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Investigation of body secretions as bioindicators in cattle estrus detection

* Correspondence: ozgulanitas01@gmail.com

were 160 dairy cows in the farm, of which 40 cows were fresh and were waiting for artificial insemination. Considering that the smallest sample size to represent this population is 5% in the 5% confidence interval, the number of dairy cows is 10% of fresh cows (= 40 / 0.10), thus 4 cows are enough to sample. However, in order to obtain more reliable results within the available possibilities, 15 cows were synchronized and samples were taken from 6 cows (3-4 years old) that were approved by other control methods. Body fluid samples (sudor, milk, blood, feces, urine, vaginal secretion, saliva) were taken in 3 estrus periods of a total of 6 cows and analyzed in duplicate. In total, 252 samples were analyzed for volatile compounds during estrus.
The Ovsynch protocol, which was developed for use in dairy cattle, was applied for grouping the estrus. The cows were injected with 2 mL i.m. GnRH (100 μg as 2 mL of Cystorelin i.m., Merial, Athens, GA) on any day of the cycle (day 0) and with 5 mL i.m. PGF2α (25 mg as 5 mL of Lutalyse i.m., Pharmacia Animal Health, Kalamazoo, MI) on day 7, and a second injection of 2 mL i.m. GnRH was performed on day 9 [9]. With this application, ovulations were synchronized, and samples were taken in order to determine pheromones in the secretions of milk, blood, vaginal secretion, urine, feces, saliva, and sudor at different stages of estrus (preestrus, estrus, postestrus). Ramesh Kumar et al. [10] collected all samples from preestrus animals 3-5 days before estrus and from postestrus animals 2-4 days after estrus period. With the help of veterinarians, the stages of the estrous cycle (preestrus, estrus, postestrus) were carefully determined by rectal palpation throughout the cycle. In addition, the diameter and development of follicles and ovaries in the ovary were determined by ultrasound (HASVET 838 ultrasound, Hasvet Medikal Ltd. Şti., Antalya, Turkey). The cows were fed ad libitum total mixed ration diet and fresh water.

Data collection conditions
Urine samples, feces, vaginal fluids, saliva, milk, blood, and sudor samples were taken by the methods of Kumar et al. [11], Sankar and Archunan [12], Sankar and Archunan [13], Saliva Sankar et al. [14], Bendall [15], Klemm et al. [16], and Kennedy [17], respectively. Urine samples were taken by applying a urinary catheter (Female urinary catheter 31 cm Kruuse, Medical Gross MEDIBIL Medikal Bilişim Teknolojileri, İzmir, Turkey) to the cows that did not urinate in order to avoid any loss of time and stress. Vaginal secretions were collected with tampon. The tampons were disinfected and dried before use. The perineum and vulva area were washed and dried with clean water before sampling. The tampon was gently released into the vagina for 30 min, and then the tampon was removed and placed into screw cap bottles (Tefloncoated) (N24 Vials, Turkey). Udder were cleaned and dried with paper towel before milk samples were collected. Blood samples were taken from vena jugularis. Sweat samples were taken from the nasal regions of animals. Nasal region was cleaned with water prior to sampling and dried with paper towels. Liquid samples were 15 mL and feces were 30 g. All the samples were stored in a freezer at -30 °C (Uğur UED 280, Uğur Soğutma A.Ş., Aydın, Turkey). One day before the analysis, the samples were allowed to thaw in the refrigerator overnight.

Gas chromatography and mass spectrometry analysis of all samples
For the analysis, 2 mL of sudor, saliva, milk, blood, urine, and vaginal secretion samples and 2 g of fecal sample were placed in the gas chromatography vial and 1 mL of CaCl 2 was added to each sample. The samples were placed in an automatic HS-40 head space autosampler (Perkin Almer GC with split splitless inlet MSD system). Volatile compounds were analyzed on an automatic HS-40 head space autosampler. Needle temperature was 120 °C, thermostatic time was 30 min, and thermostatic degree was 35 °C during the extraction in the headspace autosampler. HP-5 MS (30 m × 0.25 mm × 0.25 μm), fusedsilica capillary column was used. Helium (1 mL/min) was used as the carrier gas. The injector temperature was 250 °C, set for splitless injection. The oven conditions were set to 50 °C for 1 min and then the temperature was increased to 200 °C at a rate of 4 °C/min. Thermal desorption was allowed for 1.5 min. The detector temperature was 280 °C. The components were identified by the comparison of mass spectra and retention time data with those of authentic samples and complemented by means of performing a NIST, Wiley, Flavor library search of the acquired mass spectral data.

Statistical analysis
Experimental data were used to estimate the means and standard error [18]. The data were subjected to logarithmic transformation according to base 10 in the randomized design plan. However, the average and standard errors of experimental data were given in the tables and in the text. Duncan post hoc test was used to compare the means of the groups (preestrus, estrus and postestrus). All the statistical analyses were performed in the Statistical Package for the Social Sciences software version 16.0 (SPSS Inc., Chicago, IL, USA). A difference in the mean values of P < 0.05 was used to establish the statistical significance.

Volatile chemical compounds of feces
According to the results of feces analysis, 168 volatile compounds were detected and among these compounds, there were 72 compounds in the preestrus period, 85 compounds in the estrus period, and 55 compounds in the post-estrus period ( Table 1). As a result of the analysis of variance, 6-methylhept-5-en-2-one compound was determined to be important (P < 0.05) in terms of interperiod differences. This compound was detected in both estrus period (0.05 ± 0.00) and postestrus period (0.39 ± 0.14) and was calculated as P = 0.021.

Volatile chemical compounds of urine
According to the results of GC-MS, a total of 141 volatile compounds were detected in urine and it was found that there were 76 compounds in the preestrus period, 71 compounds in the estrus period, and 66 compounds in the postestrus period ( Table 2). As a result of the analysis of variance, Nonadecan-1-ol trimethylsilyl ether compound was determined to be important (P < 0.05) in terms of interperiod differences. This compound was detected in both preestrus period (0.22 ± 0.00) and estrus period (1.22 ± 0.47) and was calculated as P = 0.042.

Volatile chemical compounds of blood
As can be seen from Table 3, a total of 156 volatile compounds were detected in blood. Among these, 69 compounds in the preestrus period, 79 compounds in the estrus period, and 64 compounds in the postestrus period. As a result of the analysis of variance, pentane, 2-methylcompound was determined as important (P < 0.05) in terms of interperiod differences. This compound was detected in the preestrus period (0.99 ± 0.93), the estrus period (0.47 ± 0.26), and the postestrus period (3.54 ± 1.01) and was calculated as P = 0.043.

Volatile chemical compounds of milk
A total of 130 volatile compounds were detected in milk and it was found that there were 56 compounds in the preestrus period, 58 compounds in the estrus period, and 91 compounds in the postestrus period ( Table 4). As a result of the analysis of variance, the differences between the compounds in milk were found to be insignificant (P > 0.05).

Volatile chemical compounds of sudor
A total of 154 volatile compounds were detected in sudor and it was found that there were 84 compounds in the preestrus period, 79 compounds in the estrus period, and 81 compounds in the postestrus period ( Table 5). As a result of the analysis of variance, hexanal compound was determined to be important (P < 0.05) in terms of interperiod differences. This compound was detected in the preestrus period (0.93 ± 0.19), the estrus period (0.47 ± 0.11), and the postestrus period (0.18 ± 0.11) and was calculated as P = 0.014.               detected in both the preestrus period (0.41 ± 0.15) and the estrus period (0.09 ± 0.00) and was calculated as P = 0.040.

Volatile chemical compounds of vaginal secretion
According to Table 7, a total of 191 volatile compounds were detected in vaginal secretion and it was found that there were 91 compounds in the preestrus period, 89 compounds in the estrus period, and 99 compounds in the postestrus period. As a result of the analysis of variance, 1,2-benzisothiazol-3-amine tbdms compound was determined to be important (P < 0.05) in terms of interperiod differences. This compound was detected in both the preestrus period (0.61 ± 0.04) and the postestrus period (0.08 ± 0.00) and was calculated as P = 0.000.

The volatile compounds of body fluids in estrus period
A total of 1563 compounds were detected in the body secretions during the estrus period. In all body fluids, 531 volatile compounds were detected in the preestrus period, 538 in the estrus period, and 494 in the postestrus period. Furthermore, the number of compounds found in at least one of the body fluids is 216 and the rate is 69%. However, the number of compounds found in all body fluids is 8 and the rate is 2.6% (Table 8). In addition, a total of 8 compounds are common in all body fluids. The chemical formula and the Cas number of these compounds are shown in Table 9.

Discussion
As a result of the analysis, 85 compounds of feces were obtained from the cows in the estrus period. Sankar and Archunan [12] detected a total of 10 different volatile compounds, and acetic acid, propionic acid, and 1-iodo undecane compounds were found in the estrus period, butanoic acid, 2-propenyl ester, carboxylic acid, and pentanoic acid compounds were found in the preestrus period, and 3-hexanol, butane, 2,2-dimethyl, and phosphonic acid compounds were found in the postestrus period. Sankar and Archunan [12] detected acetic acid, propionic acid, and 1-iodo undecane compounds in feces during the estrus, which are similar to the results of the current study. Manikkaraja et al. [19] evaluated pheromone metabolites in urine and feces using a colorimetric method to predict cattle sex pheromones (acetic acid and propionic acid) with high precision. They detected a total of 45 compounds during the estrus period in feces. Mozūraitis et al. [20] found a total of 31 compounds in the estrus period in feces. Of these compounds, 9 were also found in the current study (Table 1). These compounds are butanol, pentanol, acetic acid, benzaldehyde, propanoic acid, pentanoic acid, dodecanal, p-cresol, and indole. In addition, Gnanamuthu et al. [21] found 13 compounds in the estrus period in feces, and 3-methyl-tricyclo, undecane, and 2, 10 dimethyloctacosanoic acid were specifically present in the estrus stage, not in other stages. As can be seen in Table  1, 1-iodo-2-methylundecane compound was detected only in the estrus period, but 2, 10 dimethyloctacosanoic acid and 3-methyl-tricyclo compounds were not detected in feces. Kumar et al. [11] found urine pheromone compounds including ethylbenzene, 2,2-dimethylbutane, 1-iodoundecane, di-n-propyl phthalate, oxiranemethanol, and 1-iododecane. Ethylbenzene and 2,2-dimethylbutane were detected in all three periods, while 1-iodoundecane and di-n-propyl phthalate compounds were detected only in the estrus. They indicated that these compounds may have an important role in sexual attraction. Archunan and Ramesh Kumar [22] stated that these 2 specific compounds (1-iodoundecane and di-n-propyl phthalate) reveal the flehmen behavior of the bull and thus are important in estrus detection. As given in Table 2, undecane 6-ethyl compound was detected only in the estrus period, but di-n-propyl phthalate compound was not detected in urine. In addition, Muniasamy et al. [23] found the volatile compounds of 4-methyl phenol (p-cresol) and 9-octadecanoic acid (oleic acid) only in urine during the estrus. Muthukumar et al. [24] developed a p-cresol-based test kit since p-cresol detected in urine has been proven to be a candidate pheromone peculiar to anger in various studies. Klemm et al. [16] detected acetaldehyde compound in blood pheromones in the estrus period. They also reported that sexual hormones regulate the metabolic production of acetaldehyde. Table 3 shows that phenyl acetaldehyde, trimethyl acetaldehyde, methyl ethyl acetaldehyde, and acetaldehyde methylhydrazone compounds are similar to acetaldehyde compound in the estrus. Zebari et al. [25] reported that acetic acid (P < 0.001), valeric acid (P = 0.016), caproic acid (P < 0.001), and myristoleic acid (P = 0.035) concentrations were high during the estrus period. In Table 7, volatile chemical compounds such as phenylpropionic acid, acetic acid, carboxylic acid, hexenoic acid, benzenetricarboxylic acid, carbamimidic acid, dicarboxylic acid, and pentanoic acid were determined from the acid group during the estrus period in milk. Weidong et al. [26] identified about 80 volatile compounds in milk, which belong to ester, aldehyde, ketone, alcohol, fatty acid, and lactone class. At the end of the analysis, no specific compounds of postestrus, preestrus, and estrus 0.14 ± 0.00 2.00 ± 0.00 0.428 * As a result of the analysis, 23 compounds in the preestrus period, 39 compounds in the estrus period and 32 compounds in the postestrus period were not included in the comparison table, since they were detected in only one period. **P < 0.05.  detected trimethylamine, acetic acid, phenol 4-propyl and propionic acid compounds in the period of estrus, carbonic acid, phosphonic dichloride, butanoic acid, and 2-propenyl ester compounds in the preestrus period, and 3-hexanol, butanoic acid, 2-propenyl ester, and pentanoic acid compounds in the postestrus period. Propionic acid and phenol compounds in saliva were detected only in the estrus period (Table 6), while acetic acid compound was found both in the estrus and postestrus phases. In addition, butanoic acid was observed to be a common compound in both studies. Sankar and Archunan [27] analyzed the volatile compounds in the vaginal secretion of animals in 3 estrus periods and found 8 different organic compounds. They stated that trimethylamine, acetic acid, and propionic acid compounds were present during the estrus period and also compounds having similar structures to these compounds were determined in all 3 periods. Preti [28] reported alcohol compounds such as 6-methyl-1-heptanol from methyl 1-heptanol group and 2-methyl-7-hydroxy-3-4 from methyl hydroxy-heptane group during the period of estrus only in vaginal secretion. It was thought that estrus-specific volatile compounds detected only in the estrus period could be important indicators of the estrus status of cows and can be used to define the optimal insemination time. Therefore, a technological device will be developed by using these volatile compounds, which is more effective and easier than other methods for the most appropriate timing of artificial insemination. Timely detection of estrus depending on volatile compounds will provide the dairy sector with a big economic advantage in terms of the correct time for insemination.


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

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Alcohol dehydrogenase (ADH) genes family in wheat (Triticum aestivum): Genome-wide identication, characterization, phylogenetic relationship and expression patterns

Alcohol dehydrogenase (ADH) plays important roles in plant survival under anaerobic conditions. Although some research has been carried out the functions of ADH in other plants, that of wheat TaADH family genes in response to abiotic stress are unclear. A total of 22 ADH genes were obtained from 14 chromosomes of the wheat genome by systematic screening. Multiple sequence alignment and evolutionary relationship show that these genes contain the characteristics of GroES-like domain and Zinc-binding domain, and these belong to Medium-chain -ADH type and can be divided into three subfamilies. There are 17 pairs of fragment replication genes among TaADH family members in the wheat genome, while there are 9 pairs of collinear gene pairs from ADH family members between wheat and rice genome. We speculate that these fragment repetition events may be the main reason for the amplication of TaADH family genes. Ka/Ks analysis indicated that there were 64 repetitive gene pairs, and the Ka/Ks value of these gene pairs was less than 1, which indicated that these sequences of TaADH gene were relatively conservative and did not change greatly in the process of evolution. Promoter element analysis showed that almost all of the upstream promoters of these genes contained the responsive anaerobic inducible element. Tissue localized expression and expression patterns also demonstrated that the TaADH genes responded to abiotic stress and may play an important role in waterlogging stress during the seed germination stage. The results of this study helpful further study TaADH determine family genes. In this study, we identied 22 ADH family genes in wheat through sequence alignment among the wheat whole genome (IWGSC RefSeq v1.0; IWGSC2018) and Arabidopsis, rice and melon genomes, which greatly expanded the previously reported (NCBI) of pairs are puried and selected. The Ks value was used to estimate the occurrence time of repetitive events. The results showed that 64 repetitive events of TaADH family genes occurred between 1.55 and 16.42 Mya, including 30 repetitive gene pairs with evolution time of 11.19–16.42 Mya and 12 repetitive gene pairs with evolution time of 7.73–9.56 Mya, all of which were earlier than the rst time of genomic replication in wheat [34]. The second time is that the subgenome of common wheat can be traced back to 300000 years ago, including Triticum urartu (A sub-genome) and the hybridization of the Aegilops speltoides to form tetraploid wheat (T. dicoccoides, A and B sub-genome). About 8, 000 years ago, tetraploid wheat, also known as the Aegilopstauschii (D subgenome, produced hexaploid wheat (T. aestivum, A, B, and D subgenomes) [35]. It showed that most of the TaADH family genes in wheat have undergone strict purication and screening in the process of evolution, and retained the original function through fragment replication events. Through phylogenetic tree analysis with other species, it was found that 22 TaADH genes in wheat belonged to medium-chain ADH type and were grouped into 3 subfamilies. Collinearity analysis within the wheat genome and between the wheat genome and rice genome showed that there were 17 fragment replication events among members of the TaADH family, while the number of collinear ADH gene pairs of wheat and rice was 9 pairs. According to the Ka/Ks and evolutionary years, it was found that there were 64 repetitive gene pairs with Ka/Ks less than 1, which tended to purication selection, indicating that strong purifying selection had taken place in the process of evolution of TaADH genes. Cis-acting elements and tissue expression analysis showed that these genes were responsive to 11 kinds of abiotic stress. TaADH3, TaADH5, TaADH8, TaADH10-11, TaADH14, and TaADH16-22 were expressed in all parts of wheat, belonging to constitutive expression, and other genes were specically expressed. By comparing the expression proles of waterlogging-tolerant wheat Bainong 607 and waterlogging-intolerant wheat Zhoumai 22 at different germination stages after waterlogging treatment, it was found that TaADH1/2, TaADH3 and TaADH9 played an important role in responding to waterlogging stress, and could be used as an important basis for screening waterlogging-tolerant wheat varieties. These results will provide valuable information regarding further functional elucidation of TaADH genes in wheat. relative humidity (16 h light/8 h dark cycles). In this study, two wheat (Triticum aestivum L.) varieties, ‘Zhoumai 22’ (ZM22, waterlogging-intolerant) and ‘Bainong 607’ (BN607, waterlogging-tolerant), were selected as the materials. ZM22 is a commercial winter wheat cultivar in Henan Province, China. The BN207 and BN607 seeds used in this study were cultivated by Prof. Xingqi Ou from the School of Life Science and Technology, Henan Institute of Science and Technology, Xinxiang, China. All the seeds were provided by the School of Life Science and Technology, Henan Institute of Science and Technology. endosperm RNase-free DNase avoid genomic DNA First-strand cDNAs the PrimeScript Reagent gDNA according to the manufacturer’s protocol. The qRT-PCR assays were performed with the Primer Script RT Reagent Kit (Takara, Dalian, China). The 18S (AJ272181.1) was used as a reference gene. Data were analyzed with Opticon monitor software (Bio-Rad). All primers for qRT-PCR were designed using Primer 6.0 software and primer follows: and s and s. Step three replicates. One three −ΔΔCt

six genes in wheat. By comparison and phylogenetic analysis with other species, it was found that these ADH family genes belong to the medium-chain ADH subgroup. In this study, the structure, promoter, tissue-speci c expression, and expression of 22 TaADH genes in responses to waterlogging stress of two wheat varieties with different sensitivity, Bainong 607 and Zhoumai 22, were investigated. The information obtained from this study will greatly promote our understanding of the gene function of the ADH family.

Results
Genome-wide identi cation A total of 22 TaADH genes in the wheat genome were further identi ed by BLAST with 26 ADH genes reported in muskmelon as bait and wheat genome database using ADH domains (PF00107.26, PF08240.12, and PF13602.6) through HMMER software. According to the location distribution of these genes on chromosomes, they were named TaADH1-TaADH22 (Table 1, Table S1). Except for chromosomes 2 and 3, TaADH genes were distributed on all chromosomes, including 6 genes on chromosome 4 and one TaADH gene on chromosomes 5, 6, and 7, respectively. The number of the intron for all 22 TaADH genes ranged from 7 to 9, while that of the exons ranged from 8 to 10. The length of amino acid in TaADH genes ranged from 347 to 415. The range of pI was from 5.68 to 8.2, and the molecular weight was among . Through the subcellular localization prediction of these genes, it was found that they were all located in the cytoplasm.

Alignment and evolutionary analysis
By comparing protein sequences of these 22 TaADH genes, it was found that most of the residues of these protein sequences were the same. Pfam scanning of the sequences showed that all of these sequences contained the characteristic motifs of ADH (GroES-like domain and Zinc-binding domain) (Fig. 1A), in which the residues of the GroES-like domain were within 35-164 amino acid, and the amino acid residues of the Zinc-binding domain were within 206-340 amino acid. However, the location of amino acid residues of the Zinc-binding domain in TaADH20-TaADH22 was different from those of other genes (marked with a blue box). It inferred that these genes belonged to the ADH family. To examine their evolutionary relationships in wheat and the other plant species: Arabidopsis thaliana (7), Cucumis melo (13), Cucumis sativus (12), Glycine max (3), Hordeum vulgare (1), Lycopersicon esculentum (7), Oryza sativa (1) and Vitis vinifera (8), a phylogenetic tree was constructed by multiple sequence alignment of 22 TaADH proteins using the adjacent linkage of (NJ) method (Fig. 1B). The predicted ADH genes were classi ed into three groups, namely short-chain ADH, medium-chain ADH and long-chain-ADH. 22 TaADH genes in wheat belonged to medium-chain ADH type. According to the evolutionary relationship, these genes can be divided into 3 subfamilies: Class I contained the largest number of TaADHs (15 genes, TaADH1-9 and TaADH11-15), followed by Class II (4 genes, TaADH10 and TaADH17-19) and III (3 genes, TaADH20-22).

Conservative domain analysis
Through the conservative analysis of TaADH genes in the wheat genome, it was found that the exon of TaADH genes in Class I had 9, and the distribution of intron number was similar; the TaADH genes of Class II had 9 exons, and the position of intron number distribution was similar; the TaADH genes of Class had 8 exons ( Fig. 2A). In order to further clarify the protein structure of TaADHs family members in wheat, we identi ed the conserved motif ( Fig. 2B and Fig.   S1) using MEME software, and found that the number of motifs in Class I TaADHs protein was 12 (such as Motif 1-7-4-9-2-8-5-11-6-10-3-14). However, the TaADHs protein of Class II has 11 motifs (such as Motif 1-7-4-9-2-8-5-11-6-10-3), and that of Class was different from other motif composition patterns (such as Motif 1-4-7-12-5-13-3). In order to further analyze the functional domains of these proteins, we analyzed the functional structure of these genes (Fig. 2C). The members of wheat TaADH family have highly conserved functional domains, in which Class I TaADHs protein was mainly alcohol_DH_plant, Class II TaADHs protein was mainly alcohol_DH_class_ domain, while Class III TaADHs protein was Zn_ADH10. Generally speaking, these TaADH family members contained the typical structural domain of alcohol_DH.

Chromosomes distribution and synteny analysis
From the distribution of TaADHs on the wheat chromosomes ( Fig. 3A and 3B ), it was found that 22 TaADHs family members were mainly distributed on 15 chromosomes, of which there were 3 genes on chromosomes 4A, 4B and 4D, respectively. These genes have tandem replication events. To explore the collinear relationship of the TaADHs in the wheat genome and between the wheat genome and rice genome, collinear analysis was carried out by MCScanX method ( Fig. 3A and 3B). We found that there were 17 fragment replication events among members of the TaADHs family in the wheat genome, including three homologous gene pairs on chromosomes 1, 6 and 7, and fragment replication in TaADH15 and TaADH16 of chromosomes 5B and 5D. However, there were 7 fragment replication events (TaADH5-TaADH8, TaADH6-TaADH9, TaADH7-TaADH10, TaADH5-TaADH11, TaADH6-TaADH12, TaADH8-TaADH11, TaADH9-TaADH12) in chromosomes 4A, 4B and 4D, which were related to the tandem replication events on chromosomes 4A, 4B and 4D. A total of 9 pairs of syntenic paralogs were found in wheat and rice genomes (Fig. 3B), in which of TaADH6 corresponds to LOC_Os11g10510.1; TaADH8 and TaADH11 correspond to LOC_Os11g10480.1; TaADH17, TaADH18, and TaADH19 correspond to LOC_Os02g57040.1; TaADH20, TaADH21, and TaADH22 correspond to LOC_Os08g01760.1.

Evolutionary analysis
The non-synonymous substitution rate (Ka), synonymous substitution rate (Ks), and Ka/Ks for 64 duplicated pairs were calculated to reveal the selection pressure of wheat TaADH family genes in the process of evolution (Fig. 4A, Table S2). It was found that the Ka/Ks of these duplicated pairs were less than 1, which tended to a pure selection, indicating that the sequence similarity of TaADH genes was very high and relatively conservative in the process of evolution. The evolution time of the duplicated events of TaADH genes can be divided into three evolution periods (Fig. 4B, Table S2), of which 30 copies of TaADH duplication genes occurred about 11.19 to 16.42 million years (Mya), 12 copies of TaADH duplicated gene pairs occurred about 7.73 to 9.56 Mya, and the other 22 copies of TaADH duplicated gene pairs occurred about less than 6 Mya, the time period mostly before the wheat polyploidization event. It showed that although these genes sequences were conserved, they were different in evolutionary time.

The cis-regulatory elements analysis of TaADH genes in wheat
To further identify the cis-regulatory elements located upstream of the TaADH genes, we selected the 2K bp promoter region upstream of the CDS of TaADH genes and used TBtools software to predict and visualize the cis-acting elements (Fig. 5). There were a variety of cis-acting elements in the upstream promoters of these genes, which are responsive to 11 kinds of stress (hormone response, anaerobic response, defense, and stress response, drought induction, light response, low-temperature response, etc.). Except for TaADH13, the upstream promoters of other genes contain elements (ARE), that respond to anaerobic induction, and TaADH6 and TaADH9 contained as many as six cis-regulatory elements of ARE. We also found that the upstream promoter of TaADH4 contains 8 cis-regulatory elements (ABRE) responsive to abscisic acid. The upstream promoter of TaADH3 contains as many as 14 cis-regulatory elements (TGACG-motif and CGTCA-motif) responsive to Me-jasmonic acid.
Tissue-speci c expression patterns of TaADH genes in different tissues and organs In RNA-seq data of different tissues and organs in T. aestivum from, FPKM values of transcript accumulation of 22 TaADH genes were obtained from publicly available expression data sets, and then the corresponding heatmaps of relative expression levels were generated using Heatmap tool. The transcription levels in various T. aestivum tissues, including the roots, leaf, stem, spike, grain, and seeding were examined (Fig. 6). We found that except for TaADH2, there was no expression of TaADH6-7 in leaves, but the expression of TaADH6 was the highest in grain and that of TaADH7 was the highest in stems. The expression pattern of TaADH4 was similar to that of TaADH6, and the expression level was the highest in grains. The TaADH1 and TaADH9 expressions were only detected in grains and roots of wheat, but not in other parts of wheat, while the expression pattern of TaADH15 was opposite to that of TaADH1 and TaADH9.
The expression of TaADH genes in wheat seed under waterlogging treatment To further analyze the response of two wheat seed with different waterlogging tolerance to waterlogging stress during the germination stage, we analyzed the relative expression levels of 22 members of wheat TaADH family (Fig. 7). The results showed that the expression levels of seven TaADH genes (TaADH1/2, TaADH13, TaADH17, TaADH18, TaADH19, TaADH20) in the seeds of the intolerant variety Zhoumai 22 were signi cantly up-regulated at 24 hours after waterlogging treatment compared with the control treatment, but there was no signi cant difference in the expression levels of TaADH1/2, TaADH17, TaADH18, TaADH19, and TaADH20 genes compared with the control treatment 72 hours after germination, only the expression level of TaADH13 gene showed an upward trend. Compared with the control treatment, the expression levels of 14 genes (TaADH1/2, TaADH3-6, TaADH8-13, TaADH19, and TaADH20) in the seeds of Bainong 607 were signi cantly up-regulated at 24 hours after waterlogging treatment, while the expression levels of TaADH1/2, TaADH3, and TaADH9 genes were signi cantly up-regulated at 72 hours after germination compared with the control treatment, while the expression levels of TaADH5, TaADH6, TaADH14, and TaADH16 genes decreased. The results showed that the difference between waterlogging-tolerant and non-waterlogging-tolerant varieties after waterlogging treatment was closely related to the early and rapid expression of TaADH genes.

Discussion
In recent years, with global warming, extreme weather occurs more frequently, in which ood disaster is one of the abiotic stresses faced by plants, and hypoxia will rst occur in the ooded environment. Waterlogging-tolerant plants can often stimulate alcohol fermentation and reduce lactic acid fermentation to prevent acidifying cytoplasm. To avoid cytoplasmic acidosis, ethanol production is necessary for plants to survive under anaerobic conditions [17]. The role of alcohol dehydrogenase has been reported in many species [18][19][20]. With the development of sequencing technology, the genome sequences of many species can be analyzed, which promotes the identi cation of plant gene families at the genome-wide level. The ADH genes have been detected in various plants, including tomato [5], rice [21], barley [22], melon [7], and pear [8]. With the publication of the wheat genome, it is possible to systematically study the function of wheat TaADH family members.

Structural characterization of TaADHs
A total of 22 TaADH genes were identi ed in the wheat genome database, including 6 TaADH genes published by NCBI. In this study, we found that there are 8-10 exons and 7-9 introns of TaADH family members in wheat, which is consistent with the 8-9 introns of ADH genes reported by Strommer [23]. For example, the ADH2/3 in barley and the ADH in wheat contain 8 introns. While ADH1 and ADH3 in Arabidopsis thaliana contain 6 and 4 introns, respectively, and ADH in Chinese cabbage contains 5 introns [23]. The increase in the number of introns in common wheat (Triticum aestivum L.) indicated that the TaADHs family was expanding signi cantly in the evolution from lower plants to higher plants, and the expansion of the number of ADH members could enhance the ability of organisms to adapt to more complex environmental changes.
The plant ADH family usually divides into short-chain-ADH and medium-chain-ADH. Kitaoka et al. [21] found that there was only one short-chain alcohol dehydrogenase / reductase SDRs (OsMAS/SDR110C-MS1) in rice, which belonged to the short-chain-ADH type, while the other long-chain-ADHs were rarely reported [24,25]. 22 TaADH family members identi ed in this study belonged to medium-chain-ADH, and these genes have a highly conserved functional domain (GroES-like domain and zinc-binding domain) (Fig. 1A). This was similar to the structure of pear PbrADHs reported by Qin et al. [8]. ADH is a member of the medium-length dehydrogenase/reductase (MDR) protein superfamily. There is a typical domain of GroES-like in MDR, which is determined by chaperonin-10, based on its similarity to GroES molecular chaperone [26]. Association of Zn co-factors with a primitive MDR may have occurred in the early days of atmospheric oxygen, when Zn is likely to have been a preferred co-factor due to its valence stability [27]. From the perspective of evolution, Vv-ADH2 in grape [28], CmADH1 in melon [29] and At-ADH1 in Arabidopsis thaliana [30] all clustered in a class of medium-chain zinc-bound ADHs (Fig. 1B). Therefore, 22 TaADH genes in wheat belonged to the typical ADHs family.

Phylogenetic analysis and evolution of TaADHs
Gene replication is an important evolutionary process of gene family expansion, and the replicated genetic material provides an opportunity for functional differentiation. Functional differences caused by gene duplication are considered to be an important factor in species formation and environmental adaptability [31]. Therefore, gene replication analysis can help us better understand the evolution of genes and species. Two repetitive genes located on the same chromosome are called tandem replication. They exist on different chromosomes but come from the same subgenome, which is called fragment replication [32]. There are 4 gene tandem replication and 17 fragment replication events among members of the TaADHs family in the wheat genome (Fig. 3A). Most of the fragment replication events occurred in homologous chromosomes, such as chromosomes 1, 4, 6, and 7. In addition, there were gene collinearity between chromosomes 4, 6 and 7 in the wheat genome and chromosomes 2, 8 and 11 in the rice genome, which indicated that wheat polyploidy was the main reason for the expansion of TaADH family members, which also con rmed the conservatism of TaADH family members on individual chromosomes.
Ka, Ks, and Ka/Ks can well explain the history of a gene or gene region facing selection pressure [33]. In this study, we found that there were 64 duplicate gene pairs in the TaADHs family, and their Ka/ KS values were all less than 1 (Fig. 4B) Mya, all of which were earlier than the rst time of genomic replication in wheat [34]. The second time is that the subgenome of common wheat can be traced back to 300000 years ago, including Triticum urartu (A sub-genome) and the hybridization of the Aegilops speltoides to form tetraploid wheat (T. dicoccoides, A and B sub-genome). About 8, 000 years ago, tetraploid wheat, also known as the Aegilopstauschii (D subgenome, produced hexaploid wheat (T. aestivum, A, B, and D subgenomes) [35]. It showed that most of the TaADH family genes in wheat have undergone strict puri cation and screening in the process of evolution, and retained the original function through fragment replication events.
Expression pro le analysis of TaADHs Gene promoters are important factors in regulating gene expression patterns. They regulate gene expression at the transcriptional and post-transcriptional levels [36]. Cis-acting elements in a speci c promoter region participate in tissue-speci c expression patterns under various environmental conditions. In the corresponding upstream region for a gene, there was a positive correlation between the number of cis-acting elements and multiple stimuli [37]. Through the prediction of cis-acting elements of wheat TaADH family members, it was found that these genes were selected by a variety of biotic and abiotic factors (Fig. 5). Alcohol dehydrogenases catalyze the reversible conversion of aldehydes to the corresponding alcohols. They are involved in the stress response of plants and are mainly responsible for the production of ethanol in an anaerobic environment. At the same time, it is also widely involved in other stress, activator, and abscisic acid responses [38]. ADH has a good protective effect on hypoxia stress after ooding [39], as well as seed development and pollen aerobic metabolism [40]. There are many isozyme genes of ADH in the seed. Studies on tracking the activity of ADH during seed development have proved that ADH isozyme genes are active at different times. When seeds were under hypoxia stress at the germination stage, ADH activity might play a very important role in germination [23]. Three ADH genes (HvADH-1, HvADH-2, and HvADH-3) in barley were found, in which the activity of HvADH-1 during aerobic growth could be detected, while the expression of HvADH-1 and HvADH-2 could be induced by hypoxia, while the expression level of HvADH-3 under hypoxia was signi cantly lower than that of the other two genes [41]. Proels et al. [42]found that HvADH-1 was the only constitutively expressed in barley seedlings. However, ADH-3 activity could not be detected in barley leaves under any conditions.
In this study, it was also found that TaADH3, TaADH5, TaADH8, TaADH10-11, TaADH14, and TaADH16-22 were expressed in all parts of wheat. This suggested that these genes might also have constitutive expression. Manangkil et al. [22]con rmed that the expression of ADH1 and ALDH2a in rice seedlings increased rapidly under submergence stress, but decreased rapidly when submergence was removed, indicating that higher express levels of AHD1 and ALDH2a might be one of the reasons why rice is more tolerant to submergence than other plants. When wheat seeds were exposed to anaerobic environment (waterlogging treatment), TaADHs was expressed differently with different exposure time. No matter the waterlogging tolerant variety Bainong 607 or the intolerant variety Zhoumai 22, the expression levels of TaADH1/2, TaADH13, TaADH19, and TaADH20 genes at 24 hours after waterlogging treatment were signi cantly higher than those of the control treatment (Fig. 7). From the tissue expression analysis, it was found that the relative expression of these genes was the highest in grains, especially the speci c expression of TaADH1 and TaADH13 in wheat grains. This suggested that these genes might be induced the rapid expression under anaerobic stress. However, after 72 hours of germination, the relative expression levels of TaADH1/2, TaADH3 and TaADH9 genes in Bainong 607 seeds were signi cantly up-regulated compared with the control treatment. However, only the expression level of the TaADH13 gene increased at 72 hours after germination of Zhoumai 22 seed (Fig. 7). This showed that TaADH1/2, TaADH3, and TaADH9 played an important role in responding to waterlogging stress and served as an important basis for screening waterlogging-tolerant wheat varieties.

Conclusions
A total of 22 TaADH genes were identi ed and analyzed at the wheat genome. These genes were distributed on 15 chromosomes, of which there were 3 homologous genes on chromosomes 4A, 4B, and 4D, respectively, and there were tandem replication events in these genes. According to Pfam domain compositions, it was found that all these protein sequences contained the characteristic motifs of ADH (GroES-like domain and Zinc-binding domain).
Through phylogenetic tree analysis with other species, it was found that 22 TaADH genes in wheat belonged to medium-chain ADH type and were grouped into 3 subfamilies. Collinearity analysis within the wheat genome and between the wheat genome and rice genome showed that there were 17 fragment replication events among members of the TaADH family, while the number of collinear ADH gene pairs of wheat and rice was 9 pairs. According to the Ka/Ks and evolutionary years, it was found that there were 64 repetitive gene pairs with Ka/Ks less than 1, which tended to puri cation selection, indicating that strong purifying selection had taken place in the process of evolution of TaADH genes. Cis-acting elements and tissue expression analysis showed that these genes were responsive to 11 kinds of abiotic stress. TaADH3, TaADH5, TaADH8, TaADH10-11, TaADH14, and TaADH16-22 were expressed in all parts of wheat, belonging to constitutive expression, and other genes were speci cally expressed. By comparing the expression pro les of waterlogging-tolerant wheat Bainong 607 and waterlogging-intolerant wheat Zhoumai 22 at different germination stages after waterlogging treatment, it was found that TaADH1/2, TaADH3 and TaADH9 played an important role in responding to waterlogging stress, and could be used as an important basis for screening waterloggingtolerant wheat varieties. These results will provide valuable information regarding further functional elucidation of TaADH genes in wheat.

Wide-genome identi cation of TaADH genes in wheat
The whole-genome data was downloaded from the wheat genome database

Sequences alignment and evolutionary analysis of TaADH genes in wheat
The ADH protein sequences were downloaded from the genomes of Arabidopsis thaliana, Chinese spring wheat, rice, and muskmelon respectively. The protein sequences of these species were compared by ClustalW2 (http://www.genome.jp/tools-bin/CLUSTORW) software, and the phylogenetic tree was constructed  Exon-intron structures and motif compositions of TaADH proteins in wheat. The sequence information for each motif is provided in Fig. S1.  Cis-acting elements distribution and statistical analysis of TaADHs promoters. The color of the square depicts the quantity of the predicted cis-acting elements in the promoter region.

Supplementary Files
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text:
Design and Implementation of State-PID Feedback Controller for Poultry House System: Application for Winter Climate

A R T I C L E I N F O A B S T R A C T Article history: Received: 08 September, 2019 Accepted: 04 January, 2020 Online: 22 January, 2020 The poultry house is the area where the chickens are maintained for the main purpose to improve the productivity and the environmental conditions for the broilers. The growth of chickens inside the poultry house can be affected by several criterions such as relative humidity and temperature. In this paper, we propose to design and implement experimentally a state-PID feedback controller in order to achieve a high stabilization of the dynamics systems of the poultry process. The purpose of this study is to keep the temperature and relative humidity at desired values and to eliminate the disturbance generated during the winter climate. The effectiveness of the proposed controller is evaluated through numerical examples and with an experimental poultry house prototype. To feature more the efficiency of the proposed approach implemented, a comparative study has been conducted between the results achieved by the proposed method and the state-PI feedback controller and that of a state feedback controller.

Introduction
The poultry house climate is defined as the principal part that can straightforwardly influence the efficiency and comfort of the raising birds. Notwithstanding, the control of the housed livestock building remains a confounded errand because of the nonlinear behavior of psychrometric mechanisms required on both physiological and psychological components.
In most cases, the poultry farming is mainly affected by the outside condition (external relative humidity and temperature) and by the control of the actuators of the system (PAD cooling, heating, and ventilation system) [1]. Recently, the agricultural sector has extended altogether regarding control and optimization strategies for the primary parameters influencing good livestock management.
The hygro-thermal parameters are the most critical environmental variable on the poultry as announced in [2], [3]. Additionally, it has mutually been shown that the relative humidity and temperature affect intently the animal's improvement in Morocco because of the dominating weather and the country's location.
In this regard, we target our works to extend the ongoing studies by designing a suitable control strategy that is created depending on the mathematical model of broiler houses under cold conditions.
Over the most recent couple of years, the late research investigation demonstrates a tendency to the utilization of progressively different advanced procedures for control systems and simulation for a livestock building.
For the most part, it exists two types of control techniques, traditional techniques, and modern techniques. In such manner, numerous researches on livestock building concerning climatecontrolling have been suggested in the literature, for example, nonlinear robust control for pig house [4], nonlinear adaptive control for animals house [5], predictive control for temperature and humidity in a normally ventilated structure [6], SMC (Sliding Mode Control) to control both of interior temperature and relative humidity in an evaporative cooling system [7].
Others studies related to the optimization control have been developed in the livestock building, for instance, the application of ASTESJ ISSN: 2415-6698 the ant colony optimization (ACO) for control broiler house under hot climates [8] and the utilization of the particle swarm optimization (PSO) in the managing of the thermal requirement of the poultry house.
In other hands, the fuzzy logic controller has been well tested in a greenhouse and poultry house [9], authors are reasoned that is fuzzy controller was able to give a superior efficiency in the stability. Other researchers [10] and [11] have linked a PID with fuzzy controllers to control the temperature indoors poultry house, they had concluded that the fuzzy-PID structure has excellent performance over a PID controller as far as settling time and steady-state error. A comparison between fuzzy and on/ off controllers have been analyzed in [12] to test and keep up the ambient parameters inside a model poultry house. Accordingly, all these advanced control systems have demonstrated their similarity to be used on control structure applications for poultry houses.
In this paper, the present work describes an extension of the original work reported in Proceedings of the International Conference on Automation and Computing [13].
The contributions of this article are portrayed as looks for: (1) to design a state-PID feedback controller to guarantee nominal stability and to regulate the hygro-thermal parameter of the system to a given set point value. (2) Implement the proposed controller in a real poultry house prototype system.
Hence, the inspiration for the state-PID feedback controller in this manuscript originates from some papers dealing with a wide variety of systems such as the SISO and MIMO systems [14] , [15], [16].
The control configuration begins with the deduction of the linearized hygro-thermal model of the poultry process proposed in [17], at that point develops the state-PID feedback controller utilizing the eigenvalue assignment algorithm.
The remainder of the paper is formulated as follows: the primary segment exhibits quickly the hygro-thermal model of the poultry process. The second section describes the methodology of the state-PID feedback controller (SFCPID). Finally, some simulation results and remarks for stabilization and disturbance rejection are given to show the effectiveness of the proposed controller.

Hygro-thermal model
Considering the mathematical modeling of the previous work detailed in [17] and the proposed studies on climate modeling inside livestock buildings [6] [18], the hygro-thermal model administered the poultry house is: Where: The state space form of the model (1) is represented in equation (2). The study is conducted with the cold operations where the controller input related to the PAD cooling system isn't working (Eev = U2 = 0). 3 1 3 .
Where x are states variables associated with the internal relative humidity and temperature, u1 and u2 are the input controller associated with the heating system and the ventilation system, d are external disturbances.
The linearized model (2) can be simplified and represented to as a state space structure yielded (3): Where: C is the output matrix, B and Bd are the input matrix and A is the state matrix.

Local Stability
We recommended concentrating to study the global stability of the general system (nonlinear) from its linearized tangent.
Let us consider the nonlinear system expressed as: The linearized of the system around the operating point e x is: ).
The eigenvalues of the matrix are: It is clear that the process is locally on the cutoff of the stability, and requires stabilization with an appropriate controller.

State-PID feedback controller design
In this section, state feedback and PID controllers are designed for the linear state space proposed model of the broiler house process.

State feedback controller
Let's consider the LTI system which having the following form: x Ax Bu =+ (5) Where: The linear system under consideration must to be totally controllable, the controllability matrix must have a full rank-n [19][20] and can be communicated as 2 1 [ The pair (A, B) is controllable. Figure 1 illustrates the basic feedback controller of the poultry house. Where Yc, U, Y and Kx are the command signal, the control law, the output of the plant and the feedback controller, respectively. The control law can be composed on the structure: The objective of this controller is to stabilize the system by the constant feedback control that imposes to place the poles at desired characteristic behavior for the states.
Using the feedback control law (7), the closed-loop characteristic polynomial system is given by: The structure issue is to determine the feedback gain matrix Kx such that the closed-loop poles { 12 , ,..... n    } of the system (8) are appointed at the desired values.
The methodology proposed to this problem is accomplished by using the pole placement algorithm. The assignment placement algorithm concedes finding the matrix Kx, such as the closed-loop, system is stable. Both i  the desired closed loop poles and i  the eigenvector relating.
The following steps present the algorithm used for the assurance of the gain components of matrix Kx is: [21] 1. ( )

State-PID feedback controller
In this area, we introduce the proposed strategy control; we use in conjunction the state feedback and the PID controller. The Proportional Integrator Derivative structure is one of the most controller broadly utilized in the industry, covering more than 90% of the industrial need in control. This predominance is because of its simplicity to implement it in a large plant does not require detailed knowledge. The control block scheme is shown in figure 2. The control law u of the state-PID feedback proposed controller is : Where ( , , ) are the planned gain matrices to achieve a desired closed-loop system. In summary, the problem described is resolved for a pole placement method consisting of three separated steps as mentioned in Guo et al [22]. The pole placement by state-P feedback is directed first prompting an intermediate system. Furthermore, state-I feedback is executed; another transitional system resulted. At last, the closed-loop system with the desired characteristic polynomial is acknowledged by state-D feedback joined as the final plan configuration.
The components of state-PID controller gain matrices for the PID structure can be obtained using the transformation into Frobenius canonical form detailed in [23], [24] and the equations mentioned in [15].

Results and discussions
In this analysis, we suggest regulating the internal temperature Tint and relative humidity Hint under cold climates, for that we design the state-PID feedback controller to get synchronization to deal with both ventilation and heating systems.
To affirm the performance of the proposed state-PID feedback controller, several comparative illustrative simulations are delineated.

Case 1: simulation study
The industrial poultry house system was equipped with controller natural ventilation, heating and PAD cooling system, the livestock building dimensions were 12,4m x 120m x 3,85m.
The real plant data have been saved for the entire period for the chickens raising of [20][21] Table 1 presents the numerical estimations of the distinct criterions used in the simulation of the proposed controller.

Design of state feedback controller
The conventional (SFC) design technique begins with the determination of the desired eigenvalues from the given specifications of the controller Kx : d  of an order of multiplicity respectively (n) and (n-1).
The basis of controllability is verified of the system (2) after including the different parameters: The specifications considered for the poultry house system are selected primarily on diminishing the steady-state error and the settling time. After choosing the desired pole and applying the assignment eigenvalues algorithm, we find: The input control of the system is :

Design of state-PID feedback controller
The feedback gain matrix is computed as: The PID gain matrices is obtained as :

Stability analysis
The comparison of the closed loop response of the hygrothermal parameters concerning the desired values of poultry house system with conventional state feedback, state-PI feedback and state-PID feedback controller using the package Simulink of MATLAB are demonstrated in figure 4 and 5.
For numerical simulation, the desired relative humidity and internal temperature have been fixed at 66% and 26°C.   From table 2, it appears that the state feedback controller gives poor results compared to that of state-PI and PID feedback controller in control of temperature. Other hands, the SFCPI gives a slow response compared to that of state-PID feedback state and a state feedback controller. Furthermore, the SFCPID affords the littlest value of rise time evaluated at 1,21s and the smallest value of settling time estimated at 1,49s.
It tends to be additionally observed that the performances indicated by the proposed controller are closely at their best values. The transient responses of states are plotted in figure 6 and 7.     From figures 6 and 7, it can be noticed that the derivative of the internal temperature accelerates rapidly within the state-PID feedback controller compared to that of SFCPI and that of state feedback. Also, it can be observed that the derivative response converges to zero after a short duration and this proves that the internal temperature and relative humidity have been well stabilized.

Disturbance rejection
The temperature and humidity response under the external disturbance with the three controllers are displayed in figures 8 and 9.
From figures 8 and 9, it very well may be obviously observed that with our proposed controller that the system reactions quicker, and recuperates totally from the external disturbance without any residue errors. This is because of a derivative and integral parameters acting as an error corrector.
Furthermore, it tends to be seen that the planned state-PID feedback controller maintains the internal temperature and relative humidity within a short time of 7 seconds after applying a disturbance; however, the conventional state feedback controller isn't able to reduce or eliminate the external disturbance in both of temperature and relative humidity response.

Case 2: Experimental poultry house prototype
The poultry house prototype has two main actuators, namely, the electric heater and the fans systems. Other subsystems contain lighting and evaporative cooling systems are also installed. The system program includes the main algorithm unit for all systems in the broiler house. In addition, the experimental data is transmitted to the computer device using a micro controller. The real data is monitored with the LabVIEW software; the users can control the important operations and can to be informed of the various changes for the system. (See figure 10) The internal temperature is measured using LM35 and the relative humidity is acquired via HIH4030 sensor. The variable input of heating and ventilation system are fitted with a thyristor driver circuit in order to produce a varying voltage for running the fans and the heater at different level speed and stage. The change in applied voltages is legitimately relative to the airflow speed and heating rate.
The three controllers are implemented for the poultry house prototype and experimental results of the temperature and relative humidity response are represented in figures 11 and 12.  Relative humidity response the state-PID feedback controller provide a better response for relative humidity and temperature response with a very smooth variation in tracking the desired set points.

Conclusions
In this article, we have proposed and designed a state-PID feedback controller for stabilizing the relative humidity and temperature indoor the broiler house process during the colds conditions.
Numerical examples are tested to confirm the effectiveness of the proposed design controller to stabilize the system. On the other, we have considered the existence of disturbance simulated as the external perturbations getting from the outside climate. The results of simulations show that the proposed methodology was proficient regarding dynamic performance, for example, a decrease of settling time and rise time. Moreover, the SFCPID was capable of tracking the desired set point with a rapid rate of convergence. Thus, the proposed controller has proven its performance through the simulations under disturbance and the comparative study conducted between the state feedback and state-PI feedback technique and the state-PID feedback controller.
In addition, the proposed controller is implemented for the real experimental poultry house prototype. It is concluded that the proposed state-PID feedback controller affords excellent performance than the state-PI feedback and state feedback controller in terms of following the set points parameters.
Finally, it is pointed out that the proposed control methodology of the poultry house accentuates the regulation of the system and the optimal parameters.


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Effects of Potassium and Humic Acid on Amelioration of Soil Salinity Hazardous on Pea Plants

Pots experiment were carried out in green house of National Research Centre, Dokki, Egypt, to study the effect of potassium and humic acid application to minimize the adversely effects of soil salinity on pea plants. Pots were divided into three main groups of soil salinity at levels (2.84, 6.03 and 8.97 dS m). These main groups were applied potassium sulfate at the rates 50 and 100 kg fed -1 . Foliar application of humic acid was applied at a rate of 0.2%. Data presented that the application of K2SO4 at a rate of 100 kg fed -1 with humic acid a foliar spray at a rate of 0.2%, gave the highest values of plant growth parameters such as, Branch No., Leave No., Plant height, leaf area, Shoot fresh and dry weight. In addition to produce high chlorophyll a and b and carotene content as compared to other treatments and control under the different soil salinity levels. Application of K2SO4 (100 kg fed ) with foliar spray of humic acid under high and moderate soil salinity condition increased pod weight, seed weight, seed dry weight over application of 50 kg fed and control. The highest values of studied chemical constituents in shoots and greens were obtained due to the application of potassium sulfate at100 kg fed -1 with humic acid. The combined Original Research Article Basha et al.; AJSSPN, 5(4): 1-10, 2019; Article no.AJSSPN.55566 2 effects of potassium application and foliar spray of humic acid had a positive effect on increasing the ability of pea plant tolerance to soil salinity and increasing of growth and yield production under saline soil conditions.

INTRODUCTION
Salinity is became one of the most serious environmental problems that caused great reduction on growth and development of plant species. In fact Salinity is one of the major yield limiting factors for crop plants mainly in arid and semiarid regions of the world [1]. In Egypt the problem is aggregated due to overuse of fertilizers and shortage of good irrigation water. Therefore, many trails and approaches have been attempted to mitigate the well-known negative effects of salinity on plant growth and production [2,3]. Naghmeh et al. [4] conducted a series of experiments to evaluate the effect of HA on qualitative and quantitative characteristics of perennial ryegrass. Different concentrations of HA (0, 100, 400, and 1000 mg L −1 ) were applied monthly as foliar application. Results showed that leaf phosphorus (P), potassium (K), and zinc (Zn) content, fresh and dry weight, chlorophyll content, and root fresh weights were not affected by HA. Meanwhile, HA improved the root and shoot development, except for root fresh weight. While just 100 mg L −1 improved height, visual quality, nitrogen (N) content, roots length, and surface of roots, all of HA concentrations were effective on iron content. These results suggest that HA foliar application might be of benefit to enhance some nutrients uptake and root development of ryegrass possibly leading to improved drought resistance.
Nitrogen, phosphorus and potassium are key nutrients that play a major role in crop production on intensively cultivated soils. The soil fertility is directly influenced by the type of fertilizer inputs [5].
Pea (Pisum sativum L.) is one of the most important leguminous vegetable crops grown during winter season in Egypt. Its seeds contain 18-20% dry matter whose 10-12% is carbohydrate and 5-8% is protein [6]. Pea is used as a fresh vegetable, frozen or canned. According to FAO 2004 data, about 12.2 million tons of pea production were achieved in 6.3 million ha agricultural lands of the world with an average yield of 1.930 kg ha -1 (Anonymous, 2007). It occupies a great figure in the local consumption and export. The total area grown with garden peas in Egypt was 47951 fed, which produced 180631 ton with an average yield 3.77 ton fed -1 , while dry peas was 162 fed and average productivity 0.77 ton fed -1 according to agricultural statistics, Ministry of Agriculture, 2012). Among those approaches is the improvement of plant nutritional status via external supplements to ameliorate salinity damages with exogenous application of K + in wheat [7]. Furthermore, some beneficial mineral nutrients have been studied that can counteract adverse effects of salt stress.
Potassium play vital role and stimulates biological process in the plant cell as enzymes activity, respiration, photosynthesis, chlorophyll, carbohydrate, formation , water amounts balance in leaves and regulate stomata opining as well as direct effect on the disease desistance [8]. One of the mechanisms for improving plant tolerance to salinity is to apply potassium, which seems to have beneficial effects potassium fertilization mitigates the adverse effects of salinity in plants by increasing translocation and maintaining water balance within plants (Greenwood and Karpinets, 1997). Hussein et al. [9] found that spraying pepper plants with potassium (200 ppm) increased the plant growth, biomass production, and fruit yield. While, chlorophyll content and total phenols significantly increased with foliar application with 100 ppm of potassium. Elsharkawy [10] indicated that foliage fresh and dry weights, No. of pods per plant, weight of pods per plant, total yield fed -1 , N, protein and K content in green pea seeds were significantly and positively affected by increasing potassium levels and the maximum promotion was detected at 48 kg K 2 O fed -1 . Balpande et al. [11] stated that significantly high seed yield and quality of pea plant were observed due to application of 30 kg K 2 O ha -1 .
Humic acid is one of the most important components of bio-liquid complex, due to its molecular structure, it provides numerous to crop production. It helps break up clay compacted soils, assists in transferring micronutrients from the soil to the plant, enhance water retention, increases the rates of seed germination, improves water, air and roots penetration and stimulates development of microflora population in soils [12]. Stumpe et al. [13] stated that the positive effect of humic acid on the yield capacity of soil consists of many components. Moreover, some researchers showed that the foliar spray of humic acid enhanced nutrient uptake, plant growth, yield and quality in a number of plant species [14] at least partially through increasing nutrient uptake, serving as a source of mineral plant nutrient uptake and regulator of their release [15]. Behzad Sania [16] studied the effects of the foliar application of humic acid on plant height in canola spring cultivar. The results showed that foliar application of humic acid significantly affected plant height and highest this parameter was achieved under 2% foliar application of humic acid and the lowest plant height was obtained under control conditions. Also, means comparison showed that plant height under 0.5% foliar application of humic acid and 1% foliar application of humic acid were in a similar statistical group. The results showed that foliar application of humic acid decreased nitrogen application in soil, that can be the most important for the non-pollution of soil by nitrogenous fertilizers.
Direct effect are those, the uptake of humic substances into the plant tissue resulting in various biochemical effects through elevate uptake and maintaining vitamins and amino acids level in plant tissues. Geries (2013) indicated that foliar spraying of onion plants with humic acid at the rate of 2 kg fed -1 at 60, 80 and 100 days after transplanting markedly increased vegetative growth, bulb yield and its components, onion quality and chemical composition in two seasons. The objectives of this study, to evaluate the effect of using potassium and humic acid on growth and nutrient content and seeds quality of pea plants under saline soil condition.

MATERIALS AND METHODS
Pot experiments were carried out in the green house of the National Research Centre, Dokki, Egypt, to study the effect of potassium and humic acid application to minimize the adversely effects of salinity on pea (Pisum sativum L.) plants.
Plastic pots (30 cm in diameter) were filled with 10 kg soil deferred in their salinity levels (2.84, 6.03 and 8.97 dS m -1 ). Physical and chemical analyses of soils used in the experiment were determined according to the methods reported by Rebecca [17] and presented in Table 1.
Pots were divided into three main groups of soil salinity at levels (2.84, 6.03 and 8.97 dSm -1 ). These main groups were applied potassium sulphate at a rate of 50 and 100 kg fed -1 to the soil surface beside plants after 1, 3 and 5 weeks after transplanting. Foliar of humic acid was applied at the rate 0.2% in the same times. Each pot received 2.2 g of calcium superphosphate (15.5% P 2 O 5 ) before sowing and 3.0 g ammonium nitrate (33.5% N) added two weeks after sowing. In each pot, 8 grains of pea (Pisum sativum L.) cv. Master B plants were sown at 15 November 2017. The seedlings were thinned to three plants per pot two weeks after sowing. Plant samples were collected at 45 and 90 days after sowing.

Statistical Analysis
Data were statistically analyzed by using factorial completely randomized design. The means were compared using the least significant difference test (LSD) at 5% level according to Gomez and Gomez [21].

Vegetative Growth Characters
Data presented in Table 2  ).These results are in agreement with those obtained by Bekheta et al. [22]. The reduction in vegetative growth characters due to salinity may be attributed to the harmful effects of salinity on many metabolic processes including, activity of mitochondria and chloroplasts [23,24,25].
Application of potassium sulfate at a rate of 100 kgfed -1 with the humic acid a foliar spray at a rate of 0.2% gave the highest values of plant growth parameters such as, Branch No., Leave No., Plant height (cm), leaf area, Shoot fresh weight and Shoot dry weight Data in Table 2 show that spraying pea plants with humic acid produced the tallest plants and the highest values at about 19.6, 18.6, 26.1, 16.4, 12.5 and 26.5% respectively, as compared with application of potassium sulphate individual at a rate of 100 ppm. Humic substances have been reported to influence plant growth both directly and indirectly. The indirect effects of humic compounds on soil fertility include, increase in the soil microbial population including beneficial microorganisms, improved soil structure and increase in the cation exchange capacity and the pH buffering capacity of the soil [26]. Humic acid (HA) compounds may have various biochemical effects either at cell wall, membrane level or in the cytoplasm, including increased photosynthesis and respiration rates in plants, enhanced protein synthesis and plant hormone like activity [27]. HA may stimulate shoot and root growth, and improve resistance to environmental stress in plant, but the physiological mechanism has not been well established [28,29].

Chlorophyll Contents
Increasing the soil salinity levels from 2.84 and 8.97 dS m -1 significantly decreased the chlorophyll a and b and carotene contents. However, the application of potassium sulfate with HA as foliar spray decreased the deleterious effect of salinity on the chlorophyll content. Application of potassium sulfate at 100 kg fed -1 produced the higher chlorophyll a and b and carotene as compared to the other treatments and control under the different soil salinity levels (Fig. 1).
The reduction in plant growth and yield due to salinity might be attributed to the inhibiting effects of salinity on many metabolic processes including, activity of mitochondria and chloroplasts [23]. El-Bagoury et al. [30] suggested that, biosynthesis of chlorophylls in generally might be inhibited by the depressive effect of stress conditions on the absorption of some ions involved in the chloroplast formation, such as Mg and Fe and/or an increase of growth inhibitors, such as ethylene or abscisic acid production which enhance senescence. Carotene content was significantly reduced by increasing salt concentration of the growth compared with the control plants grown under low saline soil with EC = 2.84 dS m -1 . These results agree with Ghassemi-Golezani et al. [31].

Yield Parameters
Data in Table 3  ) over application of 50 kg fed -1 and control. The enhancing effect of potassium sulfate treatments may be due to the role of potassium in photosynthesis, transpiration, opening and closing of stomatal, synthesis of protein, translocation of assimilates and activation of enzymes [8]. Obtained findings are in compliance by those reported by Doaa et al. [32] and Farid et al. [24].

Chemical Constituents in the Shoot and Grain
Data in Table (4 and 5) indicated that, soil salinity stress significantly decrease in N,P, K and Ca content, however reduction was lower at low salinity level (2.85 dS m -1 ) than the two levels (6.03-8.97dS m -1 ). In grain also a gradual adverse in N contents were recorded with increasing salinity level. Nitrogen was accumulated in the plants grown under saline conditions especially at moderately saline (6.03 dS m -1 ) and strongly saline (8.97 dS m -1 ) compared to control values. It may be related to an adaptation mechanism developed by the plants to overcome osmotic stress caused by salinity while decrease in nitrogen may be due to the antagonistic relation between toxic Cl and NO -3 [33].
Potassium content was lower in plants (shoot and grain) grown under saline soil conditions than those grown in low saline soil. Application of potassium sulfate at the two rates comber of control treatment (non application of potassium) significantly effected in N, P and K content of Pea shoot and grain. The highest mean values of studied chemical constituents in the leaves and seeds were obtained due to the application of potassium sulfate at 100 kg/fed with humic acid. The attractive effect of potassium at various rates on chemical constituents in shoot and grain may be due to the role of potassium in activation of vegetative growth, yields, and its components as mentioned formerly, consequently enhancement chemical constituents in the shoot and grain. These results are in conformity with those reported by Balpande et al. [11]. Concerning, the effect of foliar application with humic acid on Pea chemical composition, results in the same table showed that foliar application with humic acid resulted in the highest values of N, P and K% as compared with control treatment. Humic substances have much preformed influence on the growth of plant roots. When humic acids are applied to soil, enhancement of root initiation and increased root growth may be observed [34]. Stimulatory effects of humic substances have been directly correlated with enhanced up take of macronutrients, such as N, P and K and micronutrients, which are, Fe, Zn, Cu and Mn [27]. Also, data in Table 5 show that, sodium content was increased with increasing soil salinity levels but calcium content was lower in plants (shoot and grain) grown under saline soil conditions than those grown in low saline soil. Calcium: Sodium ratio was significantly lower under salinity stress. Potassium application enhanced Ca/Na selectivity ratio in pea thus enhancing pod and shoot yield. Application of 100 kg/fed potassium sulfate in the high salinity soil increased the Ca: Na. The exclusion of Na + ions and a higher Ca: Na ratio in pea plants grown under saline conditions have been confirmed as important selection criteria for salt tolerance [35]. Therefore, the results shown in Table 5 agree with experimentations with Pea plant by Abdelhamid et al. [35] which indicate that salt tolerance is associated with an enhanced K: Na discrimination trait. The ability of plant to limit Na transport into the shoot is critically importance for the maintenance of high growth rates and protection of the metabolic processes in elongation cells from the toxic effects of Na [36].

CONCLUSION
Potassium sulfate with foliar spray of humic acid under high and moderate soil salinity condition a promotive effect on growth parameters, Such as; pod weight, seed weight, seed dry weight over application of 50 kg fed -1 and control. The highest values of studied chemical constituents in shoot and grains were obtained due to the application of potassium sulfate at 100 kg fed -1 with humic acid. Generally, interaction between of potassium addition and foliar spray of humic acid had a positive effect on increasing the ability of pea plant tolerance of high salinity levels and increasing of growth and yield production under saline soil conditions.


extfieldsofstudy: Medicine Biology

text:
Epidemic patterns of antimicrobial resistance of Salmonella enterica serovar Gallinarum biovar Pullorum isolates in China during the past half-century

Pullorum is a chicken-specific systemic disease caused by Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum). This study was carried out to provide basic data for understanding the trends of S. Pullorum. A total of 652 S. Pullorum isolates collected in China during 1962–2019 were examined. Overall, 525 (80.5%) isolates were resistant to at least one antibiotic; 280 (42.9%) isolates resisted 3 or more classes of antibiotics and showed an increasing trend until 2015 and then decreased significantly. The most common multidrug-resistant pattern was ampicillin–tetracycline–nalidixic acid (13.6%). After 2008, 6 classes of antibiotic-resistant strains began to appear, and they have been prevalent ever since. In 2014, a strain resistant to 7 antibiotics (ampicillin–cefazolin–streptomycin–tetracycline–sulphonamides–nalidixic acid–nitrofurantoin) was isolated. The highest antimicrobial resistance was observed for nalidixic acid (71.9%), and the lowest was found for cefotaxime, meropenem, amikacin, gentamicin, fosfomycin, and polymyxin (0%). Our findings monitored the prevalence of the resistance of S. Pullorum during the past half-century in China. Continued surveillance of antimicrobial resistance and the rational use of antimicrobials is necessary and important to control the rapid increase in antimicrobial resistance in S. Pullorum.

INTRODUCTION
Salmonella is an important pathogenic bacterium capable of infecting humans and animals. Salmonella enterica serovar Gallinarum biovar Pullorum (S. Pullorum), a strictly chicken-adapted pullorum agent, is one of the more than 2,610 documented Salmonella lineages (Issenhuth-Jeanjean et al., 2014). Pullorum is a bacterial disease that results in high mortality in young chicks. Owing to its vertical and horizontal transmission, it is a threat to the modern poultry industry, causing great economic loss (Shivaprasad, 2000).
Although pullorum disease is well controlled in many developed countries, it remains common in many parts of the world. Antimicrobial therapy is being used as an important measure to control poultry disease in China, although the use of antimicrobials in controlling pullorum disease is not recommended. However, abuse of antimicrobial agents in industrial food animal production is regarded as one of the important reasons for the emergence of antimicrobial resistance in Salmonella. Moreover, the increasing appearance of multidrugresistant (MDR) S. Pullorum has been increasingly observed in China (Nhung et al., 2017). This resistance can be transmitted to humans through animal foodstuffs, which poses a serious threat to public health. This study examined the tendency and the pattern of S. Pullorum to become resistant to antimicrobials with 1 time. It also explored whether resistance trends have changed under national policies to reduce and ban the use of antibiotics.

Bacterial Isolates
A total of 652 S. Pullorum isolates collected over 58 consecutive years, from 1962 to 2019, were included in the study. The isolates were cultured from chickens with clinical signs of pullorum disease. All bacterial strains were isolated from the liver, except for 8 strains that were isolated from feces, of chickens in 10 different provinces in China: Jiangsu, Shandong, Xinjiang, Shanxi, Anhui, Shanghai, Beijing, Henan, Zhejiang, and Jilin (Supplementary Table 1). The study used the culture method of Gong et al. (2013) and Zhou et al. (2018). Once identified, the isolates were stored at 270 C in tryptic soy broth containing 30% glycerol.

Data Analysis
The results were interpreted as per the European Committee on Antimicrobial Susceptibility Testing and Clinical and Laboratory Standards Institute breakpoints (EUCAST, 2016) (Supplementary Table 2). Multidrug resistance was defined as resistance to at least 3 different classes of antimicrobials (MDR 3). Magnitude of annual change was estimated by using a slope parameter, Q, and the Sen nonparametric method. Calculations were performed by using the Excel (Microsoft, Redmond, WA) . Trend and Sen slope estimates were tested by template Mann-Kendall. A t-test was used to test the difference between means using GraphPad Prism 8 software (GraphPad, La Jolla, CA). A P-value ,0.05 was considered statistically significant.

RESULTS AND DISCUSSION
Overall, 80.5% (525) of the Salmonella isolates were resistant to at least one antimicrobial, and none were resistant to all 18 antimicrobials. The isolates exhibited the highest frequencies of resistance to NAL (71.9%), followed by TET (38.5%), AMP (27.9%), and SXT (32.1%). Relatively lower rates were observed for CFZ (8.4%), STR (4.3%), ATM (0.2%), CIP (0.3%), CHL (0.6%), OLA (0.6%), FFC (0.5%), and NIT (0.3%). None were resistant to CTX, MEM, AMK, GEN, FOS, and CL (Table 1). In China, AMP, TET, and SXT have been commonly used to control pullorum disease for a long time. Moreover, the irrational use of antibiotics may explain the high and increasing resistance rates in the period from 1962 to 2014 (Ministry of Agriculture and Rural Affairs of the People's Republic of China [MAPRC], 2013; Yang et al., 2013;Lai et al., 2014). By contrast, the Ministry of Agriculture and Rural Affairs of the People's Republic of China (2015a,b) policies for comprehensive administration of veterinary drugs from 2015 to 2019 might explain the decline in the resistance to AMP, CFZ, STR, TET, SXT, and NAL since 2015 ( Figure 1). That was limited to use antimicrobials such as CFZ and so on. In addition, it is forbidden to change the dosage and the exaggeration of indications in the instructions, to use of antibiotics beyond the market circulation period, and to add antibiotic drugs illegally (Ministry of Agriculture and Rural Affairs of the People's Republic of China [MAPRC], 2002b).
Resistance to AMP was observed in 27.9% of the isolates. In addition, the resistance of S. Pullorum strains to AMP increased between the periods 1962-1999 and 2000-2019 (P , 0.001). Previously, a high level of AMP resistance by the Salmonella Gallinarum isolate was reported in Korea from 1995 to 2001 (Lee et al., 2003) and from 2002 to 2007 (Kang et al., 2010) and in China from 1962 to 2010 (Gong et al., 2013). Different to that found for AMP, a low level of resistance to CFZ was observed throughout the period studied (8.4%), which could be because of the limited use of these classes of antimicrobial agents in veterinary health sectors of China and concurs with previous studies conducted in other countries (Wang et al., 2017;Youn et al., 2017). All isolates were susceptible to CTX, similar to published studies (Taddele et al., 2012;Penha et al., 2016) but contrary to another report from Chinese researchers (Gong et al., 2013). This discrepancy could be explained by the high cost of the third-generation cephalosporins (e.g., CTX) or the successful efficacy of the firstgeneration cephalosporins (e.g., CFZ), which are rarely used in chickens. The isolates displayed a low level of resistance to the aminoglycosides. All isolates were susceptible to AMK and GEN. Resistance to AMK was not frequent, which is consistent with that reported elsewhere (Lee et al., 2003;Parveen et al., 2007). The strains showed low resistance to STR (4.3%). Similar results have been reported in Korea (Kang et al., 2010) but differ from those previously reported in China (Pan et al., 2009). All of the isolates were susceptible to STR after 2015 (P , 0.01). Nhung et al. (2017) also found that the resistance to SUN ET AL. STR was high and then decreased from 2010 to 2012. One possible reason is that STR is rarely used in veterinary clinical settings. This idea supports the position that STR is not approved for use in feeds (McChesney et al., 1995).
High rates of resistance to SXT (32.1%) and TET (38.5%) were found among the isolates throughout the study period. The resistance to SXT and TET increased from 5.3 and 6. 3%, respectively, in 1980-2014 to 45.7 and 52.7%, respectively, in 1962-2014 (P , 0.01). Since 2015, their trends have been downward. Similar effects have been reported by other researchers (Threlfall et al., 1997;Manie et al., 1998). Salmonella strains isolated from poultry with a high level of resistance to SXT and TET were also reported as widespread in previous studies (Thakur and Bajaj, 2006;Zhao et al., 2007). In poultry, TET is used in day-old chickens as a single injection or administered via the drinking water to control infection by Salmonella and E. coli (Levy et al., 1976). Sulphonamide compounds were commonly used to control pullorum disease. Perhaps, these antimicrobial drugs have not been frequently used for the treatment of pullorum disease in China since 2015 (Krishnasamy et al., 2015;Tang et al., 2016;Qiao et al., 2017).
There were few isolates resistant to amyl alcohols; 0.6% of the isolates were resistant to CHL. There were only 4 resistant strains from 1962 to 2009 and none after 2009. There were only 3 strains resistant to FFC be-tween1962 and 1999, and no resistant strain has emerged since 2000. Chloramphenicol has been banned in food animals since 2002 in China (MAPRC, 2002), which explains why there have been no resistant strains since 2009. Similar effects have been reported by other researchers (Taddele et al., 2012;Dey et al., 2016). Florfenicol is a structural analog of CHL that was approved in China in 2002 for use in veterinary medicine (White et al., 2000). However, the resistance to FFC was low. Perhaps, this is because its resistance mechanism is not common. A group of researchers found similar results (Penha et al., 2016).
From 1962 to 2019, the strains were highly resistant to NAL, with MIC 50 and MIC 90 values of 256 and .512 mg/ mL, respectively (Table 1). However, the isolates showed low levels of resistance to CIP (0.3%), and the resistance existed only during 2000-2014. It may be that these drugs were forbidden used. Similar effects have been reported by other researchers (Taddele et al., 2012;Dey et al., 2016). In line with other studies (Padungtod and Kaneene, 2006;Cheong et al., 2007), we found that Salmonella, found predominantly in chickens, emerged as particularly resistant to the quinolone NAL after 2000 (P , 0.05).
Long-term use of antimicrobial agents causes the accumulation of drug residues and many other public health problems (Barrow et al., 2012). Multidrugresistant strains were observed in 42.9% of the isolates recovered in this study. The isolates showed an increasing trend of MDR strains between 1962 and 2014 (P , 0.001), and then, the trend declined after Table 1.

Characteristics of antimicrobial resistance of S.
Pullorum isolates in terms of years.  Krishnasamy et al., 2015;Tang et al., 2016;Qiao et al., 2017). Since 2000, meat production has plateaued in high-income countries but grown by 68, 64, and 40% in Africa, Asia, and South America, respectively (Van Boeckel et al., 2019), which is concurrent with a dramatic increase in strains with resistance to one or more classes of antimicrobials. In the period of 1962-1979, resistance to 5 or more drugs was not observed. However, during 1980-1999, 1.8% of the isolates were resistant to 5 classes of antimicrobials. In the span of 2000-2009, 1.5% of the isolates were resistant to 5 or more antimicrobials. The number of isolates exhibiting resistance to 4 or more antimicrobials increased from 7.0% during 2000-2009 to 37.8% in 2010-2014. It is noteworthy that from 2000 to 2019, 4.1% of the isolates were resistant to 6 antimicrobials. In 2014, there was a strain resistant to 7 classes of antimicrobials (Figure 2). Although the trend of drug resistance presents an obvious downward trend, it is projected that antimicrobial consumption will rise by 67% by 2030 and nearly double in Brazil, Russia, India, China, and South Africa. This rise is likely to be driven by the growth in consumer demand for livestock products in middle-income countries. We should call for initiatives to preserve antibiotic effectiveness (Thomas et al., 2015;Founou et al., 2016).
The resistance patterns of S. Pullorum isolates were further analyzed. There were 62 unique resistance patterns among the strains resistant to 3 or more antimicrobials of the total 652 S. Pullorum isolates. The most common MDR patterns were AMP-TET-NAL  Numbers "0" to "7" and the corresponding shadings indicate that isolates are resistant to 1, 2, 3, 4, 5, 6, and 7 antimicrobial agents, respectively.
This article is also the first to study the changes in resistance of S. Pullorum through time under national policy conditions. The Salmonella isolates showed an overall increasing trend of antimicrobial resistance and  Abbreviations: AMP, ampicillin; ATM, aztreonam; CFZ, cefazolin; CHL, chloramphenicol; FFC, florfenicol; NAL, nalidixic acid; NIT, nitrofurantoin; OLA, olaquindox; STR, streptomycin; SXT, sulphonamides; TET, tetracycline. TRENDS OF SALMONELLA PULLORUM RESISTANCE MDR patterns between 1962 and 2014, which declined after 2015. Most of the S. Pullorum strains were resistant to NAL, mainly after 2000. High levels of resistance were found for AMP, TET, and SXT. As per these results, we suggest strengthening the monitoring programs for pathogenic bacteria and their drug resistance in veterinary clinical practice and the food production chain. The results also suggest that the promotion of national policies is another important measure to reduce the emergence of drug-resistant strains. Moreover, interventions, such as vaccines and probiotics, can be considered to reduce salmonellosis.

DISCLOSURES
The authors declare no conflicts of interest.

SUPPLEMENTARY DATA
Supplementary data associated with this article can be found in the online version at https://doi.org/10.1 016/j.psj.2020.12.007.