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Comparison of Soil Erosion Control by Mulch and Cultivated Grass

Soil erosion has deteriorated water quality and caused land degradation. As human industrialization quickens, the effects of soil erosion are getting worse. Therefore, it is essential to have an effective mitigation measure at hand to solve this problem. In this research, two types of erosion control methods were compared to determine their effectiveness in controlling soil erosion. The two methods used were mulch made from dried grass clippings and grass cultivation grown with Axonopus compressus or more commonly known as cow grass. The plots were placed under five rainfall events together with a control plot. The runoff volume, turbidity and total suspended solids (TSS) from the plot discharges were tested and compared. The effectiveness of each erosion control method under different rainfall conditions were also evaluated. Results indicated that the mulch plot produced a lower runoff volume but the grass plot did manage to improve performance over time. The turbidity of both plots were similar. The TSS produced by the grass plot was lower than the mulch plot in 4 out of the 5 testing periods. The grass plot also performed better in longer duration and high intensity rainfall events. The mulch was able to produce similar results with the grass in short duration, low or moderate intensity rainfall events. As a conclusion, the grass cultivation is a more effective erosion control method when compared to the mulch.

Introduction
Soil erosion is a removal of topsoil due to human, natural or animal activities in our environment. Generally, the topsoil is removed faster than natural soil forming processes that can replace it [1].
Globally, there are numerous environmental, social and economic problems caused by soil erosion. The main environmental problem associated with soil erosion is the decrease in water quality as a result of runoff. Turbidity and total suspended solids (TSS) can prevent sunlight to penetrate water. In addition, the eroded soil can change the chemical composition of water as they might contain pesticides from agricultural land, heavy metals from industrial activities and nutrients from the soil itself. Excess nutrients in the water can cause eutrophication, which can lead to an increase in Biological Oxygen Demand (BOD) [2].
In recent times, Malaysia as a developing country has experienced significant environmental changes due to higher population, urbanization and faster economic growth. This has brought upon tremendous land use changes which has made the land in Malaysia more susceptible to soil erosion [3].
A slope is prone to soil erosion, but there are challenges to conserve the slope due to lacking of knowledge, technical support and cost constraint. Engineers introduce slope protection by designing gabion, retaining wall, riprap and other engineering methods [4,5]. It has been much research done previously on the topic of soil erosion control using a plot of land [6]. The effectiveness of soil erosion 2nd International Conference on Materials Technology and Energy IOP Conf. Series: Materials Science and Engineering 943 (2020) 012025 IOP Publishing doi: 10.1088/1757-899X/943/1/012025 2 control using mulch and grass has not been well identified. Mulch and grass cover represent the most cost effective and economic ways to control soil erosion at a slope among the common methods. The main objectives of this study were as follows: 1.
To examine the quality of the surface runoff produced by measuring the physical properties of the water namely the runoff volume, turbidity and total suspended solids (TSS). 2. To evaluate the effectiveness of two methods of soil erosion control, namely mulch and cultivated grass under different rainfall conditions. Furthermore, this research is able to contribute to water quality improvement as the effective soil erosion method at low cost with less turbidity, TSS and runoff volume at the soil erosion affected areas.

Materials and Methods
Different methods, designs, parameters and procedures were performed in previous studies [7,8]. In this experiment, a small-scale plot of land will be constructed and placed on a slope to induce erosion. It was then placed outside during a natural rainfall and the runoff was collected. The runoff was checked for its turbidity, TSS and runoff volume and was measured to evaluate which erosion control method is more effective in reducing sedimentation.
Plot was designed according to other similar experiments done by other researchers [9,10]. The plot designed into a width of 0.6m, length of 1m and a depth of 0.2m. The plot was made using thin waterproof plywood. The box was nailed together using nails and any gaps were closed using a hot glue gun. Three holes were drilled at the front of the box with a diameter of one and a half inches. PVC pipes were joined at each of the holes to direct the runoff out. The top of the PVC pipes was covered with a 0.1m long wooden cover. The collection buckets were placed below the PVC pipes.

Control plot
Bare soil was created as a control plot. This plot was filled to a depth of 6 inches. It was placed on an incline in the horizontal: vertical ratio of 3:1.

Mulch plot
The plot was filled with soil to a depth of 6 inches. Mulch was made using dried grass clippings and dried grass. It was laid onto the soil and spread evenly throughout the soil. The thickness of the mulch used was 1 -1.5 cm.

Grass cultivation plot
The plot was filled with soil to a depth of 6 inches. Patches of cow grass (Axonopus compressus) was planted along the soil. The plot was watered with 1 litre of water every day for a month to ensure that it grows properly. The grass coverage had more than 90% observable coverage on the soil before beginning to record the data.

Soil analysis
A soil analysis test was conducted to determine the type of soil. The test conducted is a Standard Operating Procedure (SOP), which was based on ASTM D422-63 standard Test Method for Particle-Size Analysis of Soils through sieving [11].

Rainfall data
The rainfall data was collected by the weather station located in the Curtin Malaysia campus. The rainfall intensity was categorized as low, moderate or high using the mean rainfall intensity over the specific time period. It was assumed that a low intensity rainfall event has a mean intensity of lower than 10 mm/hr, a moderate intensity rainfall event as having a mean intensity of between 10 mm/hr and 20 mm/hr and a high intensity rainfall is as having a mean intensity of more than 20 mm/hr. For the duration of rainfall, a short rainfall duration was assumed as occurring for less than one hour while a long duration The rainfall stopped briefly after 55 minutes before resuming again. It was a long duration and high intensity. 5 (01/10/2018) 55 13.17 The rainfall indicated a high intensity when it started before dropping in intensity. It later increased back up after 30 minutes before subsiding. It was a short duration and medium intensity.

Soil analysis
Soil used for this experiment was put through a sieve analysis test and the data was recorded in Table  2. The soil comprised of 4% of silt, 52% of sand and 44% of gravel.

Runoff volume
The control plot consistently produced more runoff when compared to the other two plots. This is expected as the control plot has no erosion control method and is solely to provide comparison for the other two plots. Comparison of runoff volume between mulch and grass is shown in Figure 1.
Both plots produced the least amount of runoff volume during the first test period which was the period with the shortest rainfall duration. The rainfall intensity during this testing period started out high, but later subsided. The mulch plot only produced 80 mL of surface runoff while the grass produced 184 mL. The mulch was probably able to produce such a low runoff due to the decreased amount of rainfall as it was the shortest duration. This was mainly due to the function of the mulch whereby it prevented the surface water from accumulating and forming micro rills. The grass plot was able to produce a low amount as well due to the short rainfall duration, the water had been absorbed into the soil instead of accumulating on the surface. It produced more runoff than the mulch as it could not obstruct the flow of the surface runoff [12]. In the second test period, the rainfall period was longer but was a low intensity rain throughout the rainfall period. Nevertheless, both plots produced more runoff with the mulch producing 196mL and the grass producing 540mL. This is a stark difference when compared to test period 1 where the difference between the two was only 104mL. In this case, it is more than double the amount. The longer duration could have caused the water to accumulate on the grass plot thereby producing more surface runoff. The low intensity rainfall did not seem to have much effect on the mulch plot as there was minimal difference between the test period 1 and test period 2. The low intensity rain caused the rain drops to be absorbed by the mulch material.
In the third test period, the rainfall was even longer and started out with a high intensity. But this high intensity only lasted for 10-15 minutes before reducing to a low intensity rain. It was a moderate intensity rainfall event. However, it must be noted that test period 3 took place only a few hours after test period 2. Hence, this is a chance to investigate the erosion control performance of the two methods after successive rainfall events. Both the test plots produced significantly higher amounts of runoff with the mulch producing 687 and the grass plot double that with 1287 mL. This could be attributed to the soil sealing which occurs in the grass plot reducing the infiltration rate of the soil [6]. Water accumulated on the soil surface resulting in more runoff produced. This soil sealing had a lesser effect on the mulch as the raindrops were absorbed by the mulch material as well as the soil.
In the fourth test period, the rainfall was the longest among the testing periods. The mulch produced more or less the same amount of runoff when compared to period 3. This could indicate that although the rainfall was longer and with a high intensity, the mulch plot was unaffected by extended periods of rainfall. The grass plot on the other hand, showed a significant reduction by producing 645 mL of runoff which was lower than the volume produced by mulch plot. The roots from the grass had grown more and increased infiltration rates in the soil thereby decreasing the occurrence of soil sealing [13].
In the last testing period, the rainfall was a short rainfall event with a medium intensity. Both plots produced similar results with the runoff volume produced being 155 mL and 165 mL for the mulch and grass plots respectively. The grass plot had once again showed significant improvement in the reduction in runoff produced.  The percentage reduction obtained shows that the mulch had more or less the same performance throughout the testing period as its percentage reduction ranged between 83% -95.04%. The grass plot showed more variance as its percentage reduction ranged from 53.17% -94.72%. When compared to results obtained from previous work done [10], the engineered fiber matrix (EFM) with seed showed the highest percentage reduction of runoff volume at 68.0 %. These results from the previous work are based on average runoff volume. Nevertheless, the difference between the results obtained from this experiment and the results from the previous research are too large. Hence, both of the erosion control methods used in this experiment is more effective in controlling runoff.
The mulch consistently produced a lower runoff volume when compared with the grass plot except in the last two testing periods where the runoff volume produced was very similar. The grass required sufficient time to grow which caused the roots not deep enough into the soil, therefore, the porosity of the soil was low and the water accumulated on the surface of the soil. The grass plot was a better erosion control method in terms of runoff volume over time. The mulch on the other hand, did not show any significant improvements in its performance in reducing runoff over time.

Turbidity
The control plot showed a higher turbidity (ranged from 8,550 to 23,760 NTU) when compared to the mulch plot and grass plot. Comparison of turbidity for mulch plot and grass plot is shown in Figure 2. In period 1, the mulch plot had a turbidity of 368 NTU and the grass plot a turbidity of 464 NTU. Both control measures produced similar results with the mulch performing slightly better. This could be due to period 1, having a very short rainfall duration. In a short rainfall duration, the mulch could absorb the raindrops before it hit the soil surface and dislodged the soil particles thus, resulting in a lower turbidity [6].
In period 2, the mulch plot had turbidity of only 98 NTU and the grass plot a turbidity of 668 NTU. This could be due to the surface cover provided by the mulch. As the rainfall had a low intensity, there was not enough kinetic energy in the rain drop particles to dislodge the soil. The grass cover had not grown fully to cover the soil causing the raindrops to directly impact the soil and dislodge the particles.
During period 3 which occurred a few hours after test period 2, the mulch produced 639 NTU and the grass plot 503 NTU. This grass plot showed very similar readings when compared to test period 2 with slightly decreased. However, a drastic rise in turbidity for the mulch plot. After successive rainfall events, the mulch was still full of water absorbed from the previous rainfall event. So when it rained  again a few hours after, there was more water produced as runoff instead of being absorbed by mulch. If there was time in between the rainfall events, the water absorbed by the mulch would have evaporated and it would have been able to absorb more water by the time the next rainfall event occurred.
In the fourth test period, the rainfall had the longest duration a high intensity. The mulch plot showed the highest turbidity at 858 NTU while the grass plot was 274 NTU. This could be due to the grass growing longer and thicker thereby providing more surface cover for the soil dissipating the high kinetic energy in the raindrops. The mulch plot on the other hand, was drastically affected by the high intensity and longer duration rainfall. By having these conditions, the raindrops had more kinetic energy to dislodge the soil particles, and by continuing at this high intensity for an extended period of time, the mulch cover was unable to fully dissipate the kinetic energy of the raindrops [14].
In the last test period, the mulch cover had a better performance by producing 190 NTU and the grass cover a turbidity of 271 NTU. The last test period had a short rainfall duration with a medium intensity. The grass cover produced a similar amount of turbidity as test period 4. The mulch on the other hand produced a lower amount, indicating that the mulch plot performed better when the rainfall duration is short.
The mulch plot had a reduction in turbidity with the range of 97.31% -99.1%. The grass plot once again had a bigger variance as its range varied from 92.19% -99.59%. These results are comparable to the previous study [10], whereby engineered fiber matrix (EFM) with seed indicated a percentage reduction of 98.7%. The research results are the average turbidity, hence it cannot be concluded that either of the methods used in this experiment are better as the percentage reduction from the previous research are still in the range obtained in this experiment.
The mulch showed the highest reduction most of the time when compared to the grass cultivation plot. Although the results are almost similar, the mulch showed a slightly higher reduction. This could be attributed to the mulch covering the surface of the top soil whereby reducing the kinetic energy of the raindrop particles which impact the surface thereby reducing the amount of soil being dislodged. They might even prevent the raindrops from even reaching the surface altogether. The surface cover on the grass cultivation plot was less due to the gaps. The gaps between grass cover caused the raindrops to fully reach the surface and dislodge the soil particles. However, the grass plot had a better performance compared to the mulch plot when it was a high intensity and prolonged rainfall event. The mulch lost the ability to dissipate the kinetic energy of the raindrops after a sustained rainfall.
The turbidity produced from both control measures was not up to the water quality standards in Malaysia as all the turbidity values are above 50 NTU. The water produced did not meet the Class III Standards as listed in the Malaysian national guidelines [15]. Hence, using these methods alone might not be enough to achieve the desired erosion control performance at construction sites.

Total suspended solids (TSS)
The control plot showed a higher TSS (ranged from 6.5 to 82 g/l). Comparison of TSS for mulch plot and grass plot is shown in Figure 3.
During the first test period. The grass plot produced 0.34 g/l as compared to the mulch which produced 0.7 g/l. During period two, the mulch plot had a better performance as it recorded 0.26 g/l as compared to the grass plot which recorded 0.42 g/l. For the following test periods, the mulch recorded 0.58 g/l, 0.64 g/l and 0.22 g/l for test periods 3, 4 and 5 respectively. The grass plot recorded 0.3 g/l, 0.16 g/l and 0.18 g/l for test periods 3, 4 and 5 respectively.
The grass plot indicated a better performance in 4 out of the 5 test periods. The reduced performance of the mulch could be due to the mulch biodegrading over time as it is an organic material. This could have contributed to tiny organic matter to be eroded together with the soil causing the TSS value to be higher. However, the rate of mulch decomposition is unclear. Nevertheless, when the mulch decomposes it could create a more conducive environment for the microorganisms in the soil underneath by stabilizing the temperature and moisture [16]. This advantage is nullified, however, the increase in TSS in the surface runoff causing increased pollution to water bodies.  Figure 3. TSS of mulch and grass. The higher amount of TSS detected in the grass plot during period 2 could be attributed to the soil not settling fully. Also, the roots of the grass had not grown fully at that time hence after the rainfall event, the soil on the surface was easily washed away. In addition, the rainfall conditions did not affect the TSS values obtained [8]. During period 4 when there was a high intensity and long duration rainfall event, the TSS value obtained by the grass plot was the lowest for all the test periods. The mulch plot produced a high amount of TSS during test period 4 but this amount is similar with the TSS amount produced during test period 3. Hence, the rainfall conditions did not affect the amount of TSS produced.
The percentage reduction of the mulch plot ranged from 96% -99.2% while the grass plot ranged from 93.54% -99.8%. During test period 4, when the rainfall event was the longest and had a high intensity. The grass plot showed the lowest TSS among all periods tested during period 4. When compared to previous work [10], the best performing control method which was the engineered fiber matrix (EFM) with seed achieved a 99.8% reduction. The engineered fiber matrix (EFM) with seed performs better than the two erosion control methods employed here in terms of TSS reduction.
The grass plot and mulch plot was able to occasionally achieve TSS values of below 300 mg/l which is the Class IV standard listed in the Malaysian national guidelines [18]. However, the grass cultivation plot is considered a more viable option as the biodegradation of the mulch over time was not fully quantified.

Cover factor
The cover factor is calculated by using the ratio of sediment yield from a surface with a specific control measure to a surface with no control measures. The cover factor is one of the most commonly used parameters to test the effectiveness of soil erosion control measures. The cover factor is scaled from 0 to 1 where zero means a 100% reduction of erosion and one meaning a 0% reduction in erosion or in other words it is the same as the bare soil. The average cover factor for mulch plot and grass plot is shown in Table 3.  8 parameters in use for the USLE equation, the cover factor is the most easily influenced. It is the factor most considered by policy makers and farmers [17].
The grass cultivation showed the better cover factor as compared to the mulch. The grass was better to be used as a cover than the mulch. However, these results are not entirely accurate as the TSS from different test periods with varying rainfall conditions were averaged out. Mulch with a 100% cover which is used as an erosion control at construction sites have a C factor value of 0.02 based on the Malaysia Department of Irrigation and Drainage (DID) [18]. The grass with more than 90% cover in this experiment indicated the C factor value of 0.02. Hence, the cover factor is this experiment is similar to the guideline listed in DID.

Conclusion
The mulch plot was able to consistently produce a lower runoff volume when compared to the grass plot. The turbidity produced by both sets of erosion control measures are very similar although the mulch produced a slightly lower value. The mulch acted as a better surface cover, which is effective in reducing the kinetic energy of the raindrops. However, the mulch was biodegrading over time that causing small organic particles to be eroded as well. In terms of runoff volume and turbidity, the grass plot was able to perform better in high intensity and longer duration rainfall events when compared to the mulch plot. During low and moderate intensity rainfall events, the mulch plot produced slightly better results when compared with the grass plot. It proved that the rainfall conditions had no effect on the TSS produced. Although there were certain instances when the results were very similar, after taking into account the increase in performance of the grass over time as well as its ability to perform better in harsher conditions, it is concluded that the grass cultivation is the better option to be used as an erosion control method. However, mulch can still be used as a temporary erosion control method on construction sites while it would be better to apply grass as a more permanent erosion control method.


extfieldsofstudy: Medicine Chemistry

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

text:
Effect of microbial feed additives on growth performance, microbial protein synthesis, and rumen microbial population in growing lambs

Abstract Arabi lambs (n =28; body weight = 24 ± 3.7 kg; average age = 120 ± 8 days) were used to investigate the effect of microbial additives on growth performance, microbial protein synthesis and rumen microbial population of fattening lamb based on completely randomized design. Four treatments were studied: (1) control (without additive; CON); (2) Lactobacillus fermentum and L. plantarum (FP); (3) Saccharomyces cerevisiae (SC) plus FP (SCFP); and (4) Megasphaera elsdenii plus SCFP (MSCFP). Lambs were inoculated before morning feeding (daily oral dosed) with a 50 mL microbial suspension as follows: FP, 50 mL bacterial suspension containing 4.5 × 108 colony-forming unit per day (cfu/d) of L. plantarum and L. fermentum (in ratio 50:50); SCFP, 50 mL microbial suspension containing 4.5 × 108 cfu/d FP and 1.4 × 1010 cfu/d SC; MSCFP, 50 mL microbial suspension containing 4.5 × 108 cfu/d Me, 4.5 × 108 cfu/d FP and 1.4 × 1010 cfu/d SC. Feed intake and body weight of lambs were not affected by microbial additives. Average daily gain and feed efficiency were increased on day 0 to 21. The highest concentration of uric acid, total excreted purine derivatives (PD), microbial N, microbial CP, and metabolizable protein were in MSCFP lambs. The ruminal population of Ruminococcus albus and Ruminococcus flavefaciens was higher in MSCFP and SCFP than CON and FP lambs. The highest and the lowest abundance of M. elsdenii and methanogen respectively was observed in lambs fed on microbial additives. The tendency to improve growth performance vs. CON may be due to improvements in microbial protein synthesis and microbial populations, especially fiber-degrading bacteria. The decrease in the population of methanogens as a result of the use of microbial additives is another positive result.

INTRODUCTION
Antibiotics are natural or synthetic compounds that generally kill or inhibit the growth of bacteria. Previous studies show that using low doses of antibiotics improved feed efficiency (FE) and growth performance (Chattopadhyay, 2014).
But, the use of antibiotics for growth promotor, treatment, or control of the disease, creates a pool of antibiotic-resistant bacteria that infect animals and products, that it can transmit to humans and animals through the consumption of these animal products (Van der Fels-Klerx et al., 2011). So, global concern about the use of antibiotics has led many countries to ban the use of antibiotics in animal feed (Sarker et al., 2010). Hence, given the prohibition of antibiotics, the use of alternative additives such as probiotics can be useful.
Probiotics or microbial additives (bacterial and yeast additives) are viable organisms that have positive effects on animal health and performance (Arowolo and He, 2018). In a review study of Elghandour et al. (2015) reported that the use of microbial additives leads to changes in the microbial environment, increased weight gains and improved FE. Studies showed that yeast additives such as Saccharomyces cerevisiae lead to an increase in the concentration of ruminal bacteria, especially Fibrobacter spp., due to the equilibrium in rumen pH (Beauchemin et al., 2006). Bacterial additives such as lactate producing bacteria (LAB) (Lactobacillus, Bifidobacterium, Enterococcus, Streptococcus, and Bacillus) and lactate utilizing bacteria (LUB) (Megasphaera elsdenii, Selenomonas ruminantium, and Propionibacterium) are used as microbial additives. The most important hypothesis about LAB is that they are stimulating the growth of LUB leading to stability ruminal pH (Seo et al., 2010). The LUB can influence rumen fermentation in a high grain diet (Mackie and Gilchrist, 1979), change lactate to VFA (e.g., butyrate), increase propionate production than lactic acid, increase feed efficiency, and increase ruminal pH (Seo et al., 2010). Yeast-containing additives have been investigated in lambs (Soren et al., 2013), but there is limited information about the use of combined bacterial and yeast additive on microbial population and microbial protein synthesis in lambs. Since the use of microbial additives based on LAB in dairy cows has become commonplace, our aim was to use treatments based on LAB in growing lambs. So, in the present study, we investigated three treatments based on LAB compared to controls (without additives). It was hypothesized that the mixture of L. fermentum GP10, L. plantarum (FP) (in ratio 50:50) alone or combined M. elsdenii GU1 (Me) and S. cerevisiae (SC) can improve performance, microbial protein synthesis, and rumen microbial population in growing lambs.

Animals, Diet, and Treatment
Twenty-eight autumn born Arabi lambs (body weight = 24 ± 3.7 kg; average age = 120 ± 8 d) were randomly divided into four groups (n = 7), which were vaccinated against external (Azantole) and internal (Triclabendazole and Levamisole) parasites and were penned individually (1.5 m × 1.3 m). The experimental period was 77 d (14 d adaptation and 63 d trial period) and during this period the complete mixed ration (contained g/kg of dry matter (DM)): alfalfa hay 201; wheat straw 99; barley grain 300; corn grain 210; soybean meal 123.5; wheat bran 55; calcium carbonate 4; NaCl 2.5; vitamin and mineral supplements 5) was provided for each lamb twice daily at 8:00 a.m. and 16:00 p.m. (allowed 5% of orts) (NRC, 2007). The chemical composition of the diet is presented in Table 1. The ration was adjusted to reach 250 g daily weight gain. During the experiment, lambs had free access to fresh water and salt licks.

Sample Collection and Chemical Analysis
At the end of adaptation period, the body weights of lambs were recorded before morning feeding as initial weight, and also the lambs were weighted using digital scales before morning feeding on d 21, d 42, and d 63. To determine intake, the amount of feed offered and orts for each lamb was recorded every day before morning feeding. Feed and orts samples were taken for chemical analysis and stored at −20 °C. Finally, average daily gain (ADG) and FE (gain:feed) were calculated for each lamb. On d 50 of experiments, five lambs from each treatment with the same body weight were transferred to the metabolic cages equipped with feces and urine collector for 13 d (7 d adaptation to the metabolic cages and 6 d sampling). During the collection period, samples of feed offered and orts was collected (10%) and stored at −20 °C for subsequent analysis. The total urine volume was collected and weighed during each day of the sampling period in plastic buckets containing 100 mL sulfuric acid (10% v/v) to reduce the pH to less than 3. After that 10% of urine samples were diluted five times with distilled water, to prevent the precipitation of purine derivatives (PD) and stored at −20 °C until subsequent analysis. On d 63 of experiment, ruminal fluid (RF) was obtained with a stomach tube 3 h after morning feeding and frozen at −80 °C until deoxyribonucleic acids (DNA) was extracted.

Total DNA Extraction and Real-time Quantitative Polymerase Chain Reaction (qPCR)
The RF was thawed at room temperature and microbial DNA was extracted using a genomic DNA extraction kit (AccuPrep, Bioneer Corporation, Daejeon, South Korea) equipped with spin columns according to the manufacturer's instructions. To determine the concentration and purity of DNA extracted, Nanodrop Spectrophotometer (NanoDrop ND-1000, USA) was used. Species-specific PCR primers (16S rDNA) used in this study are list in Table 2. The qPCR was performed in a CFX96 optical reaction module (Bio-Rad Laboratories Inc.) and analyzed using software Bio-Rad CFX Manager (version 3.1). Each amplification reaction was run in duplicate with a final volume of 20 μL. Components of the PCR reaction consisted of 1 µL of template DNA, 2 µL of both primers (1 pmol Forward and 1 pmol Reverse), 10 µL of SYBR Green PCR Master Mix Kit and 7 µL of deionized water. SYBR Green qPCR Master Mix contained Taq DNA polymerase, reaction buffer (KCl and (NH 4 ) 2 SO 4 ), dNTPs, MgCl 2 , and SYBR Green. The amplification program was one cycle at 95 °C for 5 min (initial denaturation), 35 cycles of 95 °C for 30 s (denaturation), 61°C for 30 s (annealing), and 72 °C for 45 s (extension) and a final elongation at 72 °C for 10 min. The specificity of amplified products was confirmed by melting temperature and dissociation curve after amplification.
Changes in targeted populations (fold changes) of Fibrobacter succinogenes, Ruminococcus albus, R. flavefaciens, M. elsdenii, Lactobacillus spp., methanogens, and protozoa were calculated using a relative quantification calculation and the 2 −ΔΔCt method (Livak and Schmittgen, 2001), with general bacteria (Denman and Mc Sweeney, 2006) cycle threshold (Ct) values used as the reference and average ΔCt of the CON group as the calibrator value.

Statistical Analysis
The data obtained from assessing feed intake, growth performance, urinary purine derivatives, microbial protein synthesis, and microbial population were analyzed as a randomized complete design using General Linear Models (GLM) procedure in SAS software (SAS Institute, 2008) according to the model: where Y ij is observation, μ is the general mean, T i is the effect of treatment, and e ij is the standard error of term. Means were compared by the Duncan multiple comparison tests at P < 0.05.

Feed Intake and Growth Performance
Feed intake (DM, OM, CP, NDF, ADF g/kg 0.75 body weight (BW) and ME MJ/kg 0.75 BW; P = 0.77, P = 0.78, P = 0.80, P = 0.77, P = 0.65, and P = 0.77, respectively) and BW of lambs on d 21, d 42, and d 63 were not affected (P = 0.98, P = 0.95, P = 0.95, respectively) by experimental treatments. Lambs ADG and FE were increased (P = 0.03, P = 0.01, respectively) by dietary microbial additives on d 0 to d 21 compare to CON, but there was no difference between microbial additives and CON on other days of the experiment. However, the total ADG increased (P = 0.04) in MSCFP vs. CON lambs (Table 3).

Urine Purine Derivatives and Microbial Protein Synthesis
Allantoin and X + H concentrations were not affected (P = 0.13, P = 0.06, respectively) by microbial additives. However, the concentration of uric acid was increased (P = 0.03) in MSCFP lambs compare to CON (2.21 vs. 1.97 mmol/d, respectively). Moreover, the concentration of total excreted PD was increased (P = 0.03) in MSCFP vs. FP and CON lambs. The highest levels of microbial N, microbial CP and metabolizable protein was observed in MSCFP lambs (P = 0.01, P = 0.01, P = 0.02, respectively), but there was no difference between MSCFP and SCFP. The amount of microbial N synthesized gN/kg DOMI (digestible organic matter intake) was not affected (P = 0.73) by microbial additives (Table 4).

Rumen Microbial Population
Ruminal microflora of F. succinogenes, Lactobacillus spp., and protozoa were not affected (P = 0.87, P = 0.53, P = 0.78, respectively) by microbial additives. The ruminal population of R. albus and R. flavefaciens were higher (P = 0.01, P = 0.01, respectively) in MSCFP and SCFP lambs than CON and FP. The lowest abundance of M. elsdenii was observed in CON lambs and was differ (P = 0.04) from MSCFP lambs. Moreover, methanogen population decreased (P = 0.01) using microbial additives than CON lambs (Figure 1).

Feed Intake and Growth Performance
Feed intake was not affected by the experimental treatments and consistent with our results, the use of microbial additives had no effect on feed intake in lambs (LAB and SC) (Alhidary    (Azzaz et al., 2015), and dairy cattle (P. freudenreichii and L. acidophilus) (West and Bernard, 2011). On the other hand, feed intake was improved in young ruminants as a result of the use of live yeast (Lesmeister et al., 2004). Also, dry matter intake (DMI) and organic matter intake (OMI) were improved in the study of Bitencourt et al. (2011) by the yeast dietary supplementation. This may be due to the increased digestibility of the NDF and the DM in their experiment, and also, may be correlated with rumen development (Lesmeister et al., 2004). However, without the effect of experimental treatments on feed intake, ADG was improved on d 0 to Indicate a differ significantly (P < 0.05). Bar indicates standard error of the mean. CON, without microbial additive; FP, Lactobacillus fermentum and Lactobacillus plantarum; SCFP, Saccharomyces cerevisiae (SC) plus FP; MSCFP, Megasphaera elsdenii plus SC plus FP. d 21 and d 0 to d 63, which consistent with the previous results (Ayala-Monter et al., 2019). They reported that improvement in ADG without altering feed intake was due to improved FE and nutrient digestibility.

Urine Purine Derivatives and Microbial Protein Synthesis
Microbial CP plays an important role in supplying ruminant protein and provides most of the amino acids needed for growth, maintenance and production of the host animal (Vaithiyanathan et al., 2007). The effect of microbial additives on PD and microbial CP synthesis in ruminants has been investigated in limit studies. Yoon and Stern (1995) in a review study also reported microbial CP synthesis increased using probiotics. Bajagai et al. (2016) reported that supplementation with yeast increased microbial CP synthesis. However, in an in vitro experiment, Direkvandi et al. (2019) reported that the use of Me increased the synthesis of microbial protein, which could be due to the increased synthesis of branched-chain amino acids by Me. In present study, the amount of microbial CP synthesis similarly was increased in SC and Me containing treatments (MSCFP and SCFP). This is probably due to the increased use of ruminal ammonia into the microbial CP (Erasmus et al., 1992). Also, the increase in microbial N and CP in the treatments containing microbial additive compared to the CON may be due to the increase in DOMI in this treatment. Pérez et al. (1998) reported a relationship between purine derivatives and DOMI. Other studies have also shown that the amount of urinary PD and microbial CP synthesis are dependent on the amount of DMI and CPI (Puchala and Kulasek, 1992). Balcells et al. (1993) who found a positive relationship between DMI and OMI and the amount of urinary PD excreted in sheep. The amount of feed intake is one of the factors affecting the rate of microbial protein synthesis and by reducing the feed intake, the amount of microbial protein synthesis is reduced. This can be due to the reduction of N and soluble carbohydrates for microbial protein synthesis.

Rumen Microbial Population
The ruminal population of Lactobacillus spp. was not affected by the experimental treatments. Qadis et al. (2014) reported that supplementation with probiotics had no effect on L. plantarum populations and Enterococcus spp. They reported the lack of an increase in LAB was a sensitivity of these bacteria to pH greater than 6. Sari et al. (2019) observed that the total ruminal population of LAB was not affected by L. plantarum TSD-10, L. plantarum MX-16, L. brevis SPCE-39 and a mix of these bacteria. However, they reported although the total ruminal population of LAB was not affected, but populations of some Lactobacillus strains are likely to be significantly different. Also reported that the use of LUB alone or combined with LAB (Propinobacterium and Propinobacterium + E. faecium) had no effect on the ruminal population of LUB and Lactobacillus spp. (Ghorbani et al., 2002). In fact, studies have shown that the use of yeast stimulates the growth of LUB (Newbold et al., 1998), which is consistent with our results.
However, population of ruminal fiber degrading bacteria (Ruminococcus and Fibrobacter) showed no significant difference between FP and CON lambs. Contrary to our results in the in vitro experiment, the use of 0.1% E. faecium (7.0 × 10 8 cfu/mL) increased the ruminal population of R. flavefaciens and F. succinogenes compared to the control (Mamuad et al., 2019). The increase in the population of fiber-degrading bacteria in treatments SCFP and MSCFP is probably due to the presence of Me and SC. Me increase the population of fiber-degrading bacteria by increasing the synthesis of branched-chain amino acids (a precursor to the synthesis of branched-chain fatty acids in the cell wall of fiber-degrading bacteria) and yeast by reducing the redox potential. Reducing the potential of redox stimulates the attachment of fiber-degrading bacteria to the fiber particles in the rumen. Providing nutrients by SC stimulated the growth of R. albus, R. flavefaciens, and F. succinogenes (Chaucheyras-Durand et al., 2008). Indeed, the positive effect of yeast-containing additives is due to the stabilization of the rumen microbial environment. In an experiment of Malekkhahi et al. (2016) showed that the use of SC (20 × 10 9 cfu/head per day) increased the ruminal population of F. succinogenes compared to the controls during the adaptation period in dairy cattle.
The results of our study were consistent with other researchers that reported microbial additives had no effect on the ruminal protozoa population (Ghorbani et al., 2002;Galip, 2006;Izuddin et al., 2019). However, Brossard et al. (2006) reported an improvement in the rumen population of protozoa using live yeast in sheep. The effect of microbial additives on the rumen protozoa population varies according to the type of probiotic and the protozoa strain. The decrease in methanogen population may be due to increased propionate production due to the use of microbial additives. Preventing the formation of hydrogen in the rumen or consuming it is a way to prevent it from entering the methane production cycle. In fact, propionate and butyrate production is a pathway for hydrogen utilization and hydrogen is a major precursor to methane production (Jeyanathan et al., 2014). Astuti et al (2018) also reported that the use of the U32 strain of L. plantarum reduced methane production and they reported that this decrease was probably due to the positive effect of LAB on the growth of LUB. The decrease in methanogen population may be due to the increase in F. succinogenes population as a result of microbial additives. Because F. succinogenes is a nonhydrogen producing bacteria, and hydrogen is a substrate for methanogens (Mamuad et al., 2019), therefore, less substrate will be accessible for methanogens.

CONCLUSIONS
The main finding in this study was that the simultaneous use of all three microorganisms in MSCFP treatment compared to control and other treatments had a greater effect to improved nutrient intake, final BW, ADG, and microbial CP production. The tendency to improve growth performance in lambs may be due to improvements in microbial protein synthesis and microbial populations, especially fiber-degrading bacteria (R. flavefaciens and R. albus). The decrease in the population of methanogens (all treatments compared to control) and increased the population M. elsdenii (MSCFP) as a result of the use of microbial additives is another positive result.

ETHICS APPROVAL
All animal management and sampling procedures conducted according to The Care and Use of Agricultural Animals in Research and Teaching guidelines (FASS, 2010). All procedures and guidelines involving animals were approved by the Animal Experiment Committee at Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran.


extfieldsofstudy: Medicine Biology

text:
Identification and Characterization of Verticillium longisporum Lineage A1/D1 from Brassica Crops in Manitoba, Canada

Verticillium stripe in canola (Brassica napus L.) caused by Verticillium longisporum was first reported in Manitoba in 2014. In this study, Brassica crops including canola, mustard (Brassica juncea) and radish (Raphanus sativus) with visible symptoms of Verticillium stripe were collected from Portage La Prairie, Manitoba, and the pathogens were isolated. Isolates from canola and radish were identified to V. longisporum, which produced longer conidia (7.92–12.00 µm) than Verticillium dahliae (4.32–7.04 µm). An isolate derived from mustard was characterized as V. dahliae. Molecular diagnostics with 18S rDNA, 5.8S rDNA and mating-type marker primers were used to confirm the identification of Verticillium isolates. PCR-RFLP of the mitochondrial small subunit rDNA and the cytochrome b gene were also employed to distinguish V. longisporum isolates from V. dahliae. The multi-gene characterization approach allowed for lineage determination, and V. longisporum isolates from canola and radish were in the A1/D1 group. Isolates of Verticillium longisporum from canola inoculated onto the canola cultivar ‘Westar’ caused symptoms of stem striping, stunting and short plants. Re-isolated fungal strains from infected stems were again inoculated onto canola plants, in order to confirm that V. longisporum was the causal agent of Verticillium stripe disease in the pathogenicity test.

Introduction
Canola (Brassica napus L. AACC, 2n = 38) is a relatively young species derived from a spontaneous interspecific hybridization between Brassica rapa L. (AA, 2n = 20) and Brassica oleracea L. (CC, 2n = 18) [1]. Canola is one of the most important oilseed crops worldwide, especially in Canada, where approximately 21.3 million tonnes were produced in 2017 (Canola Council of Canada 2018). Mustard (Brassica juncea L. AABB, 2n = 36) is an amphidiploid derived from the combination of two diploid genomes (B. rapa and B. nigra L. BB, 2n = 16). Radish (Raphanus sativus L. 2n = 2x = 18) is a member of the family Brassicaceae, and is closely related to B. rapa [2]. Verticillium stripe in canola, which is caused by Verticillium longisporum, was first observed and confirmed in Manitoba in 2014 (Canola Council of Canada). A survey conducted by the Canadian Food Inspection Agency and the Canola Council of Canada confirmed the presence of the pathogen in canola stubble from British Columbia, Alberta, Saskatchewan, Ontario and Quebec (http://www.inspection.gc.ca/plants/plant-pests-invasive-species/ diseases/verticillium-stripe/eng/1420746212959/1420746213803).
A Verticillium species supposedly representing V. longisporum (but not named so) was first described on Brussel sprouts (isolate 111) in the UK by Isaac in 1957 [3]. Verticillium longisporum

Pathogen Isolation
Naturally infected sampled stems exhibited black striping on the stem with microsclerotia. Twenty-nine Verticillium isolates from canola, one isolate from radish and one isolate from mustard were obtained (Table S1).

Morphological Identification
Verticillium isolate VL-H1 was obtained from canola tissue and grown on potato dextrose agar (PDA) for 14 days, which produced white colored mycelia on the top of cultures (Figure 1a). The V. dahliae isolate displayed greyish colonies with radiating ridges (Figure 1b). The mean length of Verticillium isolate VL-H1 conidia was significantly longer than that of the V. dahliae isolate (Vd1396-9) (Figure 1c,d,i). The Verticillium isolate from canola (VL-H1) produced longer conidia, ranging from 7.92 to 12.00 µm (mean 10.08 µm), while the mean length of V. dahliae isolate conidia was 5.27 µm and ranged from 4.32 to 7.04 µm (Figure 1i). Under the microscope, the Verticillium isolate VL-H1 from canola produced irregularly-shaped microsclerotia (Figure 1e), while colonies of the V. dahliae isolate (Vd1396-9) formed regularly-shaped microsclerotia (Figure 1f). Isolated VL-H1 produced more branched hyphae, while the V. dahliae isolate produced less profusely branched hyphae (Figure 1g,h). Taken together, the colony growth, conidia length, microsclerotia and hyphal traits suggest that the Verticillium isolate VL-H1 was V. longisporum. The other 28 isolates that were derived from canola and the one isolate identified from radish all exhibited similar morphological characteristics, suggesting that they too were V. longisporum. However, one isolate retrieved from mustard displayed morphological traits similar to V. dahliae. These results were further validated through molecular identification. the one isolate identified from radish all exhibited similar morphological characteristics, suggesting that they too were V. longisporum. However, one isolate retrieved from mustard displayed morphological traits similar to V. dahliae. These results were further validated through molecular identification.

PCR Characterisation
Polymerase chain reaction (PCR) amplification of the 18S rDNA intron region with the primers VlspF1/VlspR4 produced a 275 bp band in all the tested V. longisporum and V. dahliae isolates ( Figure  2a). Verticillium longisporum isolates derived from canola and radish produced a 1,598 bp band, while the V. dahliae isolates from mustard produced a 757 bp amplicon when amplified with the primers VeruniF2/VeruniR3, designed for the 18S rDNA region. However, the 18S rDNA region cannot be used to distinguish the V. longisporum isolate A1/D3 group from V. dahliae isolates, since both produced the same amplicon (757 bp) (Figure 2b). Nucleotide sequence analysis of 18S rDNA indicated that isolates derived from canola and radish had 99% similarity with V. longisporum, while the sequence identity of an isolate identified from mustard was similar to V. dahliae (data not shown). All isolates were categorized as mating type 1-1, since only the VdMAT1-1-1F01/VdMAT1-1-1-R01 primer designed for mating type1-1 was amplified (Figure 2c).
Verticillium isolates derived from canola and radish produced 1,020 bp ITS and 310 EF -1α gene amplicons, similar to the V. longsiporum control isolates from the A1/D1 group (Figure 2d). The Verticillium isolate from mustard produced a 490 bp GPD gene, similar to the V. dahliae isolate from potato. With this multiplex PCR assay, we were able to differentiate the V. longisporum isolate from the A1/D3 group, which produced both GPD and EF -1α genes with 490 bp and 310 bp bands, from the V. dahliae isolate, which only produced the 490 bp GPD gene (Figure 2d). The V. longisporum isolates from the A1/D2 group yielded only a 310 bp amplicon (EF -1α gene) ( Figure 2d). All other Verticillium isolates from canola were characterized as the V. longisporum A1/D1 group.
The Verticillium isolates from canola and radish, as well as the V. longisporum isolates from the A1/D1 or A1/D3 groups, produced a 258 bp mtSSU-rDNA band, and the V. dahliae isolate from potato and V. longisporum isolate from the A1/D2 group produced 317 bp bands (Figure 2e). However, the

PCR Characterisation
Polymerase chain reaction (PCR) amplification of the 18S rDNA intron region with the primers VlspF1/VlspR4 produced a 275 bp band in all the tested V. longisporum and V. dahliae isolates (Figure 2a). Verticillium longisporum isolates derived from canola and radish produced a 1598 bp band, while the V. dahliae isolates from mustard produced a 757 bp amplicon when amplified with the primers VeruniF2/VeruniR3, designed for the 18S rDNA region. However, the 18S rDNA region cannot be used to distinguish the V. longisporum isolate A1/D3 group from V. dahliae isolates, since both produced the same amplicon (757 bp) (Figure 2b). Nucleotide sequence analysis of 18S rDNA indicated that isolates derived from canola and radish had 99% similarity with V. longisporum, while the sequence identity of an isolate identified from mustard was similar to V. dahliae (data not shown). All isolates were categorized as mating type 1-1, since only the VdMAT1-1-1F01/VdMAT1-1-1-R01 primer designed for mating type1-1 was amplified (Figure 2c).
Verticillium isolates derived from canola and radish produced 1020 bp ITS and 310 EF -1α gene amplicons, similar to the V. longsiporum control isolates from the A1/D1 group (Figure 2d). The Verticillium isolate from mustard produced a 490 bp GPD gene, similar to the V. dahliae isolate from potato. With this multiplex PCR assay, we were able to differentiate the V. longisporum isolate from the A1/D3 group, which produced both GPD and EF -1α genes with 490 bp and 310 bp bands, from the V. dahliae isolate, which only produced the 490 bp GPD gene (Figure 2d). The V. longisporum isolates from the A1/D2 group yielded only a 310 bp amplicon (EF -1α gene) ( Figure 2d). All other Verticillium isolates from canola were characterized as the V. longisporum A1/D1 group.
V. dahliae isolate from mustard produced a 413 bp band, which was different from the V. dahliae potato isolate ( Figure 2e). Furthermore, for the cytochrome b gene, all V. longisporum isolates produced a 226 bp band, whereas V. dahliae isolates from mustard and potato both produced a 320 bp band ( Figure  2f).

Disease Assessment
The Westar plants inoculated with V. longisporum showed disease symptoms in the form of yellowing and chlorosis at 7 and 14 days post-inoculation (dpi) ( Table 1). The mean scores of disease severity were significantly higher in the plants infected with the V. longisporum isolates identified in this study than in those inoculated with water after 14 and 21 dpi (Table 1). After 35 dpi, the plants inoculated with V. longisporum produced symptoms such as a short height, leaf yellowing, chlorosis, leaf senescence and plant stunting ( Figure 3a, Table 1), and approximately 17% of the V. longisporuminoculated plants were dead. The V. longisporum and V. dahliae isolates, identified from radish and mustard, respectively, caused similar symptoms and disease severity on canola Westar plants (Table  1). After harvest, the stems infected with V. longisporum displayed streaking, striping or blackening, and microsclerotia were observed on the stems (Figure 3b). V. longisporum isolates were recovered and confirmed from the infected stems of the canola plant, showing similar morphological characteristics ( Figure 3c). Westar plants were inoculated by the recovered V. longisporum isolates, and showed dwarfed and stunted plant growth, which indicated that the recovered V. longisporum isolate is the causal agent of Verticillium stripe disease in canola ( Figure 3d). The Verticillium isolates from canola and radish, as well as the V. longisporum isolates from the A1/D1 or A1/D3 groups, produced a 258 bp mtSSU-rDNA band, and the V. dahliae isolate from potato and V. longisporum isolate from the A1/D2 group produced 317 bp bands (Figure 2e). However, the V. dahliae isolate from mustard produced a 413 bp band, which was different from the V. dahliae potato isolate (Figure 2e). Furthermore, for the cytochrome b gene, all V. longisporum isolates produced a 226 bp band, whereas V. dahliae isolates from mustard and potato both produced a 320 bp band ( Figure 2f).

Disease Assessment
The Westar plants inoculated with V. longisporum showed disease symptoms in the form of yellowing and chlorosis at 7 and 14 days post-inoculation (dpi) ( Table 1). The mean scores of disease severity were significantly higher in the plants infected with the V. longisporum isolates identified in this study than in those inoculated with water after 14 and 21 dpi (Table 1). After 35 dpi, the plants inoculated with V. longisporum produced symptoms such as a short height, leaf yellowing, chlorosis, leaf senescence and plant stunting (Figure 3a, Table 1), and approximately 17% of the V. longisporum-inoculated plants were dead. The V. longisporum and V. dahliae isolates, identified from radish and mustard, respectively, caused similar symptoms and disease severity on canola Westar plants (Table 1). After harvest, the stems infected with V. longisporum displayed streaking, striping or blackening, and microsclerotia were observed on the stems (Figure 3b). V. longisporum isolates were recovered and confirmed from the infected stems of the canola plant, showing similar morphological characteristics (Figure 3c). Westar plants were inoculated by the recovered V. longisporum isolates, and showed dwarfed and stunted plant growth, which indicated that the recovered V. longisporum isolate is the causal agent of Verticillium stripe disease in canola (Figure 3d).

Discussion
This study identified and characterized Verticillium isolates from Brassica crops in Manitoba, Canada. A total of 29 isolates derived from canola were identified as the V. longisporum A1/D1 group by morphological and molecular characterization. To the best of our knowledge, this is the first scientific peer-reviewed report on the Verticillium disease in canola and radish caused by V. longisporum in Canada.
As described previously by Tran et al. (2013), V. longisporum A1/D1 strains have an intron within the 18S rDNA region, while V. longisprum A1/D3 strains have the same 18S rDNA and 5.8S rDNA as V. dahliae [19]. Therefore, we could not differentiate the V. longisporum A1/D3 isolates from V. dahliae using the rDNA region. All V. longisporum isolates (30) identified from canola and radish were characterized to the A1/D1 group and carried a MAT1-1 idiomorph. The polymerase chain reaction (PCR) identification of Verticillium isolates indicated that the multiplex PCR was the best assay, since it not only characterized the different V. longisproum lineages, but also differentiated them from the V. dahliae isolate. Verticillium longisporum and Verticillium albo-atrum produced 258 bp mtSSU-rDNA PCR-RFLP, while a 317 bp band was detected in Japanese isolates of V. dahliae [16]. However, the V. dahliae isolate from mustard identified in this study gave a longer digested fragment than the isolate from potato, indicating diversity among V. dahliae isolates from different host plants. As shown in this study, the PCR-RFLP genotyping assay with mtSSU-rDNA cannot differentiate the V. longisporum A1/D2 group from V. dahliae. At the same time, the PCR-RFLP genotyping assay using the cytochrome b gene did successfully differentiate V. longisporum and V. dahliae isolates. Thus, the multiplex PCR assay is recommended for the successful molecular identification of Verticillium species. In addition, the morphological differences between V. longisporum and V. dahliae, e.g., significantly longer conidia, irregular microsclerotia and more branched hyphae in V. longisporum, can assist identification.
Verticillium longisporum caused pale black stripes on the stem, as well as plant stunting, leaf senescence and microsclerotia formation close to harvest (Figure 3b). Pathogenicity testing using a V. longisporum A1/D1 isolate from canola indicated that inoculation with V. longisporum caused significantly greater disease severity after three weeks than the water control (Table 1). Since some of the disease symptoms scored were leaf yellowing or blackening veins, the canola plants experiencing regular leaf senescence were also rated as 2 or 3 in later stages of growth. This likely caused the scoring of the disease at 28 and 35 days post-inoculation (dpi) in canola plants inoculated with water. Verticillium longisporum A1/D1 is considered the most virulent group across Brassicaceae crops, especially on oilseed rape [20]. Verticillium longisporum A1/D1 was identified from cauliflower, eggplant and watermelon in California [20,21]. Verticillium dahliae has limited colonization capacity on canola, and can cause wilting at the seedling stage [10]. Verticillium longisporum is more virulent on Brassicaceae crops, which are its main hosts. Verticillium dahliae generally has a wider host range, and may affect other plant species more severely [8,11]. To the best of our knowledge, this is the first report to show V. longisporum lineage A1/D1 as a pathogen on oilseed rape in a North American field. Verticillium longisporum lineage A1/D2, which is considered the least virulent lineage of V. longisproum, was reported on horseradish in Illinois, in close proximity to the main oilseed rape-growing regions of the United States (Minnesota, North Dakota and Oklahoma) [20]. Canola acreage in the prairies had topped 22 million acres by 2017 (https://www.canolacouncil.org/markets-stats/statistics/harvest-acreage/). Identification of V. longisporum lineage A1/D1 isolates from canola and radish in Canada highlight the potential risk of Verticillium stripe disease in canola fields in the future as a threat to the trade of oil, seed and meal to global markets, especially considering that V. longisporum microsclerotia can survive in soil for up to 15 years, and has a wide range of Brassicaceae host species (https://www.canolacouncil.org/canolaencyclopedia/diseases/verticillium/#fnote6, Canola Council of Canada). Our study indicates that V. longisporum can cause significant yield losses and reduce oil quality. Ancestral species harboring A1 and D1 have not yet been identified, and they may come from non-agricultural hosts or non-pathogenic saprotrophs [8,14]. Since this is the first study to report V. longisporum lineage A1/D1 in canola and radish fields in Canada, surveys of this disease in fields of other Brassicaceae species are warranted. A recent study indicated that the 'V. longisporum A1/D1 West' population is genetically more diverse than the 'A1/D1 East' isolates, based on their geographic origins in Europe, which caused the sudden emergence of Verticillium stripe disease in the UK [22]. Understanding the genetic and population diversity of V. longisporum isolates derived from Brassica crops from east to west North America will help to identify the origins, the genetic basis of the hybridization process and the host range of V. longisporum lineage A1/D1.
Currently, no effective fungicides are registered to control Verticillium stripe disease in canola. The identified V. longisporum isolates will be used for B. napus resistance screening in both breeding varieties and commercial cultivars. Introducing resistance from Brassica carinata or Brassica oleracea (low susceptibility) is also an option for B. napus breeding programs to overcome Verticillium stripe disease [23,24]. Proper crop rotation, biosecurity practices, new fungicides, weed management, increasing soil fertility and resistance breeding will help to develop a successful control strategy against this soil-borne disease.

Sample Collection and Fungal Pathogen Isolation
Stems of Brassica crops such as canola, mustard and radish showing Verticillium disease symptoms were collected in Portage La Prairie, Manitoba in 2016. The striped stems were peeled and cut into small pieces (1 cm long). The small diseased pieces were surface-sterilized by dipping into a bleach solution of 10% NaOCl with 20 µL Tween-20 (Sigma, Toronto, ON, Canada) for 2 min. The sterilized sections were then rinsed in sterile distilled water for 2 min, soaked in 70% ethanol for 2 min and washed again with sterile distilled water for another 2 min. The stem sections were placed in Petri dishes containing potato dextrose agar (PDA) and incubated at room temperature. Fungal colonies growing out of the diseased tissues were purified using the single-spore technique, and cultured on PDA for two weeks. An isolate of V. dahliae from potato (Vd1396-9) was obtained from Dr. Fouad Daayf (Plant Science, University of Manitoba), and included as a reference isolate for this study. To categorize the lineages of V. longisporum, three reference isolates were included, one representing each of the three species A1/D1, A1/D2 and A1/D3. Reference lineages were kindly supplied to us by Drs. A. Tiedemann (Department of Crop Science, University of Gottingen) and K. Subbarao (Department of Plant Pathology, University of California, Davis) (Table S1).

Morphological Identification of Isolates
A representative isolate of V. longisporum from canola, VL-H1, which was obtained in this study, and a reference isolate of V. dahliae from potato (Vd1396-9) were grown and maintained on PDA at room temperature for two weeks. The colony morphology, conidia shape, microsclerotia and hyphae of isolates were observed under a microscope (Fisher Science Education), and used to differentiate the Verticillium species [5,6]. Each of the 30 conidia from 14-day-old cultures of V. longisporum and V. dahliae, respectively were measured under the microscope, using a micrometer to determine conidia length.

DNA extraction, PCR Amplification and PCR-Restriction Fragment Length Polymorphism
Genomic DNA from 29 Verticillium isolates obtained from canola, radish and mustard, and reference isolates (Table S1) were extracted from a mixture of mycelia, microsclerotia and conidia suspensions using a modified CTAB method [25]. The extraction buffer was briefly aliquoted to the harvested mixture and homogenized. After incubation at 65 • C for 30 min, DNA was extracted with phenol/chloroform/isoamyl (25:24:1). The supernatant was then precipitated and washed with 95% and 70% ethanol, respectively. Finally, the DNA pellet was dissolved in 100 µL DNase-free water.
mating type gene amplification [16]. All primers used are listed in Table 2. The polymerase chain reaction (PCR) amplification was conducted in a total volume of 25 µL, with a reaction mixture containing 25 pmol of each primer, 3.75 mM MgCl 2 , 1.25 mM of each deoxynucleoside triphosphate (dNTPs) and 1.25 U EconoTaq DNA polymerase (Econo Taq DNA polymerase, Lucigen, Middleton, WI) with 2.5 µL supplied 10 × PCR reaction buffer, and a 10 to 50 ng DNA template. The PCR thermocycling began with a 3-min first step at 95 • C for denaturation, and then 35 cycles of amplification at 95 • C for 30 s, annealing temperature for 30 s and extension at 72 • C for 1 min, and then completed with a final extension step at 72 • C for 5 min. The PCR products were separated on a 2.0% agarose gel stained with Redsafe (iNtRON BIOTECHNOLOGY, Seongnam-Si, Korea). A multiplex PCR assay developed by Inderbitzin et al. (2013) was used to identify the lineage of the characterized Verticillium isolates [26]. Briefly, the primer mixture was prepared by adding 6.25 µL each of D1f/AlfD1r (GPD gene, glyceraldehyde-3-phosphate dehydrogenase), 6.25 µL each of A1f/A1r (elongation factor 1-alpha) and 3.25 µL each of Df/Dr (ITS, internal transcribed spacer region) ( Table 2), and then finally adding 93.75 µL sterile water to a total volume of 125 µL. The initial concentration of mixed primers was 100 µM. The PCR reaction was conducted in a 25 µL volume, which included 2.5 µL of mixed primers, 2.5 mM dNTPs, 2.5 µL of supplied 10 × PCR reaction buffer, 2U EconoTaq DNA polymerase (Econo Taq DNA polymerase, Lucigen, Middleton, WI, USA) and a 50 ng DNA template. The PCR program comprised a 2-min initial denaturation at 94 • C; 35 cycles of amplification at 94 • C for 10 s, 54 • C for 20 s and 72 • C for 1 min, and a final extension at 72 • C for 7 min.
To further confirm the identification of Verticillium isolates, regions of the mitochondrial small-subunit rRNA gene and the cytochrome b gene were amplified with the primer pairs NMS1/NMS2 and cobF1/cobR1, respectively [9,27] (Table 2). The amplicons of 584 bp for mtSSU-rDNA and 320 bp for the cytochrome b gene were then digested using the restriction enzymes MseI and DdeI (New England BioLabs, Ipswich, MA, USA), respectively. The digested products were separately visualized in 1.5% agarose gels, as described above.

Pathogenicity Tests of V. longisporum on Canola
Pathogenicity was tested on B. napus cultivar Westar, a spring canola cultivar which is mostly susceptible to fungal pathogens in Canada. To prepare the inoculum, identified Verticillum isolates were grown on a PDA medium for 10 days at room temperature. Five agar discs were transferred to 250 mL flasks of sterile potato dextrose broth, and incubated for two weeks at room temperature with shaking (120 rpm) in the dark. The conidia suspension was harvested by filtering with sterilized Miracloth (Millipore Sigma, Oakville, ON, Canada), and the concentration was adjusted to 1 × 10 6 conidia mL −1 with sterile distilled water on the day of inoculation. Four-week-old seedlings of cv. Westar were gently uprooted and washed with tap water to clean soil off the roots. The roots of 16 seedlings were then immersed in 250 mL of the conidia suspension for 30 min [16,20], and then transplanted to pots. Controls for the pathogenicity test included 16 seedlings that were dipped in water for 30 min and then transplanted to pots. After treatments, all the plants were placed in a growth chamber at 16 • C (night) and 21 • C (day), with a 16 h photoperiod. The experiment was repeated once in the greenhouse to check data reliability. After maturing, the infected stems of canola were subjected to the same method to recover the isolates from infection sites, as described above. Then, the recovered isolate was inoculated onto the Westar plant again to confirm that the V. longisporum isolate was a causal agent of the disease.

Statistical Analysis
Statistical analysis of the conidia length of Verticillium isolates, the disease score of pathogenicity test, the F measurement of the distance between two repeats and canola phenotypes, including plant height, oil content, seed weight and glucosinolate contents, were conducted using SAS version 9.4 (SAS Institute, Inc., Cary, NC, USA).


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Optimizing productivity of fat-tail sheep using single cell protein in concentrate

Application single-cell protein in ruminant feed has a purpose to fattening, which one of parameter to measure is average daily gain (ADG). The name of single-cell protein in this research is ajitein. The research aimed to evaluate the nutritive value of ajitein toward feed consumption, average daily gain and feed conversion in fat-tailed sheep. In this research, ajitein was mixed with other feedstuffs (soybean meal, pollard, coconut cake, corn bran, palm cake, molasses, urea, and minerals) and the crude protein in this concentrate was isoprotein (22%). The treatments in this research consist of P0: elephant grass (ad libitum) with concentrate; P1 : elephant grass (ad libitum) with concentrate (ajitein 2%); P2 : elephant grass (ad libitum) with concentrate (ajitein 4%); P3 : elephant grass (ad libitum) with concentrate (ajitein 6%). The result showed that the highest feed intake in this research was P0 (104.9 ± 12.90 g / kg BB0.75 / day). Then the higher body weight gains are P0 and P3, with 140 g/head/day respectively. The feed conversion of P3 was 6.6 ± 0.87. The conclusion was P3 had good ability to change the feed to be meat more effective.

Introduction
The potential for developing sheep fattening in Indonesia is growing due to an increasing amount of meat demand. Besides, sheep breeding is prospective to be developed in the future because of its easy maintenance, relatively short reproductive cycle, and resistance to disease. Sheep fattening ideally starts when the age of the sheep is less than one year old, considering it is the age when the sheep is in a fast growth phase, ie when feeding will be converted into meat. An important factor that needs to be considered in the process of sheep fattening is feed.
Feed is defined as a substance that can be eaten, digested and used by livestock. The amount of feed consumed by a livestock is one of the important factors that directly affect livestock production. Feed consumption is the number of feed that are eaten by livestock to meet nutrient needs for daily life, growth, and production. Sufficiency of these nutrients can be seen through the weight gain of livestock, making it the benchmarks for assessing feed quality. Knowing feed consumption and body weight gain, we can estimate the feed conversion value. Feed conversion value is used to see the efficiency of feed consumption. The lower the feed conversion value, the better the quality of the feed.
One nutrient requirement in feed that must be considered is protein. In the body of the cattle, protein is used to improve body tissues and produce new tissues [6]. Sheep get protein from feed and microbial protein. Increased protein consumption is also influenced by the protein content in the feed, the higher the protein content, the more protein is consumed. In addition to being associated with the level of feeding, the use of protein is also related to the body weight of livestock. Livestock with low body weight and that are in the growth phase require higher protein than adult livestock that are in the  [6]. Efforts made to improve the quality of ruminant feed are usually hampered by protein content because high protein feed ingredients have a higher price than the normal feed. Therefore, there is a need for an alternative to using protein feed from non-conventional feed ingredients. Many studies have suggested increasing the protein content in feed by utilizing single-cell proteins.
Ajitein is a single cell protein that has a high protein and amino acid content. Adding Ajitein in feed may reduce the use of soybean and fish flour, resulting in cheaper feed cost. As a conclusion, it is necessary to conduct research on the effect of ajitein as a source of protein used in concentrate on feed consumption, average weight gain (ADG), and the feed conversion of Fat Tailed Sheep. The objectives of this study was to evaluate the nutritive value of ajitein toward feed consumption, average daily gain and feed conversion in fat-tailed sheep and the optimum level of using Ajitein in the ratio of feed concentrate.

Material and Methods
The research method used in this study was an experimental method using a completely randomized design consisting of four feed treatments with three replications (table 1). The experiment was carried out by using fat-tailed sheep which were placed in individual cages (metabolic cages). Before entering the metabolic cage, body weight is weighed to classify livestock based on their body weight ie low body weight, moderate body weight, and big body weight.
The treatment in this study is the usage level of Ajitein in concentrate by considering the same protein content (isoprotein). The treatment given to sheep during the study is as follows: P0 = Elephant Grass (ad libitum) + concentrate without Ajitein; P1 = Elephant Grass (ad libitum) + concentrate (Ajitein 2%); P2 = Elephant Grass (ad libitum) + concentrate (Ajitein 4%); P3 = Elephant Grass (ad libitum) + concentrate (Ajitein 6%). Data obtained during the study were analyzed using variance analysis (ANOVA). If the treatment has a significant effect on the variables observed, the next analysis will be Duncan's Test.

Feed Nutrient Content
The content of DM (dry matter), OM (organic matter), and CP (crude protein) of feed used in the study can be seen in table 2. The content of these nutrients was obtained from the analysis at the Laboratory of Animal Nutrition, Faculty of Animal Scinces, University of Brawijaya. The CP forage content of elephant grass used in this study is 11.46 %. The number of leaves is closely related to cutting age, the older the cutting age, the greater the production of stems. Forages that have the ability to produce a lot of leaves will have good quality, namely high nutritional content and ultimately large digestibility [10]. Production of elephant grass, if it exceeds or passes the age of cutting, will reduce the quality of the forage. To optimize production and maintain quality, cutting must be done on time. Optimal cutting age is 7 weeks or 50 days.
The protein content of the concentrate for each treatment P0, P1, P2, and P3 based on the data above is 21.73%; 22.85%; 22.61% and 22.3% respectively. From these data, it can be concluded that the protein content of the studied feed used is isoprotein. This showed that the protein content in the feed is in accordance with the research method. The protein content is sufficient for the CP sheep needs. The CP concentrate in this study has higher content compared to that in [3] study which added FML (Fermented Mother Liquor) to the concentrate. CP content at P0, P1, P2, and P3 was 19.22%; 19.62%; 20.01% and 20.39 % respectively. In general, CP requirement for sheep is 9.6% -19.3% [8]. This requirement declined as the body weight of the sheep increased. The addition of concentrates in livestock rations is an attempt to meet the needs of feed substances for livestock, both protein and energy need, in order to obtain high production. Besides, the use of concentrates can increase digestibility of dry matter ration, increase body weight and efficiency in ration used.

Feed consumption
Feed consumption is the amount of feed that can be eaten by livestock in a certain time [7]. Consumption is an important indicator in the feed evaluation. Consumption of DM (DMC), OM (OMC) and CP (CPC) for each feed treatment is shown in The results of the DM consumption (g/kg BW 0.75 /day) showed that the addition of Ajitein did not give a significant effect on the consumption of DM. This could be due to the CP and TDN (total digestible nutrient) content in the treatment feed used was similar so that it did not affect the feed consumption.
From the data above, it is known that the total consumption of DM (kg/head/day) for P0, P1, P2 and P3 respectively are 0.972 kg, 0.846 kg, 0.889 kg and 0.915 kg. Dry matter consumption in this study was higher than the results of the study by [3] who used the addition of FML to the concentrate. The dry matter requirement in sheep feeding according to [8] is 500-1000 grams per day with a body weight of 10-20 kg. Low consumption of total dry matter might be due to the low level of palatability. Palatability is influenced by the smell, taste, texture, and form of feed given to livestock. The factors that affect the palatability for ruminants are the brightness of forage color, taste, texture, and nutrient content. This is influenced by the physical and chemical factors of forage [4]. The amount of the feed consumption depends on palatability, the crude protein content of feed, body size of livestock, type of ration and physiological status of livestock [7]. The more the amount of concentrate given, the higher the amount of feed consumption.
Crude protein consumption for each treatment P0, P1, P2, and P3 respectively are 0.179 kg; 0.153 kg; 0.158 kg and 0.162 kg. The results of variance analysis showed that the treatment had no significant effect on the total CP consumption of livestock (g/kg BW 0.75 /day). These results showed that the addition of Ajitein levels on experiments may increase the consumption of crude protein. The requirement of crude protein in sheep feeding according to [8] is 114-160 kg, for the body weight of 20-30 kg and daily body weight gain of 100-200 g/head/day. Therefore, it can be concluded that the CP requirement have been met. Protein is an important element in the livestock's body and is needed continuously to repair cells in the synthesis process [2].
Livestock consume feed to meet feed needs. The feed consumption is influenced by several factors, namely the type of animal, type of feed, and the environment. In addition, limited rumen capacity is a factor that influences the consumption of dry matter. Although the data from this study did not show any significant differences, consumption (g/kg BW 0.75 / day) of DM, OM and CP tended to increase along with the addition of Ajitein in the treatment feed.  From the total DM consumption data above, it is known that the total consumption of livestock (% BW) ranges from 4.67-5.00%. The higher the Ajitein levels in the treatment feed may increase the amount of livestock feed consumption. This can be seen from the increase in consumption (% BW) at P1, P2, and P3 in table 4. The ratio between consumption of forage and concentrate for P0, P1, P2, and P3 were 38.96%: 61.04%, 44.33% : 55.67%, 47.17% : 52.83%, and 44.78% : 55.22% respectively. These ratios are still below the normal feeding ratio for fattening.
According to [7], meeting the needs of balanced protein and energy in fattened cattle cannot be obtained from forage feeding only but also from additional concentrate feeding. This is because the concentrate is a source of protein and energy, while forage is only the source of fiber. Therefore, the ration prepared for sheep fattening should consist of fiber and concentrate to complement the needs of livestock and optimized its appearance. The high energy content in feed may cause ruminant to stop eating if the feed needs have been met even though the rumen capacity is still able to accommodate more feed [1]. Addition of Ajitein in sheep feeding does not give a real effect on the level of consumption of DM, OM, or CP. However, the addition of Ajitein leads to the lower use of soybean pulp in the ration. The following is a diagram of the use of soybean pulp in the researched ration.
In P0 (without Ajitein addition), the highest amount of soybean meal used is 8%. This is considered inefficient and requires high feed cost. But in the treatment of P1, P2, and P3 with the addition of Ajitein, the use of soybean meal is lower than P0. In P3, the use of soybean meal is only 5% of the ration, this greatly saves the feed cost. From this argument, it can be seen that the addition of Ajitein at the level of 2%, 4% and 6% may reduce the use of soybean meal in rations and followed by an increase in the amount of feed consumption.

Average Daily Gain
One factor that influences body weight gain is feed consumption. This is closely related to the nutrients contained in the feed and the level of digestibility of the feed. Rations that have high nutritional value and a good level of palatability may quickly increase body weight gain of livestock during fattening. The average daily weight gain of sheep in each treatment can be seen in The results of the analysis of variance in the data above showed that the treatment had no significant effect (P> 0.05) on the daily body weight gain of sheep. However, it can be seen that the Ajitein addition of 2% to 6% gives a good influence on increasing the average daily gain. ADG of P0, P1, P2, and P3 in this study was 140; 120; 126.67 and 140 g/head/day respectively. The results of ADG are in line with feed consumption, namely DMC, OMC and CPC in table 3. The increase of Ajitein addition, leads to increased feed consumption, followed by increased ADG.
Changes in body weight data are used as an indicator to determine the nutritional needs of livestock. Increasing and decreasing of feed consumption is usually followed by an increase and decrease in body weight each week. This shows that body weight gain is positively correlated with feed consumption and feed substances.
The amount of feed consumption of sheep will experience a shift in accordance with the BW of the sheep. According to [8], at 10 kg BW, DM consumption of sheep may reach 5% BW and at BW 50 kg the consumption may shift to 3% BW. Based on the value of the shift, it can be seen that each increase of 1 kg BW, DM consumption by sheep may decrease by 0.05% BB.

Feed Convertion
Feed conversion shows the ability of livestock to convert feed consumed into meat. The lower the conversion value, the higher the ability of livestock to turn feed into meat. The results of the variance analysis showed that the treatment did not give a significant effect on feed conversion (P> 0.05) because DM consumption and ADG produced showed no significant effect. Average feed conversion can be seen in table 6.
From the above data it can be seen that the feed conversion at P0, P1, P2, and P3 is 7.00; 7.23; 7.20 and 6.59 respectively. The lowest conversion value is 6.59 (P3) which means that to produce 1 kg of meat requires 6.59 kg of feed. P3 feed conversion value is better than P0. At P0, DM consumption is 972.45 gr/head/day with BWG 140 gr having a conversion value of 7.00 while in P3 the consumption of DM is 914.87 g/head/day with ADG 140 g having a conversion of 6.59. By comparing these two data, it can be seen that sheep feeding using Ajitein addition has the ability to convert feed into meat better than feed with no Ajitein. Although in P0 feed consumption is higher than P3, the ADG produced are the same. Accordingly, it can be concluded that feed with the addition of Ajitein is more efficient and may reduce the feed conversion value. This indicates that the addition of 6% Ajitein in the concentrate is most effective for increasing body weight gain.
This study differs from the research done by [10] which has a higher feed conversion average value of 7.63. This might be due to the use of different protein feed and crude protein content. The CP content in the feed used in this study was 21.73 -22.3% while the average CP used in [10] study was lower, i.e. 13.60-16.99%.
The feed conversion value estimated in this study is good because according to [5], feed conversion for sheep in tropical regions ranges from 7-15. Sheep in the fattening period, generally have a feed conversion value of 5 to 10. Feed conversion, especially for small ruminants, is influenced by the quality of the feed, digestibility, and efficiency of nutrient utilization in metabolic processes in the body tissues of livestock. The better the quality of feed consumed by livestock, followed by high body weight gain, the lower the conversion value and the more efficient the feed consumption.

Conclusion
Addition of Ajitein level may increase feed consumption, body weight gain, and reduce feed conversion value. P3 treatment (6% Ajitein addition) showed the highest consumption and weight gain, as well as low conversion value and is efficient in the use of soybean meal.