxic in the basal feed increase in metabolic rate and causes abnormalities of organ weight as a result of reduce toxic effect. Feeding 0.5 and 0.8 ppm aflatoxin (AFB1) in broiler chicken was significant increase the relative weight of heart during period of 42 days (Lakkawar, Narayanaswamy, & Satyanarayana, 2017). Accumulation of lipids in the hepatocytes would change the heart size due to the severe fatty change, lipidosis, and inflammatory reaction (Lakkawar et al., 2015). This result in agreement with Awad, Ghareeb, Abdel-Raheem, and Böhm (2009) explained that supplementation probiotic had no significant difference in the weight of liver as compared to the control group. Increasing beneficial bacteria such as Lactic acid probiotic that decrease the activity of acetyl-CoA could reduce the lipid synthesis (Zhou et al., 2009).

The effect of probiotic supplementation either powdered or encapsulated (form) on intestinal morphometry
The effect of either powder or encapsulated probiotic forms on villus height (μm), villus width (μm) and crypt depth (μm) showed in Table 2. The effect of the use of either powdered or encapsulated probiotic showed that either powdered or encapsulated probiotic has no significant effect (p > 0.05) on the morphometry of the small intestine (villus height, villus width, and the crypt depth). There was appropriate because either powdered or encapsulated probiotic has the same ability to repair the local duck's gut microvilli. This research was supported by (Matur & Eraslan, 2012) which reported that growth of microvilli affected by several factors such as age, sex, and type of animal. Moreover, feed nutrients, environmental conditions of the cage, humidity, temperature and natural factors such as weather and seasons. A study reported by Maiorka et al. (2016) said that difference villus height due to age phase, it also was reported that the height age villi 60 wks longer than the age of 30 wks.

The effect of either powdered or encapsulated probiotic (level) on relative carcass
The effect of level of either powder or encapsulated (Table 3) probiotics on relative carcass showed there was significant effect (p < 0.05). This may due to the level of addition improve body weight and greater carcass weight obtained. As increasing the levels of probiotic used increased the relative carcass due to the presence of probiotics in the feed could improve the digestibility of nutrients by producing bacteriocin as an antibacterial that altering the growth of pathogenic bacteria. In the gastrointestinal tract, probiotic would break down proteins and carbohydrates into amino acids, N, and the soluble carbon that require synthesizing of proteins. Increased protein digestibility affects the improvement of protein metabolism, thus directly increasing the protein synthesis of meat.

The effect of either powder or encapsulated probiotic (level) on giblet weight
The effect of levels of either powder or encapsulated (Table 3) probiotics on giblet weight showed there was no significant difference (p > 0.05). Although increasing levels used tended to increase gizzard, heart, and weight liver relatively. This may due to the addition of different levels amount of different probiotic forms ranged between 0-0.4% did not significantly affect the weight of giblet. Moreover, indicated that the same nutrient content in the feed of dietary such as protein and fat content, age of slaughter, and antinutrition. Mc-lelland (1990) said that factors affected were size, color, and consistency of liver such as breed, genetics, age, sex, individual status and feed intake. Sarangi et al. (2016) reported that liver weight and gizzard weight in Cobb broilers under their study had no significantly different, then were agreed with Sahin, Kaya, Unal, and Elmali (2008) and Saiyed et al. (2015) that there was no effect using mixed probiotic and prebiotic in carcass quality of quail and broiler.

The effect of either powder encapsulated probiotic (level) on intestinal morphometry:
The effect of level of either powder or encapsulated (Table 3) probiotics on the villus height and villus width showed were significant effect (p < 0.05), but did not significantly affect (p > 0.05) to the crypt depth. There was assumed that the level of feed supplemented contains more probiotics, thus optimizing the growth of the villi due to probiotics are more susceptible to deterioration of viabilities before entry into intestinal microvilli. In addition, the villus width is also determined by the basal feed content consumed. This is in contrast to research conducted Harimurti of probiotic supplementation could increase villi width. Dong et al. (2016) reported that disruption of GIT epithelial cells causes micro-encapsulation of Enterococcus faecium does not work on the crypt. Another reason have reported that several aspects such as increased mRNA expression regulation of MUC2, then induced mucus protein secretion.

Conclusion
Supplementation of either powdered or encapsulated probiotic resulted similar result on relative carcass, giblet weight and intestinal morphometry. Using 0.2% and 0.4% level of encapsulated probiotic on relative carcass, villus height and villus weight better than powdered probiotic


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

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The relationship of body condition and chewing time with body weight, the level of plasma cocaine and amphetamine regulated transcript, leptin and energy metabolites in cows until reaching the lactation peak

This study examined the relationship of body condition and chewing time (CT) with body weight (BW), the level of cocaine-and amphetamine-regulated transcript (CART), leptin and energy metabolites in cows until reaching the lactation peak. The results showed the greatest loss of BW between days 11 and 45 of lactation and a decrease in the body condition score (BCS) until day 75. Chewing time showed an increase from day 45 with the highest values after lactation peak. The CART and leptin concentrations demonstrate a reduction of both indices (P < 0.05) between days 11 and 75. The function of leptin as a factor positively correlating with BW and BCS was found. In the heaviest individuals and those with higher BCS, the blood leptin levels were higher. The results of beta-hydroxybutyrate (BHBA) indicate that cows with the lowest BCS had the most intensive energy transformation. This led to a higher BHBA concentration compared to the cows with high BCS (P < 0.05). The obtained results show that CART was most strongly negatively associated with CT (P < 0.05). For leptin, the tendency was the opposite and the correlation with CT was not significant. The results suggest that CT may be stronger regulated by CART, which has anorectic properties, than by appetite inhibiting leptin. Significant decrease of body condition during lactation is a great problem for dairy farmers. The explanation of the issue of the participation of CART and leptin in the regulation of body’s energy homeostasis may therefore be of importance for milk production. Blood indicators, energy balance, milk production, neuropeptide Metabolic profile indicators are of great importance for early identification of energy metabolism disturbances in cows. Knowledge of the processes regulating the secretion of milk and physiological factors determining fat tissue accumulation is particularly important in high-yielding cows. In practice, despite the use of high-energy diets, a strongly negative energy balance is observed in these animals until lactation peak is reached. In addition, it is accompanied by reduced dry matter (DM) intake which increases the energy deficit even more, and insufficient coverage of the organism’s nutrient needs (Ellis et al. 2006; Wathes et al. 2007; Leblanc 2010). In response to negative DM intake, a strong loss of the body condition score (BCS) is commonly observed (Patton et al. 2007). This situation results in a decrease in the level of leptin in the blood and the activation of energy reserves accumulated in fat (Vargová et al. 2015). It can also negatively affect the functions of many other organs (Roche et al. 2007). Leptin is the main regulator of feed intake, an inhibitor of lipogenesis and the main stimulator of lipolysis (Ahima and Flier 2000; Ingvartsen and Boisclair 2001; Chilliard et al. 2005). However, leptin functions may be somewhat attenuated by anorectic agents, including the cocaineand amphetamineregulated transcript (CART). It is considered as factor affecting the suppression of appetite (Brady et al. 1990; Hwang and Guntz 1997). By regulating appetite, CART has an effect on feed intake and chewing time (CT) which determine the rumen metabolism and ACTA VET. BRNO 2020, 89: 31–38; https://doi.org/10.2754/avb202089010031 Address for correspondence: Beata Głowińska Department of Animal Physiology, Physiotherapy and Nutrition University of Science and Technology Mazowiecka 28, 85 084 Bydgoszcz, Poland Phone: +48 52 374 9725 E-mail: bglow@utp.edu.pl http://actavet.vfu.cz/

Metabolic profile indicators are of great importance for early identification of energy metabolism disturbances in cows. Knowledge of the processes regulating the secretion of milk and physiological factors determining fat tissue accumulation is particularly important in high-yielding cows. In practice, despite the use of high-energy diets, a strongly negative energy balance is observed in these animals until lactation peak is reached. In addition, it is accompanied by reduced dry matter (DM) intake which increases the energy deficit even more, and insufficient coverage of the organism's nutrient needs (Ellis et al. 2006;Wathes et al. 2007;Leblanc 2010). In response to negative DM intake, a strong loss of the body condition score (BCS) is commonly observed (Patton et al. 2007). This situation results in a decrease in the level of leptin in the blood and the activation of energy reserves accumulated in fat (Vargová et al. 2015). It can also negatively affect the functions of many other organs (Roche et al. 2007). Leptin is the main regulator of feed intake, an inhibitor of lipogenesis and the main stimulator of lipolysis (Ahima and Flier 2000;Ingvartsen and Boisclair 2001;Chilliard et al. 2005). However, leptin functions may be somewhat attenuated by anorectic agents, including the cocaine-and amphetamineregulated transcript (CART). It is considered as factor affecting the suppression of appetite (Brady et al. 1990;Hwang and Guntz 1997). By regulating appetite, CART has an effect on feed intake and chewing time (CT) which determine the rumen metabolism and the energy balance in cattle (Hunter et al. 2004;Nikkhan 2011). One of the sources of CART are neurosecretory cells (DNES) in the hypothalamus and other tissues (e.g. gastrointestinal tract) that release CART into the blood (Kasacka and Piotrowska 2012;Janiuk et al. 2013). In the hypothalamus the presence of CART has been observed in nuclei responsible for nutrition or motor activity and also in the regions of the central nervous system considered to be the most important in the regulation of the cardiovascular system (Koylu et al. 1998;Kasacka and Piotrowska 2012). Peptide has also been localized in the peripheral nervous system (Wierup et al. 2007), among others locations in the nerve ganglia of the pyloric part of the abomasum in cattle. This presence has been confirmed by the studies conducted by Młynek et al. (2015). According to Elias et al. (2001), the location of CART-containing structures which are in the vicinity of leptin secreting receptors, may inhibit the transduction of the leptin signal, therefore, the excessive mobilization of fat reserves in cows during energy deficit periods may also increase the activity of the areas releasing CART (Kristensen et al. 1998;Wang et al. 1999).
Most reliable indicators of the cow's energy status are beta-hydroxybutyrate (BHBA) and glucose concentrations. The body fat mobilization in high-yielding cows is associated with non-esterified fatty acids production, which are esterified into triacylglycerols and BHBA (Sumner and McNamara 2007). According to Stengärde et al. (2008), the concentration of these parameters is in high correlation with the amount of deposited fat (BCS) during the peripartal period.
The aim of this study was to examine the relationship of body condition and CT with body weight (BW), the level of CART, leptin and energy metabolites in high-yielding dairy cows until reaching the lactation peak. The experimental hypothesis was that the concentrations of CART, leptin, glucose and BHBA are correlated with cow's fat deposition and chewing activity, and are dependent on the lactation phase.

Animals, housing, and feeding
The study was conducted under a research protocol approved by the Third Local Ethics Committee in Warsaw, No. 70/2013 of 19 December 2013.
The animals were obtained from a private farm located in eastern Mazovia. The experiment was carried out in 69 Holstein-Friesian (HF) cows whose mean production age was 2.5 lactations (± 0.9). The animals did not show any disease symptoms (ketosis, acidosis, perinatal diseases). In the analysed period of lactation, 5 post partum phases were distinguished: the first week (1 to 7 days), the second week (8 to 14 days), the second month (31 to 60 days), the third month (61 to 90 days) and the fourth month (91 to 120 days). The material for evaluation of the indices in the individual phases was acquired on days: 4 ± 1.2, 11 ± 2.1, 45 ± 3.5, 75 ± 4.4 and 105 ± 5.3 on average. About 24 h after calving, the cows were transferred to the same production group. The animals were kept in a free-stall barn with separate lying areas where they had free access to water. The cows were milked by an A3 milking robot (Lely, Maassluis, the Netherlands) and fed in concentrated feeding stations. A Juno automatic feed push-up robot (Lely) was used at the feed bunk. The average number of milkings was 2.5 ± 1.2 per day. The roughage was prepared in a feed wagon and given ad libitum (5:30 h and 17:30 h). The cows were fed using the total mixed ration (TMR) system in order to ensure the proper amount of all nutrients ( Table 1). The nutritional value of the feed was determined each time after the silos with silage were opened. The diet was formulated to meet or exceed the nutrient requirements for a lactating HF breed weighing 550 kg, according to the INRA feeding standards with the use of INRAtion Software for Ruminant Diet Calculation, version 2.03 (DJ Group, Krakow, Poland). The diet in each period of the experiment was determined based on the production of milk standardized for 4.0% fat and 3.5% protein. The average dry matter intake was determined for the group in each period of the experiment. The dry matter intake balance was calculated on the basis of the difference between the weight of given feed and the leavings (kg). Checks were carried out every few days during the experiment. The particle size in the feed was defined according to Heinrichs' procedure (2013). Particle size distribution was as follows: 19 mm: 21.5 to 23.7% ± 3.35; 8 mm: 27.8 to 28.2% ± 2.16; 4 mm: 8.7 to 9.05% ± 1.59; Pan: 39.5 to 41.8% ± 1.54. The data are mean values for all lactation periods.

Production and body condition monitoring
Transponders were used for identification of the cows in the T4C 3.7 (Lely) management software. The chewing time was measured using noseband-sensor halters (QWES-HR system; Lely). The time of feed intake (head down) was not included in the CT. The body weight was determined using a weighing platform mounted on the floor of the milking stall (A3 sensor system; Lely). Calibration of the devices was performed at the beginning of the experiment. In each period of the experiment, the mean values of the analysed factors (BW, CT and milk yield) were determined based on the data collected individually from each cow. The cows were evaluated for the amount of deposited fat using BCS (Edmonson et al. 1989;Metzner et al. 1993) in the range of 1 to 5 points (1 point = emaciated; 5 point = obese). The BCS was the mean of the ratings performed by two independent persons, carried out at the beginning of each period. For the purposes of the experiment, the division of animals into classes I, II and III in relation to the BCS and CT was made by analysing the normal distribution of a given factor and using general discriminant analysis (GDA) taking into account the analysed lactation phases (P < 0.05).

Blood collection and storage
The blood samples were acquired in the morning, on days 4, 11, 45, 75 and 105 post partum, about 1 h before feeding and about 2 h before milking. Blood was collected from the abdominal vein using a 10-ml vacuum tube with sodium heparin, and a 1.6 × 3.8-mm needle (Medlab-Products Ltd., Raszyn, Poland). After collection, all blood samples were transported to the laboratory on ice (the time did not exceed 3 h). Plasma was harvested after centrifugation at 2,000 × g for 15 min at 4 °C and frozen at -75 °C. The plasma samples were analysed for the levels of CART and the leptin hormone using the bovine specific ELISA kit (EIAab, Wuhan, China). In the ELISA, fragment 55-102 of CART was recognized. Blood for the determination of glucose was collected into tubes with sodium fluoride and sodium heparin (Medlab-Products Ltd.). The glucose content in the blood was measured using original Randox kits (Randox Laboratories Ltd, Crumlin, UK) and a UV-Vis spectrophotometer (Varian Inc., Palo Alto, CA, USA). Samples to determine BHBA were centrifuged at 1,500 × g at 4 °C for 20 min. The supernatant was collected and stored at -75 °C until it was analysed for BHBA using original Randox kits (Randox Laboratories Ltd.) and a UV-Vis spectrophotometer (Varian Inc.). All samples were measured in triplicate.

Statistical analysis
The data were subjected to statistical analysis using the Statistica 13.1 program (TIBCO Software Inc., USA). The ANOVA model with repeated measurements was applied, taking into account one of the studied factors: post partum time, BCS, or CT. A division into study groups within the factors was made using a multidimensional discrimination model. The analysis was based on the mixed linear model taking into account post partum time as a permanent effect (covariance type AR) and an animal as a random effect. The tables present the weighted mean values of the analysed indicators, standard error of the mean (SEM), and the P value. Differences between means were tested by Tukey's method (the level of significance set at 5%). Pearson's correlation coefficients were calculated for BCS and CT, including BW and blood parameters (P < 0.05).

Results
The analysis of indicators characterizing the body condition shows that up to day 45 of lactation, there was a gradual decrease in the BW (Table 2). However, the greatest loss was observed between days 11 and 45 post partum. On the other hand, BCS decreased until day 75 of lactation. At the same time, in the period from 4 to 75 days there was an increase in the daily milk production by an average of 11.7 kg. During this period, the cows most often reached the peak milk yield. After this period, the animal's condition began to improve, as evidenced by the increasing values of BW and BCS. The CT data obtained in the analysed post partum phases (Table 2) showed a gradual increase of this index from day 45 of lactation with the greatest values usually achieved after the lactation peak (day 105). The CART and leptin concentrations presented in Table 2 demonstrate a significant reduction of both indices between days 11 and 75 post partum (P < 0.05). During this period, a systematic increase in daily milk production was noted. There was no significant effect of the analysed lactation phases on post partum glucose values (P = 0.146). As for BHBA, it was shown that its concentration in the cows' blood was relatively higher in the period preceding the lactation peak (day 75 post partum). After this time, the value of this parameter clearly decreased by 0.228 mmol·l -1 on average (P < 0.05). Table 3 shows the summary of the BW results in the tested cows, the level of peptides involved in energy metabolism, the concentration of glucose and BHBA depending on the BCS. In the BCS classes (I to III), the mean values ranged from 1.89 to 3.57 points. These data indicate that in the heaviest individuals and those with higher BCS, the blood CART concentrations were lower and leptin levels were higher. The mean CART concentration in the blood plasma of cows ranked in the first BCS class (< 2.4) was 1.148 ng·ml -1 . In comparison, the blood of individuals with a BCS higher than 2.4 points contained by 0.453 ng·ml -1 lower mean CART concentration (P < 0.05). The blood of individuals ranking in the class > 2.4 points (II and III) was characterized by a higher content of leptin (P < 0.05). The glucose values differed significantly in BCS classes II and III in comparison with class I. These tendencies of changes of the analysed indicators depending on the BCS (Table 3) were confirmed by the values of the correlation coefficient presented in Table 4. The results of the BHBA concentration in the blood plasma shown in Table 3 Mean time of post partum ( SEM -standard error of the mean; BW -body weight; BCS -body condition score; CT-chewing time; CART -cocaine-and amphetamine-regulated transcript; BHBA -beta-hydroxybutyrate; a,b,c,d -means in the row with different superscripts differ significantly (P < 0.05) indicate that cows with the lowest BCS (1.89 points) more frequently had the most intensive energy transformation. This led to a higher BHBA concentration compared to cows in good condition and a consequently high BCS (P < 0.05). A decreasing tendency of BHBA serum concentration, which was observed in our studies with the simultaneous increase in BCS, was confirmed by the value of the correlation coefficient (P < 0.05, Table 3). Table 4 presents the concentrations of these compounds depending on CT. Longer CT (P < 0.05) was observed in individuals with higher BW. This was confirmed by the value of correlation coefficient (P < 0.05). The data in Table 4 show that CART was most strongly negatively associated with CT (P < 0.05). There was a clear tendency for the value of this parameter to decrease with the prolongation of CT (P < 0.05). The differences of CART between the CT classes ranged from 0.389 to 0.268 (P < 0.05). The level of glucose in individuals with a longer CT was higher, which was confirmed by the differences between the analysed CT classes (P < 0.05) and the value of the correlation coefficient (P < 0.05). The results of the negative correlation between the concentration of BCS -body condition score; SEM -standard error of the mean; BW -body weight; CART -cocaine-and amphetamine-regulated transcript; BHBA -beta-hydroxybutyrate; a,b,c -means in the row with different superscripts differ significantly (P < 0.05); * P < 0.05 CT -chewing time; SEM -standard error of the mean; BW -body weight; CART -cocaine-and amphetamineregulated transcript; BHBA -beta-hydroxybutyrate; a,b,c -means in the row with different superscripts differ significantly (P < 0.05); * P < 0.05 CART and leptin in the blood are shown in Fig. 1 (Plate IV) (P < 0.05). Fig. 2 (Plate IV) and Fig. 3 (Plate V) demonstrating the relationship between the glucose concentration in the blood show a stronger link with CART concentration (Fig. 2) than with glucose and leptin concentrations (Fig. 3).

Discussion
The function of leptin as a factor positively correlating with BW and the amount of fat accumulated in the body, was demonstrated in the studies by Daniel et al. (2002) and Delavaud et al. (2002). A higher blood leptin level in the heaviest individuals with higher BCS in the present experiment also coincides with the results reported by Reist et al. (2003) and Vargová et al. (2015). In contrast, Holtenius et al. (2003) did not find a positive correlation between BCS and blood leptin concentration.
As for BHBA, which was used to describe lipid metabolism in the body, the concentration in the blood plasma indicates that cows with the weaker body condition more frequently had the most intensive energy transformation. This led to the higher BHBA level compared to cows in good condition. A similar relationship was demonstrated in the study by Samanć et al. (2011). The decreasing tendency of BHBA serum concentration with a simultaneous increase in BCS is in line with the results obtained by Kessel et al. (2008) and Vargová et al. (2015).
Given the peculiarity of cattle digestion and the increasing energy deficit during the first weeks of lactation, high yielding cows should devote the most time to chewing food. This stimulates the functions of the digestive tract and increases the use of ingredients from feed. The effect of CT on energy metabolism may be manifested, among others, by changes in the concentration of glucose and BHBA in the blood. The level of these parameters is, however, indirectly dependent on peptides and hormones, such as CART and leptin, which are involved in the regulation of lipid metabolism, and can significantly regulate the feeling of satiety (Ahima and Flier 2000;Ingvartsen and Boisclair 2001;Chelikani et al. 2004). The strongly negatively correlation between CART and CT observed in this study can partially explain the presence of CART in the nerve ganglia of the pyloric part of the abomasum, which was demonstrated in earlier studies (Młynek et al. 2015). The higher level of glucose in cows with a longer chewing time appears to be similar to that observed in earlier studies, which found that the quantity and quality of feed had an impact on the process of chewing and determined the level of glucose in the blood of lactating cows (Frohli and Blum 1988;McGuire et al. 1995;Chelikani et al. 2004). The stability of the glucose level in the body, which is one of the most important energy management substrates, is an indicator of body metabolic homeostasis. In the present experiment, the blood glucose concentration shows a stronger correlation with the CART concentration than with the leptin concentration. Thus, it can be hypothesized that by shortening the duration of the processes related to food intake and CT, CART delays the release of glucose into blood. This results in a lower glucose concentration in the final energy metabolism balance felt as an energy deficit and induction of the mechanisms of lipid transformation in which leptin, released by adipocytes, is involved.
The negative correlation between the concentration of CART and leptin in the blood obtained in this study suggests that the functions of this anorectic neuropeptide may have an antagonizing effect on leptin signal transduction. This may partly explain the stronger and negative correlation between CART and the BCS and the weaker correlation between leptin and this index as well as the correlation with CT. These results are in line with the outcomes of the study conducted by Elias et al. (2001).
This study confirmed that both CART and leptin levels are strongly but oppositely correlated with a cow's fat deposition and are dependent on the lactation phase. In the case of CART, the correlation with BCS is strongly negative and the same relationship applies to BHBA. For leptin, the correlation with BCS is positive and the same type of correlation occurs for glucose concentration. The results obtained in the present experiment suggest that chewing may be more strongly regulated by CART which has anorectic properties, than by appetite inhibiting leptin, but to fully confirm this conclusion, it is necessary to conduct further research in this direction. The problem for dairy farmers is the reduced dry matter intake of cows until the peak of lactation is reached. This results in a negative energy balance and excessive activation of fat reserves which causes a significant decrease of body condition. The explanation of the issue of the participation of CART and leptin in the regulation of the body's energy homeostasis may therefore be of great importance for milk production.


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Effect of Seaweed Powder on the Quality of the Pineapple-Chili Sauce

This study was conducted to produce pineapple-chili sauce mixed with seaweed (Kappaphycus alvarezii) based on the best formulation, to determine nutritional composition of the control and the best formulation and to determine the effect on quality of this product. A total of 3 formulations had been developed using different composition of seaweed powder at 2.0%, 2.5%, 3.0% and were undergo sensory evaluation and physicochemical analysis to choose the best formulation. The selected and control samples were then analysed for proximate values. The increasing in seaweed powder composition influenced significantly (p<0.05) the aroma, viscosity, aftertaste and overall acceptability of the sauces. In the physicochemical analysis, increasing in seaweed powder percentage was significantly (p<0.05) influenced positively in the viscosity, syneresis and water activity while it did not affect (p>0.05) the total soluble solids, total acidity and pH. The results of proximate analysis shown the composition of the best formulation was 72.54% moisture content, 23.44 % carbohydrate, 2.70% ash, 0.81% crude fibre, 0.37% crude protein and 0.14 % rude fat showed significantly higher (p<0.05) in ash, crude protein, and crude fibre compared to control.

INTRODUCTION
Nowadays sauces become popular convenient food product among the population due to the changes in the lifestyles and the changes in the eating habits. In Malaysia, consumption of sauces has shown an increase of 75,567.5 MT in 2010to 84,565.2 MT in 2015 and is believed to be increased further to 91,028.7 MT in 2020 1. In the local market, fruit sauces had become increasingly popular as they provide various interesting natural flavour and taste profiles which meet the consumer demand. Besides that, production of fruit sauces can be defined as a way to preserve the fruits, to extend their shelf life and to avoid the wastage of fruits. However, the market for sauces had become more limited as the food producers and manufacturers produce same types of sauce and they are forced to compete as well as cannot meet the demand of consumer on trying new flavour 2. Pineapple is the main choice in the processing of fruit sauces because of its natural colour, strong flavour, high sugar content, and natural acidity which suitable be eaten as dessert 3,4. Pineapple is also rich in nutrients that can provide health benefits, such as vitamins, mineral, phenolic and fibre. In addition, pineapple is a tropical fruit which can easily found in the local market throughout the year. Thus, it had been commercially processed into products with additional values such as sauces, jam, juice, candy and vinegar 5. Seaweed is macroalgae with its economic value are increasing in the world market now. Recently, the used of seaweed is becoming popular in the food industry for the production of nutritious and functional food due to it rich of polysaccharides, mineral, fiber, protein and omega-3 fatty acid 6.7. Furthermore, seaweed is the source of hydrocolloids which usually can be used as a thickening agent, gelling agent, emulsifier, and stabilizer in various food product processing such as sauces, ice cream and soup 8. In Malaysia, Kappaphycus alvarezii is the most common type of red seaweed which had been cultivated largely in the farms around Sabah. It became high demand because it is an important source of kappa-carrageenan for industrial applications, either used in fresh or in powder form. It also is considered as a sustainable food source and a low-cost raw material 9. However, the use of seaweed is still limited in the local food industries. In local usage, seaweed mainly used in the production of salad, soup and pudding 10. The fishy smell of seaweed also makes it become unacceptable and less consumable among consumer 11. In order to make seaweed more commercialize and diversify the use of seaweed, as well as to increase the sauce variety in the market, seaweed (Kappaphycus alvarezii) powder is used as a thickening agent in the production of pineapple-chili sauce. The study was conducted to determine the best formulation of pineapple-chili sauce mixed with seaweed through sensory evaluation and physicochemical analysis, to determine the nutrient composition of the control and the best formulation of pineapple-chili sauce mixed with seaweed and to study the effect of seaweed powder on the quality of the sauce.

Materials
Pineapple, seaweed Kappaphycus alvarezii, chili and garlic were purchase from the wet market, Kota Kinabalu. Other raw materials to produce pineapple-chili sauce such as sugar, modified corn starch, xanthan gum, citric acid and sodium benzoate were purchase from Bake with Me, Jalan Lintas, Kota Kinabalu.

Preparation of Seaweed Powder
The seaweed was washed with water, dried in a drying cabinet (Thermoline TD-78T-SD, Australia) at 50°C for 48 hours and was ground using a grinder (Panasonic, Japan). Them, it was sifted using sieve shaker (Minor 1760-07, UK) to make a fine powder (0.25mm).

Preparation of Sauce
The sauces were prepared according to the formulation by 12 with modification by added seaweed powder in a range of 2.0 -3.0%. The pineapple was cleaned, peeled, sliced and blended (Panasonic, Japan) to make a puree. Chili was washed and unseeded, garlic skin was removed and they were blended together. Later, pineapple puree, chili and garlic were mixed inside a cooking pot, heated and stirred regularly. Sugar and salt were put in the pot and the mixture was boiled. Seaweed powder was added into the mixture and was stirred until dissolved. After that, citric acid and sodium benzoate were added into the mixture and the mixture was boiled. The sauce was lifted and was filled into a sterilized bottle while still hot and was closed immediately.

Sensory Evaluation
The hedonic test was conducted to determine the best formulation of the sauce among F1, F2 and F3. A total of 40 panellists were selected randomly from the Faculty of Food Science and Nutrition, University Malaysia Sabah (FSMP, UMS). The hedonic test has used a seven-point Likert scale to assess the sensory attributes (colour, taste, aroma, viscosity, aftertaste and overall acceptance) of the given sauce samples. A hedonic scale score 1 represents dislike extremely while score 7 represents like extremely. The sauce samples have been served with cucumbers and warm water was provided to rinse the mouth.

Physicochemical Analysis 2.5.1 Syneresis test
Syneresis test was conducted using the centrifugation method with centrifuge machine (Thermo Scientific, Sorvaii Biofuge Prime R) 13. A sample of 10.00 ± 0.01g was centrifuged for 30 minutes at 3000g and the percentage was calculated based on equation 1.
Where, a = weight of water separated from the sample (g) b = total weight of the sample prior to centrifugation (g)

Water activity
The water activity of the sample was measured using a water activity meter (Rotronic HygroLab) and was set at 105°C 13. Water activity was shown as equilibrium relative humidity (ERH).

Viscosity
The viscosity of the sample was determined using the Brookfield viscometer DV-l type l + Pro (AOAC, 2000). Sample of 250.00 ± 0.01g was placed into a 250ml beaker before the viscometer fixed with spindle 5 and rotation set at 30 rpm.

pH value
The pH of the sample was measured using pH meter with type BP 3100, UI TransInstrument 14 where 100 ± 0.01g sample was place in the beaker, the pH probe was then penetrated into the sample and the stable reading was indicated.

Total soluble solids
Determination of total soluble solids is carried out using a hand refractometer ATAGO type (N-2E) which has a range between 28 ° -62 °Brix 14.

Total acidity
Determination of total acidity was conducted using the titration method 15. Total acidity of the sample is regarded as a percent of citric acid and it was calculated based on the equation 2. Three replicates were performed for each sample.

2
Where, V = average volume of NaOH required to neutralize the acidity of the sample N = normality of NaOH F = factor milliequivalent citric acid (0.064) S = weight of a sample

Proximate Analysis
Control and best formulation were choosing to undergo proximate analysis which included the moisture content, ash, crude protein, crude fat, crude fibre and total carbohydrates were determined according to 15. Moisture was analysed in an oven at 105°C for 24 hours. Ash was analysed by burning the sample in a furnace at 550°C overnight. Kjedahl method was used to determine protein content while the Soxhlet method was used to determine fat content. Crude fiber was determined using the gravimetric method. Carbohydrates were calculated by the difference method which is shown in equation 3.

Statistical Analysis
All analysis done in triplicate and data were expressed as means ± standard deviations. Data were analysed by using IBM SPSS Statistics Version 22.0 and the significant difference was considered at the level of p<0.05. A hedonic test was analysed by the Friedman test followed by Wilcoxon Signed Ranks Test. Independent Group t-test was used to analyse the results of the proximate analysis. One-way ANOVA and Tukey test were used to analyse the significant differences between the samples of sauce tested.

Sensory Evaluation And Physicochemical Properties Of Pineapple Chili Sauce Mixed with Seaweed Powder
Sensory evaluation of these three formulations showed that the percentage of seaweed powder added affected several attributes measured such as aroma, viscosity, aftertaste and overall acceptance. Additional of seaweed powder at 3.0% gave significantly (p<0.05) lower aroma score due to fishy smell of the product can be detected by the panels. The viscosity of sample added with 2.5% seaweed powder was most accepted (p<0.05) by the panels due to its consistent and sticky properly on the carrier. Aftertaste of 3.0% seaweed powder added give unpleasant flavour due to the fishy taste of the sample. Seaweed has a neutral taste, thus increasing the composition of seaweed powder in the samples would not affect the taste such as sweetness and sourness 16. Overall acceptability of panel chosen F2 was the best and the detail was shown in table 1. These sensory results also are supported by the physicochemical properties of samples with total soluble solids and total acidity of sauce samples which are presented in figure 1 and figure 2, respectively. All the formulations did not show a significant difference (p>0.05) on total soluble solids and total acidity. However, there was slightly increased in total soluble solids with increasing in seaweed powder percentage as seaweed content of carrageenan which is soluble in water 17. On the other hand, total acidity decreased slightly as seaweed powder can be functioned as alkalizing seasonings which neutralized the acids presented in the sauce samples 18.   F2 obtained the highest mean score in terms of viscosity (5.47) and aftertaste (5.60) which give the significant difference (p<0.05) compared to other samples. The increasing composition of seaweed powder caused the viscosity of samples increased with a significant difference (p<0.05) presented at the level of 3.0% as shown in figure  3. The range of viscosity was 130.46-131.00 poise. This is due to the increase in the amount of hydrocolloid, especially kappa-carrageenan, which can be dispersed in water and restrict the movement of molecules to form a bounded network in sauce 19. The result of viscosity indicated that F3 with 3.0% seaweed powder had the lowest acceptability (4.45) among panellist due to its highest viscosity (131.00 poise) and gave the thickest body. In addition, the panellists were able to detect the fishy aftertaste when seaweed powder is used at the level of 3.0%.

Advances in Social Science, Education and Humanities Research, volume 406
For syneresis property, increasing the percentage of seaweed powder in the formulation caused by decreasing the percentage of syneresis. The syneresis ranges were 7.23% to 9.77% as shown in figure 4. There was a significant difference (p<0.05) presented at a level of 2.5% seaweed powder (F2). Reported by 20 that Kappaphycus alvarezii which contains kappa-carrageenan as a major hydrocolloid can form a rigid or brittle gel in a liquid or semi-liquid structure which is characterized by high syneresis. Decreasing in syneresis due to the increase in the number of hydrocolloids presented in the sauce when increasing in seaweed powder composition. Thus increasing the gel strength as the resulted gel is more dense and compact so it has a good ability to form a more rigid network and to withstand weight per width area 21. Thus, it can be assumed that 2.5% of seaweed powder can improve the quality of sauce by reducing the syneresis significantly (p<0.05). Figure 5: Water activity of F1, F2 and F3. Figure 6: pH of F1, F2 and F3.
Besides that, figure 5 showed that increases in seaweed powder composition caused decreasing in water activity of the sauce samples with a significant difference (p<0.05) presented in the level of 2.5% seaweed powder. 22 reported that water holding capacity was increased with the increasing of seaweed powder composition increasing, thus the powder can attract and hold more water in the food system, more bond water are formed and decreased the water activity as well as make the product more stable.
On the other hand, figure 6 showed that increases in the composition of seaweed powder without affected too much on the pH of the sauce as the powder has an almost neutral pH value 23. The result of pH showed no significant differences (p>0.05) between all the formulations. Base on the sensory evaluation and physicochemical analysis, the best formulations (F2) has been chosen and was undergoing proximate analysis with the control.

Nutrient Composition of the Control and the Best Pineapple-Chili Sauce Mixed with Seaweed (Kappaphycus alvarezii)
There were significant difference (p>0.05) found for moisture and crude fat content for the control and F2. The moisture content of the control and F2 were high, which were 71.99% and 72.54%, respectively as presented in Table 2. Adding seaweed powder increased the moisture content of the sample due to the nature of it which has significant water holding capacity, which is 17.73 g/g 24. Ash content in F2 (2.70%) was higher than the control samples (1.50%) with a significant difference (p<0.05). This is because seaweed is rich in minerals such as sodium, potassium, calcium, magnesium, iron and phosphorus. Generally, the mineral content of seaweed was 8% to 40% 25. According to 24, seaweed (Kappaphycus alvarezii) powder has relatively high ash content, which is 14:52%. In contrast, for the control sample, modified corn starch and xanthan gum used are artificial materials which lack minerals. Moreover, the crude protein content in the control samples (0.29%) and F2 (0.37%) were a significant difference (p<0.05). This is due to the use of different thickening agents in the two formulations. In a control sample, xanthan gum did not contain protein while modified corn starch only contained 0.26% protein. Thus, crude protein content was increased with the using of seaweed powder as a thickening agent as it contained 11.5% protein 24. In addition, the crude fibre content of F2 (0.81%) also significantly higher (p<0.05) compared to control (0.67%). Finally, data obtained showed that the number of total carbohydrates significant reduction (p<0.05) in the total carbohydrates of F2 (23.44%) compared to the control sample (25.37%). Both formulations have low carbohydrate content since most of the nutritional composition made up of water. The use of seaweed powder which has a strong water holding capacity caused F2 to have a higher moisture content. In addition, F2 also has higher ash, crude fibre and crude protein content than that of the control formulation. Thus, seaweed (Kappaphycus alvarezii) powder has the potential to reduce the number of total carbohydrates in the sauce sample.

CONCLUSION
In overall, seaweed powder has influenced differently the quality of pineapple-chili sauce in terms of sensory evaluation, physicochemical properties and nutrition composition. Increasing in seaweed powder concentration did not change significantly the taste and colour of the sauce but it affected significantly the aroma and viscosity of the sauce. Increasing in seaweed powder concentration also improved the quality of sauce by reducing syneresis and water activity; however, a higher concentration of seaweed powder (3.0%) make the sauce became more viscous and unacceptable. Pineapple-chili sauce mixed with seaweed produced from 2.5% seaweed powder was chosen the best formulation with significantly increased the percentage of crude fibre, protein and ash content.


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A technical-economic analysis of telemetry as a monitoring tool for crop protection in viticulture

Based on the European Community framework directive 2009/128/EC that is devoted to the sustainable use of pesticides, farmers’ sensitivity and their administrative fulfillments are growing in recent years. Great attention is directed towards remote data acquisition by smartphone, satellites, drones. An available technological tool to accomplish this in the scenario of precision viticulture technologies is telemetry. This study aimed to evaluate the usefulness of the data acquired with a telemetry system used when applying crop protection products in a winemaking farm for management optimization. Results showed an incorrect operative operation rate for 9.53% of the total kilometers worked during the spraying phase with a variable cost for fuel and pesticides ranging between 0.01 € m–1 and 0.03 € m–1.

Introduction
Application of crop protection products in viticulture, and more generally in specialized crops, is the phase of highest frequency and logistical complexity and has a direct impact on the success of the entire production process. The scarce availability of companies which provide remote-control technology and data logging in the agriculture sector limits the possibility of technicaleconomic optimization of this strategic phase. In vineyard crop protection, it is possible to highlight a dualism: i) intense work and investment made by the pesticide producer to identify new and more sustainable molecules; and ii) the slow technological improvement of smart sprayers and devices for acquiring data during the application stages which still remain limited. At the same time, telecommunication systems are growing and spreading quickly and can contribute to the implementation of precision monitoring and field data mining (Albedo et al., 2016;Oksanen et al., 2016). Tseng et al. (2006), one of the pioneers of telemetry systems in the agricultural sector, state that this type of technology can provide a wide range of advantages to enhance agricultural production, optimise returns, reduce risks for crops, and minimise the environmental impact.
Telemetry has been successfully introduced for various agricultural operations, e.g., the monitoring of harvesting olive yards (Castillo-Ruiz et al., 2015). Gil et al. (2014) implemented a telemetry network sensor to assess the drift produced during the spraying operation in viticulture. Sarri et al., (2017) developed a telemetry system based on general packet radio service (GPRS) global system for mobile communication (GSM) for the monitoring of crop protection stages. This telemetry provides operative parameters such as sprayer status, maps of pathways, forward speed, applied volume, and applied rate through a combination of WebGIS platforms and hardware. Similarly, the Sika-PICORE monitoring system combines technologies Wifi, Bluetooth, GPRS or GSM for the local transfer between a smartphone and remote of the operating parameters of sprayers (Sika-PICORE, 2019). Other solutions provide local data acquisition and the generation of reports such as the system Agrotrack, which stores data such as application rate, forward speed, pathways in an SD memory but without the transmission to a web server (Reyes et al., 2012). In this framework, this study aimed to evaluate the technical and economic usefulness of the data acquired with a telemetry system to assess the magnitude of operative errors compared to the ideal implementation in economic and efficiency terms. The economic aspects were analysed by fixed and variable costs related to the yard consumption (tractor coupled to air-blast sprayer) according to the ASABE Standard EP496.3. A particular focus was made on fuel, pesticides and water consumption, which are the three elements that cause the most significant impact of agriculture on the environment. Finally, thanks to the telemetry system, it was possible to monitor the efficiency rates of each single working day during the crop protection stages.

Materials and methods
The research site was located in Tuscany, in the central part of Italy, near the city of Siena, on a winery farm (43.435641 N, 11.302821 E). Vineyards were in the Val d'Elsa hills, in the center of the Chianti Classico production area. The total area of the vineyard was 117 ha. There were 73 vineyard production units, divided into a total of 120 plots, 90% of which with a row spacing of 2.0 m. The study analysed data related to crop protection stage performed in the 2017 season. A total of 13 treatments, applied between May 7 and September 14, were monitored. The application rate used for the treatments varied according to the seasonal average phenological stage: the first phase was from budding to distension of the first three to four leaves, average LAI 0.5 and was sprayed with 150 L ha -1 (AR150); the next phase was up to LAI 0.9 and was sprayed with 200 L ha -1 (AR200), while at the maximum canopy growth LAI 1.3 was sprayed with 250 L ha -1 (AR250).

Instrumentation -telemetry module
The hardware set up consists of an OVIDIA MTX 65 + G V3 differential global positioning system receiver (DGPS) plus GSM and GPRS radio terminal ( Figure 1). The GPRS modem had its intrinsic transmission control protocol (TCP) and internet protocol (IP) stack that allowed the data packet to transfer every 10s. Two external receivers for the DGPS and GSM were installed on the roof of the tractor. The DGPS receiver had a wide area augmentation system (WAAS) and used the European Geostationary Navigation Overlay Service (EGNOS) for differential correction. The accuracy was 1 m in the horizontal plane for circular error probability (CEP) and 1 m in the horizontal and vertical plane for the spherical error probability (SEP).

Instrumentation -improved system scheme
The MTX 65 + G V3 has its own SIM card reader and standard connector interfaces. The connector interface had six connecting pins including two analogue inputs, one pulse counter, and two for power supply. To monitor spraying operations, the following connections were made: pin 1 was connected to the tractor ON/OFF key, pin 2 and pin 4 were connected to the right and left side of the spray-head, pin 5 was connected to 12 V DC power supply, and pin 6 was connected to the negative terminal of the tractor battery. The connection on pin 1 allowed monitoring the status of the tractor. After turning the tractor ON/OFF key or after the activation of the ON/OFF line, the system would send attention commands (AT) to the server and initiate or end up the section. A real time clock (RTC) provided accurate timekeeping and enabled time stamping of messages. When the tractor key was turned OFF, the MTX 65 + G V3 terminal was logged off from the network. At the same time, the software would lead the module into a secure state and save data before disconnecting the power supply. This mode was referred to as power-down mode. In this mode, only the RTC stayed active and battery discharging was limited. The MTX 65 + G V3 configuration was done by setting a forwarding threshold . This allowed the system to recognize a change in condition from parking or activity. Given the limited accuracy of the GPS system, it was set to be 0.6 km h -1 because smaller values introduced noise in the discrimination process. The monitoring of the sprayer was carried out by connecting the analogue inputs to the two drive switches linked to the solenoid valves of the right and left section of the sprayer-head. This configuration made it possible to evaluate the individual activation and switch-off phases. The PTO drive was not considered as it was continuously active for machine operation and does not represent a spraying error risk, as the failure to activate was clearly audible. Hardware settings and GPRS data  packet management were available through the WebGIS Agroplanning platform. Agroplanning consisted of two main elements: a cloud server and a user terminal. A graphical user interface (GUI) allowed for instantaneous interaction and settings for the client. The platform was divided into eight main sessions: i) dashboard with the sub-sessions of activities performed in the last 30 days, minimap which showed the last parked position of the vehicle, and notifications window for the communication from server administrator; ii) Map with a set of base layers of terrain map, routes, and satellite images; iii) Vehicles where all data related to the machine were stored and where it was possible to edit the features; iv) Farms which was a simplified GIS where it was possible to edit and upload each single farm plot and perform individual analysis; and v) Report where the algorithms and equations to calculate and query the system for each variable of interest (sensors, vehicle status, speed, heading) were found. The other three sessions were related to upgrading solutions of the platform, communication with the site manager, and client assistance, and were not used for the study. Agroplanning processed all the data received from the MTX 65 + G V3, distinguishing four main activities: i) Idle, or pause state, refers to conditions in which the vehicle was stationary or was recording speeds of less than 0.6 km h -1 ; ii) Towed, refers to distances travelled with the engine OFF, i.e., when the vehicle is towed or hauled on a trailer. In this case, the device remained active using the on-board battery it was equipped with; iii) Transport, relative to moving equipment to other locations, was recorded when speeds exceeded 0.6 km h -1 and with left and right sides of the spray-headswitched off; iv) Worked, refers to the work operations (in this study, only crop protection applications), and was identified when speeds were higher than 0.6 km h -1 and with at least one of the sides of the spray-head working. Available data were: Date (mm/dd/yyyy), Position (Latitude, Longitude -WGS 84), Height (meter above the sea), Speed (km h -1 ), Heading (compass direction in degree), Fix, Coverage (% GSM network), RPM (revolutions per minute n°), Analog1 (ON/OFF), Analog2 (ON/OFF), Engine Status (1 ON -0 OFF), Battery (level %), Total Hours (hours.minutes), and Total Km (nnnn.nn). Data used for the technical analysis were time, latitude, longitude, speed of the sprayer, and functioning side of the spray-head (left or right). The values acquired through the telemetry system, in the form of machinery transit pathways, were analyzed and compared with the correct lines of transit in the vineyard to assess the differences and identify errors.

Instrumentation -spraying vineyard
The MTX 65 + G V3 was installed onboard of a tractor(New Holland T4/95N), which was used for the entire season for the crop protection applications. A pair of cables were connected to the drive switches on the left and right side of the sprayer. This installation allowed monitoring of the activations and deactivations performed by the operator. The average forward speed was fixed at 5 Km h -1 . Treatments were performed by an articulated pneumatic sprayer (Link55, Cima®) with a 1000 L tank and eight spray-head, four on each side (Cima, 2019), which simultaneously sprayed four sides of the inter-rows of a vineyard. Logistically, spraying was done in alternate vines' rows. In addition, each plot was sprayed around the entire external boundary after the vine interrows were sprayed.

Operative assessment
To assess the potential of the telemetry system, operational error cases were identified. These were compared with respect to the correct execution, considering the pathways and sprayer activation errors. Four main recurring operational errors were identified ( Figure 2 twice; ii) non-alternating sprayed inter-rows (NAI) -incorrectly travelled with the sprayer in operation; the correct inter-row was not travelled, and therefore the execution of the treatment was not carried out based on the right course of alternating inter-rows; iii) non-travelled inter-rows (NTI) -inter-rows that the operator should have travelled with the sprayer activated to perform the treatment properly; iv) nonsprayed external boundaries (NEB) -untreated canopy espalier of the external rows of the vineyard where the operator did not travel. The assessment of analytical errors was determined based on the meters of inter-row canopy espalier treated in excess or shortfall by the vineyard, also distinguishing between the conditions in which the sprayer had to be activated or not. The Keyhole Markup Language (KML) files of each working session, which allow machine data rendering on the WebGIS Google Earth Pro platform (Google Earth, 2019), were downloaded. Moreover, for each treatment, the related database in comma separated values (.csv) was used to perform an analytical evaluation through spreadsheet software (Microsoft, 2013). The georeferenced position data were analysed with the geographical information system (GIS) ESRI ArcMap 10.3 software (ESRI, 2013). This software was used to remove all GNSS position outliers to correct .csv data. The total error path (TEP), expressed in kilometres, was measured by summing the four types of errors described above (Eq. 1).

Methodology for the cost analysis
Spraying equipment costs ASABE Standard EP496.3 methodology was used to assess the spraying equipment costs. The cost was determined by calculating the Total hourly cost. Two main categories of costs were considered: variable costs and fixed costs. The former were costs that are activated together with the production process, and they include fuel and lubricant consumption costs (proportional to the power used), repair and maintenance costs, and the costs associated with driver's working hours (labour costs). The fixed ones are: sundry expenses (taxes, housing and insurance), annual amortization rate and yearly interest.

Fuel consumption
Fuel consumption data were acquired by breakdown of consumption during the spraying and the transfer phases. These were quantified in six working stages, with variable orographic conditions ranging from flat land to hill with 15% of slope, by measuring the remaining fuel litres manually inside the tank by difference to the known initial volume of 25 L. The working stages were monitored for a minimum of 30 minutes. Then, the consumptions were attributed to the spraying stages paths obtained from the Agroplanning platform. Then the specific fuel consumption of operational errors RI, NAI, NTI, and NEB was calculated as follows (Eq. 2): (2) where FCTEP is the fuel cost of total error path (€), v is the mean forward speed (km h -1 ), Fc is the mean fuel consumption in the spraying stage (L h -1 ), and € L -1 is the national fuel price set at 0.85 € L -1 (CCIAA Siena, 2018). The values were considered as the amount of fuel in excess (+) and lost (-) consumption compared to the correct path.

Pesticide consumption
The pesticide costs of total error path (PCTEP -€) were evaluated based on the unitary costs provided by the farm at the three levels of application rates (Eq. 3). The active ingredients used belong to the category of organic fungicides based on copper and sulfur, and to the systemic fungicides active against the major fungal diseases, such as Plasmopara Viticola (Berk & Curt.) Berl. & de Toni, Uncinula Necator (Schw.) Burr., Guignardia Bidwelli (Ellis) Viala & Ravaz) and Botrytis Cinerea Pers. ex Fr. A three step process calculated the cost. Firstly, the duration of operational error was calculated by dividing the errors paths to the average forward speed recorded by Agroplanning. Secondly, each duration (min) was multiplied to the sprayer flow rate (L min -1 ). This provides the amount of spraying in excess (+) and lost (-) compared to the correct path. Then these data were multiplied by the average costs of treatments for the three levels of AR. Finally, the PCTEP was calculated by summing the average costs of treatments for the three level of AR (Eq.3).
(3) Q150; 200; 250 are the three levels of flow rate of the sprayer (L min -1 ), v is the mean forward speed (km h -1 ), Cm150; m200; m250 are the average costs of pesticide mixture (€ L -1 ). For the AR150 level the average cost (Cm150) is 49.56 €, for AR200 (Cm200) is 103.12 € and for AR250 (Cm250) is 72.93 €. The winery farm provided these costs and therefore they were the real costs that the farm incurred for the purchase of pesticides.

Water consumption
For water consumption we mean the water used to prepare the phytoiatric mixture. The water costs of total error path (WCTEP -€) were evaluated based on the same pattern of PCTEP. The error paths were divided to the average speed, recorded by Agroplanning, to find the duration of operational error. Then, each duration (min) was multiplied to the three levels of sprayer flow rate (L min -1 ). Finally, the sum of these data was multiplied by the unit water cost (Eq. 4).

Sprayer equipment efficiency analysis
The telemetry system installed on the tractor allowed to record the working time (i.e. when sprayer equipment was spraying vine-Article N o n -c o m m e r c i a l u s e o n l y yards), the time of transport (i.e. when sprayer equipment was moving between vineyards) and of pause idle (i.e., when the tractor was stationary, for example to recharge the tank of the sprayer). With these data it's possible to know the sprayer equipment efficiency rate. It was calculated by dividing the working time by the sum of working time, transport and pause (Eq. 5). (5)

Statistical analysis
The length of pathways errors in relation to the AR, which were normally distributed (p-value of the Shapiro-Wilk test > 0.05) were modelled by a two way ANOVA using the R statistical software (R Core Team, 2013). The main effects of the two treatments (Application rate, Error pathways) and their interaction are all of equal interest. Test for significant treatment effects for factor AR, Error pathways and significant interaction effects were performed with a two-way ANOVA. All model specification tests were conducted, i.e., verifications that the mean of the errors was not significantly different from zero using the Student's t-test, that the errors were normally distributed using the Shapiro-Wilk's normality test, homoscedasticity verification using the Levene's Test and Breusch-Pagan's test, and the serial correlation using the Durbin-Watson's test. A multiple pairwise-comparison between the means of Error Pathways with Tukey's HSD test was performed. From the model outputs we have been set that the test does not reject the null hypothesis with equal variances at a 5% significance level.

Results
Test for significant treatment effects for factor AR and Error pathways showed no difference in the means of factors. The twoway analysis highlighted that there was no statistically significant interaction between the effects of AR and errors pathways (F=2. 25, P=0.09). Tukey's HSD post hoc tests were carried out. For all the error pathways there is no evidence to suggest differences (P values range from 0.47 to 0.99). Normality checks and Levene's test were carried out. Therefore, we can assume the homogeneity of variances in the different Error pathways (RI -F=0.35 p values =0.71; NAI -F=0.39 P=0.67; NTI -F=0.41 P=0.67; NEB -F=0.55 P=0.59). Table 1 lists the economic parameters used for applying the ASABE EP496.3 methodology. The purchase price of the tractor was estimated in 50,000 € according to the price list of New Holland, and for the air-blast sprayer in 12,000 € according to the  price list of Cima Spa (New Holland Agriculture, 2019; Cima, 2019). The cost analysis was divided into two main categories: variable and fixed costs. Each category referred both to single equipment units (tractor or air-blast sprayer) and to coupled equipment unit (tractor and air-blast sprayer). Variable costs were: i) repair and maintenance cost; ii) fuel and lubricant cost; iii) and labor cost (€ h -1 ). The repair and maintenance costs were calculated using the factors of 80% on the purchase price for tractor and to 10% for air-blast sprayer. Then, these values were divided for the service life to find the repair and maintenance hourly cost (€ h -1 ). The fuel and lubricant costs were calculated on the used power for each equipment through the engine power (kW) of the tractor and the used power factor, i.e. 10% for the tractor and 55% for air-blast sprayer. Thus the used power found was multiplied for the fuel and lubricant cost referred to kWh provided by the manufacturers. Finally, labour cost was set at 15 (€ h -1 ) considering the salary of a not specialized worker. Instead, in fixed costs there were: i) yearly sundry expenses; ii) yearly amortization rate; iii) yearly interest. The yearly sundry expenses were calculated applying a factor of 2% for tractor and 0.3% for the sprayer on the purchase price. The yearly amortization rate was calculated based on the purchase price minus the remaining value (20% of the purchase price for the tractor and 37% of the purchase price for the air-blast sprayer) divided for the economic life of the equipment. The annual interest was calculated on the present value (50% of the purchase price for each equipment) multiplied for investment interest rate (1.5% for each item). Then to find the fixed hourly costs, the total fixed costs for each equipment were divided into the annual machine use (service life divide to the economic life for the coefficient of use, 75% for tractor and 100% for air-blast sprayer). The assessment was performed using technical parameters found in the specialized literature that, for each category of machines, allowed the estimation of the operating cost starting from the new value and the power of the machine. The total variable costs were 32.35 € h -1 , divided in 20.18 € h -1 for tractor and 12.17 € h -1 for air-blast sprayer. Instead, the total fixed hourly costs were 10.52 € h -1 , divided in 5.79 € h -1 for the tractor and 4.73 € h -1 for the air-blast sprayer. Finally, the total hourly cost was 42.87 € h -1 . The data related to the technical and economic analysis of error pathways have been summarized in Tables 2 and 3. During the entire season, the machine has travelled a total distance of 1450.9 km, of which 437.24 km in the working phase with the sprayer active and 1013.65 km in the transporting step respectively. The errors related to the erroneous pathways TEP for each AR levels were reported both in kilometres and percentage % ( Table 2). The percentage represents the single path error (RI; NAI; NTI; NEB) divided by total path error of each AR. Moreover, the total TEP (57.34 km) and the absolute error of RI, NAI, NTI and NEB were highlighted in Table  2. Specifically, 14.46 km were measured for the RI, 21.72 km for the NAI, 13.63 km for the NTI, and 7.53 km for the NEB. Finally, a sum- AR application rate is in L ha -1 , % represents the weight of every single error path on the total of them on each level AR, STD is standard deviation and CV represents the coefficient of variation. Table 3. Costs for fuel, pesticide and water used in the crop protection season.

Application rate Fuel Pesticide
Water  mary of descriptive statistics of mean, standard deviation (STD) and coefficient of variation (CV) of the TEP of each AR was done. The costs (€) for fuel, pesticide and water consumption were reported in Table 3. The individual costs were calculated for each level of AR and within each level. Then the costs were divided by the four types of operative error (RI, NAI, NTI, NEB) and expressed as € (+) or in deficit € (-), i.e., costs deriving from meters of inter-row canopy sprayed in excess or shortfall. Totals of the various cost items (FCTEP, PCTEP, WCTEP), differentiated, for each item, in excess and in deficit costs were reported (Table 3). The average daily working session highlighted a time of 9.53 h divided among working, transport, and idle, with average fuel consumption of 113.27 L. The fuel consumption measurements during work phases were 13.85±0.05 L h -1 , while for the transport phases were 7.76±0.05 L h -1 . Based on such analyses, the FCTEP total variable fuel costs generated by the incorrect execution of the treatments was 145.30 € per season. Of this, 91.63 € were due to the RI and NAI in excess of the correct one, while 53.67 € were the costs of NTI and NEB that the yard should have performed. The item of total variable costs of pesticides generated by the incorrect execution of the treatments was 1941.10 € per year. The costs calculated for the errors RI and NAI attributable to a condition of over-sprayed were 1243.43 €. The total variable cost items associated with NTI and NEB impact on the annual budget for 706.67 €. Finally, the water costs of total error path (WCTEP), generated by the incorrect execution of the treatments, was 17.69 € per year, divided in 11.14 € attributable to a condition of over-sprayed caused by RI and NAI error paths, and in 6.54 € generated by NTI and NEB error paths. The efficiency rates (Max, Min, Mean) of each AR levels and the whole protection stage were reported in Table 4. Efficiency rates highlighted low values on all working days with an average value during the entire season of 0.37. The minimum efficiency rate was achieved in the AR250 phase and settled to 0.18. Instead, the maximum efficiency rate is 0.5 and was reached in the AR 250.

Pathways errors
The analysis of seasonal errors showed that there was independence between the AR phases based. The phases AR150 and AR200 highlighted lower error proportions in the ratio among km worked with 4.43% and 7.55%, respectively, compared to 17.69% of the AR250 phase. If overall length values were considered, the AR250 phase had the largest number of km erroneously travelled (43.94 km). The error distribution among the three AR phases showed a greater uniformity for the phase AR250 with a CV 0.370, while the AR150 phase had the highest CV of 0.793, consequent of the limited proportion of the RI and NTI error. The smaller amount of erroneous pathways in AR150 phase may be due to both the overall reduced distance travelled and the greater attention in the execution of the work sessions, which led to fewer errors. This phase represented a strategic time period in the grape growing season. It was characterized by high susceptibility to the risks of infestations due to climatic conditions favourable to the diffusion of pests and disease for which it was necessary to protect the growth of shoots and inflorescences (Siegfried et al., 2016). The pathways Article Figure 3. Least squares means and 95% confidence interval bars of error pathways (m) in the three different application rates.  Figure 3). In the cases that were identified, the spraying yard travelled two adjacent rows and then continued following the rows alternately. One of the smaller amounts of error NAI in % (37.63%) on three levels, is in the AR150 phase. In this phase, this result was probably due to vineyard soil management. In fact, in the vineyards cover crops were seeded in alternating inter-rows way. The presence of the cover crops in alternating inter-rows makes the correct inter-rows clearly distinguishable by the passage of mechanical means. This was also confirmed for RI error that, overall, resulted in AR150 the one with the lowest incidence (6.86%) in proportion to the km travelled incorrectly. During the season, the cover crops progressively disappeared due to the natural decomposition process and the field processing carried out (Snapp et al., 2005). Also, the canopy growing makes the operating scenario uniform and the combination of these factors increases for the operator the difficulty of proper inter-rows identification. The maximum detected value of RI (12.37 km -28.16%) was observed in the AR250 phase, i.e. when the LAI had almost reached its maximum value.
Total pathways errors related to NTI have an important amount (13.63 km) in relation to the other types of errors. They constitute the type that exposes the production process to higher risks due to the almost complete absence of coverage differently from the NAI in which part of the endo-drift, can induce a partial coverage in those parts of the canopy not reached by the direct spraying. This inefficiency of the distribution process could cause production losses with negative effects on the yield.
Total errors of non-sprayed external boundaries (NEB) represent those with reduced rates of pathways error in terms of kilometers (7.53 km). Its impact was mainly linked to logistical-operational reasons. In the analysis of the potential causes that induced this error, it has been observed the impossibility to carry out properly turning maneuvers due to the limited spaces at the headlands, which led the operators not to deal the path. This type of error leads to the no spraying of the external boundaries of vineyards, and so it exposes the vineyard to damage risks due to the absence of coverage. This opens the way to diseases inoculation in the vineyard, which may destroy the bunches. These low-efficiency rates were due to the site of vineyards because they were located far enough from each other, so transport times would reach high value lowering the efficiency rate consequently.

Cost analysis associated with pathways errors
The cost analysis was focused on the consumption of fuel, pesticide and water consumption. The total costs due to path errors were 2104.09 €, but the incidence of each item on the total was very different. The costs related to fuel consumption in the excess or shortfall have been a limited influence on variable costs. Based on the market price of agricultural fuel, equal to 0.85 € L -1 (CCIAA Siena, 2018), throughout the season there has been extra consumption of 107.80 L, while 63.14 L for the part of not-consumption. This volume, if compared to the fuel consumption during the work phase, which was 13.85 L h -1 with average working productivity of 1.8 ha h -1 , was equivalent to an area of 14.01 ha.
Total costs of water consumption have had even less impact on the total variable costs compared to those of the fuel. They have affected the total costs for 17.69 €. In terms of water consumption, there was a consumption error of 5980.05 L, which corresponds to six full sprayers not correctly sprayed.
The part of the variable costs generated using pesticides was the cost item with the greatest impact (1941.10 €). During the sea-son, there was a progressive increase in the average cost of the pesticide mixture due to the intensification of treatments and the introduction of systemic products with a higher unit cost.
The result of cost analysis associated with path errors was a progressive increase in the error cost per linear meter, which varies between 0.01 € m -1 and 0.03 € m -1 .

Conclusions
The study highlighted how the absence of tracking systems in the yards used in the crop protection limited the knowledge of the critical aspects which could emerge after improper spraying execution. From an operational point of view, it was highlighted that in the progress of the vegetative season the presence of devices that can assist workers in driving the spraying yard to limit pathways errors is desirable. The telemetry system allowed the acquisition of useful information for the understanding of the operative dynamics of crop protection stage, allowing an analytical characterization of the management process. The errors detected made it possible to evaluate critical issues in both operative and economic terms. Within the context of growing attention to the sustainable use of pesticides, the telemetry systems have proved to be a valid support for farmers. Despite the wide configurability of the Agroplanning platform, improvements are needed in order to increase the number of parameters to monitor (analogue and digital inputs).