extfieldsofstudy:
Medicine
Environmental Science

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An assessment of irrigated rice production energy efficiency and environmental footprint with in-field and off-field rice straw management practices

The research provided scientific evidences for improved rice straw management. Rice cultivation with in-field burning of rice straw is the worst option with the lowest energy efficiency and highest air pollution emission. This article comprises a comparative assessment of energy efficiency and the environmental footprint of rice production using four different rice straw management scenarios, namely, straw retained, straw burned, partial straw removal, and complete straw removal. Paddy yield, grain quality, and energy balance were assessed for two seasons while greenhouse gas emissions (GHGE) were measured weekly starting from land preparation through to the cropping and fallow period. Despite the added energy requirements in straw collection and transport, the use of collected rice straw for mushroom production can increase the net energy obtained from rice production systems by 10–15% compared to burning straw in the field. Partial and complete removal of rice straw reduces GHGE by 30% and 40% compared to complete straw retention, respectively.

crop, soil, and water management all straw can be removed from flooded rice fields after harvest without reducing the levels of soil organic matter or soil fertility 10,11 .
Life cycle assessment (LCA) of rice production was reported in recent studies. Amarante et al. 12 reported that using rice straw for bioenergy production through anaerobic digestion to be used as alternative or substitute to diesel fuel for transportation purposes has the lowest environmental impact as compared to other alternatives such as soil incorporation of rice straw. Soam et al. 13 conducted a LCA study on cellulosic production from rice straw in India and reported the major benefits of GHGE and energy when using biomass to generate electricity resulting to displacement of coal-based electricity. The LCA on environmental footprint of rice production was also presented in other publications such as Blengini and Busto 14 ; Thanawong et al. 15 ; and Brodta et al. 16 .
However, these studies have not considered the various straw management practices utilized by farmers. To identify the best practices of rice straw management for irrigated rice production, within this study, we conducted a comparative analysis on energy balance and environmental footprint of rice production under contrasting rice straw management scenarios using an LCA approach and based on a field-experiment at the International Rice Research Institute in the Philippines. The knowledge gained from this research will illustrate the potential environmental and economic consequences of contrasting rice straw management options. While this study aims to identify the impact of contrasting straw management options on the energy balance and productivity of rice farming it does not aim to identify the total scope of agronomic changes that may be required to optimize these contrasting straw management scenarios.

Materials and Methods
Site description and experimental design. Two  Four rice straw management scenarios which are considered treatments were implemented in a completely randomized design using plots of 500 m 2 with three replications. The treatments were classified as -all straw retained in the field after harvest (SRt), straw burning after harvest (SB), partial straw removal (PSRm) where about 60% rice straw was removed from the field after harvest and complete straw removal (CSRm) where both stubble and straw were removed from the field after harvest. The treatments were imposed at the start of the 2015WS after a uniform rice crop was harvested from the experimental field. LCA was undertaken on data collected from this field experiment in conjunction with an investigation of greenhouse gas emissions under contrasting straw management scenarios 4 .
The cropping schedule and agronomic practices used in this study were representative of common irrigated rice production practices in many rice growing regions of Southeast Asia (SEA). Each season during land preparation the primary tillage was undertaken with a disc plow under dry soil conditions using a four-wheel tractor, while the secondary cultivation, in the form of puddling and harrowing, was done under saturated soil condition with a two-wheel hand tractor. A final leveling before crop establishment was undertaken using a two-wheel tractor pulling a wooden plank approximately 3 meters wide. Fourteen day-old seedlings were used and established by manual transplanting in a 20 centimeter (cm) by 20 cm spacing. The rice variety grown each season was National Seed Industry Council (NSIC) Rc18 which is a popular variety in the Philippines. Transplanting was undertaken on the 18 th June 2015 for the wet season crop and on the 22 nd December 2015 for the dry season.
Fertilizer management in this experiment was uniform across all treatments with details of timing and rate provided in Table 1. The amount of fertilizer applied for both seasons was determined using the site specific nutrient management software which is the IRRI Rice Crop Manager. The fertilizer was a complete fertilizer (14-14-14), which was applied each season at 7-10 days after transplanting (DAT). The succeeding two splits of nitrogen were applied as Urea (46-0-0) at maximum tillering (28)(29)(30) and at panicle initiation (42)(43)(44)(45). All fertilizers were applied using a Polaro fertilizer spreader manufactured by Lehner Agrar GmbH.
Weeds were managed through the application of a pre-emergence herbicide with active ingredient (a.i) Pretilachlor, which was tank-mixed with molluscicide (a.i. Niclosamide) to control Golden Apple Snail (Pomacea canaliculata). The tank mix was applied immediately after transplanting. In addition to the application of the  molluscicide, from 0 to 7 days after transplanting (DAT) the soil in the experimental field was kept saturated but without any standing water to reduce the risk of damage caused by Golden Apple Snail. Hand weeding was also conducted twice during each season to prevent and control weeds. In the 2015WS the irrigation supply was managed based on a conventional method of continuous flooding. Water was maintained at a depth of 3-5 cm from 14 days after transplanting until 10 days prior to harvest when the field was drained to encourage uniform maturity of rice grains and to enable harvesting activities to be conducted under dry soil conditions. In the dry season, mild water stress was experienced by the crop between tillering and flowering on a number of occasions, due to the limited availability of irrigation water. However, when water was available the field was kept flooded at 3-5 cm of standing water and a similar end of season drainage event was implemented as was achieved during the wet season.
Soil sampling and analysis. To quantify any impacts of the straw management scenarios on soil chemical conditions, soil samples were collected from each experimental plot prior to land preparation at the start of the 2015WS and after harvest of the 2016DS crop. Composite soil samples of approximately 500 gram (g) dry weight were collected randomly from 0-15 cm using a soil auger with a diameter of 5 cm from within each experimental plot. The soil samples were air dried at 35-40 Celsius (°C) and then ground to pass a 2 mm sieve to remove any gravel before analysis. All soil analysis was conducted by the Analytical Services Laboratory at IRRI 17 . Quantification of cation-exchange capacity (CEC) was conducted using the indophenol blue method. Particle size distribution was determined using the hydrometer method with Calgon as the dispersing agent. Available potassium (K) was determined using ammonium acetate extraction with the extract being analyzed via flame emission spectrometry. Total soil carbon (C) and nitrogen (N) were quantified via combustion coupled with a gas chromatograph and thermal conductivity detector. Soil pH was determined in a 1:1 soil-water solution.
Quantification of grain yield and total biomass. Straw biomass samples were collected immediately prior to harvest using three 1 meter (m) × 1 m sampling frames randomly placed in each plot with all above-ground biomass collected. Grain yield was determined from the total harvested yield from each experimental plot. The threshed paddy and the rice straw yield were weighed and recorded at fresh weight, and at dry weight (MC = 0) for both yield and biomass. The moisture content of the paddy was determined by the drying oven method 18 . Head rice recovery (HRR), a grain quality parameter that represents the percentage of whole grain recovery after milling, was calculated using Equation Eq. 1.

= × HRR
Weight of whole grains Weight of paddy samples (%) 100 (1) To quantify HRR after threshing, three subsamples of at least 500 g of paddy were taken randomly from the grain harvested in each plot. After cleaning these samples using a Seedburo Paddy Blower, 250 g of filled grains were passed twice in the RISE 10" Rubber Roll Husker, then through a SATAKE Abrasive Whitener, and finally through a SATAKE Test Rice Grader. The whole grain recovered during milling was graded and weighed for the measurement of the HRR ratio.
Life cycle assessment. The life cycle assessment scope of this study is presented in Fig. 2 and its impact analysis was conducted using the SIMAPRO 19 software. This study does not consider the effect of transport of agronomic inputs or the influence of irrigation source in the analysis, as generally there is limited opportunity for an individual farmer to manipulate these aspects of their farming practice. However, in the analysis of the energy www.nature.com/scientificreports www.nature.com/scientificreports/ balance and GHGE for rice straw, assumptions on the transport of this biomass and other factors in its utility outside of the field after harvest are included. nutrient balance analysis. To calculate the balance of nutrient in straw incorporated into the soil, the nitrogen, phosphorous, and potassium content of straw retained in the field was measured from samples collected in the field immediately before in-field burning and incorporation. The laboratory result showed that rice straw contains 0.76-0.86% dry matter (dm) Nitrogen; 0.05-0.06% dm Phosphorus; and 1.30-1.54% dm Potassium. energy balance analysis. An energy analysis of agronomic inputs and harvested outputs was undertaken over the duration of this study and both components were recorded and converted to an energy value using energy factors obtained from the available literature, as were the harvested outputs from the system. Net energy (NE) was calculated based on difference between the total input energy (IE) and output energy (OE) (Eq. 2).
fuel labor a gronomic production maintenance where E fuel , E labor , E agronomic , E production , and E maintenance represent the energy consumed (MJ ha −1 ) converted from diesel consumption, labor, agronomic inputs (fertilizer and pesticide), production of machines and equipment, and machine maintenance, respectively. The values obtained for harvested grain and rice straw were used to calculate the output energy of each straw scenario system. Pimentel and Pimentel 20 quantified the energy content of rice grain as 15.2 MJ kg −1 dm, which is the value used in this study for all straw management scenarios. In contrast to grain as a human food source, the energy value of rice straw will vary depending on its treatment and utility. Within this research the energy value of rice straw was based on the following assumptions: www.nature.com/scientificreports www.nature.com/scientificreports/ • Straw retained in the field (SRt and PSRm): energy accounted for N, P, and K contained in rice straw. These data were measured from straw sample analysis before incorporation into the soil. • Straw burnt in the field (SB): energy value of this scenario was based on the N, P, K contents determined for the rice straw. However, losses of N, P, K in rice straw as a result of burning were assumed to be 100, 25, and 20%, respectively, as described by Dobermann and Fairhurst 21 . • Straw removed from the field (PSRm and CSRm): the removed straw was accounted in the supply chain of mushroom production. Net energy of this production accounted for mushroom produced (economic based equivalent) and all the inputs (rice straw, water, power consumption, etc.) was about 3,500 MJ Mg of rice straw 22 .
The energy and GHGE conversion factors for agronomic inputs, processes, and products were presented in Table 2. The energy value and GHGE conversion factors of related materials were based on Ecoinvent database 3.0 5 , global warming potential 100 years (GWP-100a) of IPCC 23 incorporated in SIMAPRO software 19 . Global warming factors -100 years (GWP-100a) of CH 4 and N 2 O are 30.5 and 265 kg carbon dioxide equivalent (CO 2 -eq). Production inventory data of energy and GHGE per unit of fertilizer chemicals refer to 1 kg N in urea with an N-content of 32%; 1 kg P 2 O 5 in ammonium nitrate phosphate with a N-content of 8.4% and a P 2 O 5 -content of 52%; and 1 kg K 2 O in potassium chloride with a K 2 O-content of 60%. These data take into account the production activities including transports of raw materials and intermediate products but do not account for waste treatment of catalysts, coating and packaging. Similarly, energy and emission factors of herbicide are accounted for from their life cycle of production. Energy consumption and GHGE of machines were calculated based on 44.8 MJ L −1 of diesel 5 accounting for production, transportation, and combustion in machinery. In addition 15 MJ L −1 was added for machine production 24 . Estimation of GHGE incurred from straw removal scenarios included emissions eminating from the straw collection process, transportation, and mushroom production. Estimation of emissions from straw collection were based on the study by Nguyen et al. 22 , which concluded that GHGE in this activity were between 60-165 kg CO 2 -eq Mg −1 of straw collected. Transportation of straw bales from the rice field to the site of mushroom production was assumed to be 10 km, which is equal to a GHGE of 5.78 kg CO 2 -eq Mg −1 of straw 5 . Emissions from the mushroom production process are estimated to be between 3.2 and 10.1 kg CO 2 -eq Mg −1 rice straw 25,26 .
Labor energy was calculated based on the metabolic equivalent of task (MET). Ainsworth et al. 27 describes the MET as the ratio of human metabolic rate when performing an activity to the metabolic rate at rest. This ratio is converted to energy value as MJ h −1 using the method described by Quilty et al. 28 with the assumption of an Asian human body weight of 54.4 kg 29 .
Measurements and analyses of greenhouse gas emissions. The GHGE from the flooded soil were directly quantified in the field by Romasanta et al. 4 , while the emissions from fuel consumption and the indirect emissions from agronomic inputs were calculated using conversion factors presented in Table 2. Direct GHGE were measured in-situ in each experimental plot on a weekly basis during each of the two seasons. The total sampling period for GHGE each season was 175 days. GHGE sampling began prior to land preparation of the www.nature.com/scientificreports www.nature.com/scientificreports/ 2015WS crop, and continued through both cropping seasons and fallow periods after harvest. The GHGE samples were collected using the static chamber method as described by Sander et al. 30 . Emission factors from in-field rice straw burning used in this analysis are presented in Table 3. The emission factors for methane and nitrous oxide generated from straw burning are based on the results reported by Romasanta et al. 4 . Emissions were converted to Mg ha −1 rice straw at 14% MC based on the yield of rice straw in the experimental plots. Table 3 also shows the other pollution factors from straw burning including particulate matters (PM 2.5 and PM 10 ). However, these pollution factors are simply used for discussing pollution and health problems that are not accounted for by GHGE. An indicator of pollution and health problems is represented by a human toxicity index with its unit of kg of 1,4-dichlorobenzene equivalent (kg 1,4db-eq). This can cause chronic and cancer effects with a risk threshold of 0.4 mg per kg of body per day or equivalent to 30 mg per person per day 31 .
Statistical analysis and software. Analysis of Variance was used to evaluate the effects of the contrasting rice straw management scenarios on the measured production and environmental parameters using a least significant difference at P < 0.05 to compare mean values. The ANOVA was computed using the Statistical Tool for Agricultural Research (STAR) software developed by IRRI 32 . Energy balance analysis was based on the Cumulative Energy Demand 1.09 method 32 , and CO 2 equivalent analysis was based on the GWP-100a of IPCC 23 . Conversion of agronomic inputs and fuel consumption to energy value was carried out using the Agri-Footprint, ECOINVENT 3, Industry Data 2.0 database 5 .

Results
Effects of straw treatments on soil chemical condition. No significant differences were identified in the measured soil properties between the experimental plots in the samples collected prior to land preparation for the 2015WS (Table 4). Similarly, there were no significant differences in the soil samples collected after harvest of the 2016DS. The mean value for all measured soil parameters, apart from soil pH, were found to increase in each straw treatment scenario between the initial soil samples collected before land preparation in the wet season of 2015 and the soil samples collected after harvest of the 2016DS crop. The mean soil pH values decreased, but not significantly, across all treatments between the initial and final soil samples. Significant differences (p-value < 0.05) were identified between the initial and final soil samples in the total soil C and CEC in both the PSRm and SRt treatments, and in available K in the SRt scenario (Table 4).
Rice grain and straw yield and head rice recovery. No significant differences in grain yield or head rice recovery were observed between any of the straw management scenarios in either of the seasons (Table 5). Across the four scenarios the rice yield in the wet season ranged from 4.9 to 5.2 Mg ha −1 in dry weight (dw). In the dry season the rice yield was lower than in the wet season, ranging from 3.5 to 3.8 Mg dw ha −1 . Similarly, HRR was higher in the grain produced in the wet season (62. 5  www.nature.com/scientificreports www.nature.com/scientificreports/ mean of straw yield at harvest was 2.54 Mg dw ha −1 . The harvest indexes (grain yield per total harvested biomass yield) were 0.66 and 0.52 for 2015WS and 2016DS, respectively. This factor, particularly for 2015WS was high mainly because of the short-plant variety (NSIC Rc18) with its plant length of about 1 meter. The mean amount of straw incorporated (SRt scenario) or burn (SB scenario) in the field were about 2.2 Mg ha −1 in dry weight, lower than the straw yield at harvest because of the mass loss from harvest to the straw treatments. Similarly, the mean amount of straw removed from the CSRm and PSRm scenarios was 2.2 and 0.9 Mg ha −1 in dry weight, respectively, lower than the straw yield at harvest because of accounting for the losses. energy balance. The total fuel consumption in the 2015WS varied from 88 to 94 L ha −1 across the four straw management scenarios, which is not significantly different to the values recorded in the 2016DS in which the fuel consumption ranged from 87 to 89 L ha −1 . In the 2015WS the total IE from manual labor activities for PSRm, SB, and SRt scenarios was 244-263 MJ ha −1 while for CSRm it was recorded at 361 MJ ha −1 with the additional labor for cutting the remained stubble after harvest. The IE values for manual labor during the 2015WS were more than double to that of the dry season for the PSRm, SB and SRt scenarios, and 50% higher in the CSRm scenario.
The total IE for rice production was approximately 14 and 16 GJ ha −1 for the wet and dry season, respectively ( Table 6). The IE of the different scenarios in each season was similar because it did not include the energy for rice straw collection required in both the PSRm and CSRm scenarios. This energy for removing straw was accounted in the supply chain of mushroom production and generated an additionally net energy of 2.7-6.7 GJ ha −1 .
The total OE ranges were 76-84 GJ ha −1 and 54-62 GJ ha −1 for the wet and dry seasons, respectively. The higher OE achieved in the wet season was the result of the higher yield produced in this season. OE consists of energy obtained from paddy, using rice straw removed for mushroom production (for CSRm and PSRm), and incorporation of rice straw and ash retained in the field (for PSRm, SB, and SRt). Despite that, incorporation of all rice straw generated about 1.3 GJ ha −1 , however the OE of SRt remained lower by 3-10% than that of PSRm and CSRm. The loss of the nutrients from burning of rice straw in the field in the SB scenario resulted in the OE of SB being 7-14% lower than that of PSRm and CSRm.
The net energy values ranged from 62 to 71 GJ ha −1 in the wet season and 38 to 46 GJ ha −1 in the dry season. Only the net energy of SB scenario in the wet season of 2015 was significantly different from that of the other scenarios. The net energy value of SB for wet and dry seasons recorded at 62 and 38 GJ ha −1 , respectively, was the lowest due to the nutrient losses resulting from the in-field straw burning process. environmental footprint. Greenhouse gas emissions. Table 7 shows the total annual GHGE of different scenarios accounting for both indirect and direct emissions. The total values for all scenarios ranged from 6.8 to 11.2 Mg CO 2 -eq ha −1 per year. Only the GHGE value of SRt scenario was significantly different from that of the other scenarios. The GHGE value of SRt at 11.2 Mg CO 2 -eq ha −1 year −1 was the highest due to the increased direct emissions from the soil resulting from straw incorporation that caused increased methane production. The order of annual GHGE from the four straw management scenarios from highest to lowest contributor is as follows -emissions coming directly from the soil during rice cultivation (63-84%); emissions from mechanized operations (9-15%); the embedded emissions in fertilizer production (6-11%); and emissions during in-field burning (11% for SB).
Human toxicity. Rice production annually caused air pollution with a human toxicity index of 1150-1345 kg 1,4 DB-eq per ha, mainly constituting from 70-80% of fertilizer, 12-14% of pesticide, and 15% additionally caused by rice straw burning (SB scenario). The burning of straw generated pollutants such as 8-13 kg of PM 2.5 , and 4-10 kg of PM 10 . These total pollutants cause 150-200 kg of 1,4-dichlorobenzene equivalent per ha of rice production in

Discussion
This study was just conducted under the condition of irrigated rice for one variety in the Philippines. However, the result would be an important evidence for promoting of more sustainable options of rice straw management rather than burning it in the field.
The changes in soil properties identified in this study may be the result of increased cropping intensity in the experimental field. For at least 10 years prior to the current study, the cropping schedule for this field had been one rice crop per year followed by a long fallow period of 6 months. The increases in total soil C and N, available K, and CEC are likely to be the result of increasing amounts of organic matter in the soil resulting from increased frequency and amount of above and below ground biomass production in the field. These results are similar to the findings of Thammasom et al. 33 , who reported an increase in soil CEC with the addition of 6.25 Mg ha −1 of rice straw after a single rice cropping season of 111 days duration. Our results potentially demonstrate the capacity of organic matter to provide exchange sites in the soil and improve soil C stocks. However, the longevity and extent of changes in soil properties resulting from the implementation of new agronomic management practices cannot be determined in a short-term experiment. More detailed investigations of the soil over a long-term period are required to draw conclusions on the longevity and sustainability of changes in soil condition.
While the results of this short-term study do not clearly demonstrate any influence of straw management on rice yields, a number of studies have concluded that incorporation of rice straw can have a positive influence on   www.nature.com/scientificreports www.nature.com/scientificreports/ yields and soil fertility in rice production. Dobermann and Fairhurst 21 claim that straw is often the only organic matter available in significant quantities to rice farmers, and others have concluded that the incorporation of rice straw into soil can help improve the fertility of soil and lead to improved yields 34,35 . Ponnamperuma 34 demonstrated that the incorporation of rice straw resulted in an increase in the soil C and N content, and improvement in the availability of P, K and Silicon (Si) in the soil. Rice straw contains 0.5-0.8% N, 0.07-0.12% P, 1.2-1.7% K and 4-7% Sulfur (S), which are all essential nutrients for rice crop production 21 . However, other studies concluded that the incorporation of rice straw into anaerobic soils can result in the immobilization of N 36,37 , and has been attributed to rice yield decline 38 .
A study conducted by Pampolino 39 demonstrated that the removal of rice straw does not necessarily result in a decline in soil organic matter in irrigated rice under continuous flooding. However, removal of rice straw can have a negative impact on the availability of soil nutrients if not carefully managed 21 . The maintenance of soil organic carbon (SOC) with complete straw removal is only shown for double cropped irrigated rice, it is not true for systems with one rice and one upland crop. In such systems the partial removal might be the more prudent option. A nutrient balance approach can be used to account for the impacts of straw management and determine fertilizer application rates required to sustain rice yields in systems where straw is removed 40 . Our study did not attempt to optimize the application rate of fertilizers for each individual scenario, but the nutrient balance differed between the contrasting straw management practices. Overall, considering to the air pollution and nutrient loss caused from rice straw burning and high GHGE caused from incorporation of rice straw in flooded fields, we would strongly recommend to promote the option of partial removal of rice straw using for mushroom production which can generate a value -added about 50-100 $US to a ha of rice production 41 and also reduce GHGE by more than 30% compared with incorporation of all straw. In addition, spent straw after mushroom incorporation can be put back to the field to enhance soil nutrients, however on the other hand the incorporation of spent straw will increase GHGE that needs to be considered in the whole LCA.
Comparison of yield, head rice recovery, net energy, GHGE, and human toxicity of irrigated lowland rice production with different rice straw management options is shown in Fig. 3.
The total input energy of rice production in our study closely agrees with that reported in research recently conducted in the Philippines 14,15,28 . The output energy values in the current study are slightly higher than those reported by Quilty et al. 28 , which is due to the energy values attributed to N, P, and K in rice straw, and the energy associated with straw utilization once it is removed from the field.
Utilization of rice straw removed from the field can increase the net energy obtained from rice production systems by 10-15% compared to burning straw in the field which demonstrated that the energy balance can be improved through the off-field use of rice straw in mushroom and bio-energy production. Our findings are consistent with previous reports 13,26,41 and demonstrate the potential to add value to straw for farmers through off-field utility of this biomass. If off-field industries that use large volumes of rice straw can be successfully developed, then the frequency of in-field straw burning in many parts of SEA can be reduced. One aspect of off-field use of rice straw that could provide tangible solutions to reducing pollution by avoiding burning and reduce greenhouse gas emission (GHGE) is using rice straw for ethanol production as alternative fuel in place of gasoline 13 . More research is required to optimize rice production systems to ensure that the impact of straw removal from rice fields and the industries that utilize the straw are both sustainable.
Partial or complete removal of rice straw from the field reduces the GHGE by 30% and 40% compared to complete straw retention and incorporation, respectively which illustrated that removal of rice straw from the field for alternative uses has the added advantage of reducing methane emissions. Acharya 42 also demonstrated that under anaerobic conditions the incorporation of rice straw into soil resulted in increased production of methane. Annual human toxicity (Mg 1,4 DB-eq/ ha) Figure 3. Comparison yield, head rice recovery, net energy balance, GHGE, and human toxicity of a 2-season irrigated lowland rice production with different rice straw management options. In a factor (i.e. paddy yield, head rice recovery, net energy balance, GHGE, and human toxicity), the columns followed by the same letters are not significantly different by the F-test Two-Sample for Variance at 0.05 level; *There was a significant difference between the net energy balance of CSRm and SB in 2015WS but not in 2016DS.
This phenomenon means that irrigated rice production is a significant contributor to atmospheric greenhouse gases and global warming. However, the results of LCA studies investigating GHGE in rice production appear to be inconsistent, which may be due to a range of contributing factors. The total GHGE from rice production computed by Bordta et al. 16 were similar to the current study, and used similar emission factors for the production of machines and agronomic inputs. In contrast, in the LCA studies reported by Hokazono and Hayashi 43 conducted in Japan, and Blengini and Busto 14 in Italy, the GHGE was more than double the current study. The difference is mainly attributed to differences in the emission factors (EF) used. For example, the EF of CH 4 measured during direct field emission and then used for the LCA in our study is in the range of 4-22 g kg −1 of paddy. This is only 10-50% of the CH 4 EF for the same category (48 g kg −1 of paddy) used in the other studies. Similarly, research undertaken in Thailand by Thanawong et al. 15 used emission factors that were between 2 and 3 times higher than those used in our study. The carbon footprint of agricultural production, in this case greenhouse gas emissions per rice yield, can be assessed through LCA and expressed as GHG Intensity (GHGI). The trend of the GHGIs followed what was reported for overall emissions because the rice yield did not significantly differ between treatments. The SRt treatment showed a GHGI of 1.02 kg CO 2 -eq kg −1 grain yield, the SB, PSRm and CSRm treatments follow with 0.54, 0.65 and 0.64 kg CO 2 -eq kg −1 grain yield, respectively.
Open-field burning of rice straw does not emit large amounts of GHGs. However, it generated the lowest net energy balance and could be assumed to have the lowest economic profit. In addition, the burning of straw generated pollutants such as 8-13 kg of PM 2.5 , and 4-10 kg of PM 10 equaling to about 20-30 kg of 1,4-dichlorobenzene equivalent per ton of rice straw burned. To place this pollution figure in a specific context, the Human Toxic index was estimated for rice straw burning in the Mekong River Delta of Vietnam. If we assume that about 10% of the dry season crop, equal to a million tons of rice straw produced, are burned in the field over 15 days and affect a community of 10 million people, then about 90 mg 1,4db-eq per person per day is produced. This is three times higher than the risk threshold established by the EPA 31 .

conclusions
The research provided a scientific evidence for improved rice straw management. Rice cultivation with in-field burning rice straw is the worst option with lowest energy efficiency and highest air pollution emission. We demonstrated that despite the added energy requirements in straw collection and transport, the utilization of rice straw removed from the field for mushroom production can increase the net energy obtained from rice production systems by 10-15% compared to burning straw in the field. Additionally, partial or complete removal of rice straw from the field reduces the GHGE by 30% and 40% compared to complete straw retention and incorporation, respectively. Our findings were obtained from a two season experiment at a specific area in the Philippines, thus, it is difficult to extrapolate on a national scale. Additional data from other regions or long-term experiments should be gathered and more utilization options of rice straw such as for production of bio-char, compost, cattle fodder, bio-board or bio-plastic should be included in the LCA for a more comprehensive picture of the comparative environmental footprints of different straw management alternatives.

Data availability
All data generated or analyzed during this study are included in this published article (and its Supplementary Information files).


extfieldsofstudy: Medicine Chemistry

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

text:
Effects of salinity on photosynthetic traits, ion homeostasis and nitrogen metabolism in wild and cultivated soybean

Background Carbon and nitrogen metabolism need to be highly regulated to achieve cell acclimation to changing environmental conditions. The understanding of physio-biochemical responses of crops to salinity stress could help to stabilize their performance and yield. In this study we have analyzed the roles of photosynthesis, ion physiology and nitrate assimilation toward saline/alkaline stress acclimation in wild and cultivated soybean seedlings. Methods Growth and photosynthetic parameters, ion concentrations and the activity of enzymes involved in nitrogen assimilation were determined in seedlings of one wild and one cultivated soybean accession subjected to saline or alkaline stresses. Results Both saline and alkaline stresses had a negative impact on the growth and metabolism of both wild and cultivated soybean.The growth, photosynthesis, and gas exchange parameters showed a significant decrease in response to increasing salt concentration. Additionally, a significant increase in root Na+ and Cl– concentration was observed. However, photosynthetic performance and ion regulation were higher in wild than in cultivated soybean under saline and alkaline stresses. Nitrate reductase (NR) and the glutamine synthetase/glutamate synthase (GS/GOGAT) cycle showed a significant decrease in leaves of both genotypes. The reduction in the GS/GOGAT cycle was accompanied by high aminating glutamate dehydrogenase (NADH-glutamate dehydrogenase) activity, indicating the assimilation of high levels of NH4+. A significant increase in the activities of aminating and deaminating enzymes, including glutamate dehydrogenase (GDH), alanine aminotransferase (AlaAT) and aspartate aminotransferase (AspAT), was observed, probably due to the high glutamate demand and maintenance of the Krebs cycle to correct the C: N status. Conclusions Cultivated soybean was much more stress sensitive than was the wild soybean. The decrease in growth, photosynthesis, ion regulation and nitrogen assimilation enzymes was greater in cultivated soybean than in wild soybean. The impact of alkaline stress was more pronounced than that of saline stress. Wild soybean regulated the physiological mechanisms of photosynthesis and nitrate assimilation more effectively than did cultivated soybean. The present findings provide a theoretical basis with which to screen and utilize wild and cultivated soybean germplasm for breeding new stress-tolerant soybean.

physiological mechanisms of photosynthesis and nitrate assimilation more effectively than did cultivated soybean. The present findings provide a theoretical basis with which to screen and utilize wild and cultivated soybean germplasm for breeding new stresstolerant soybean.

INTRODUCTION
Soybean (Glycine max) is an important economic crop, supplying 30% of the world's edible oil and 69% of its edible protein . However, cultivated soybean is generally salt-sensitive and needs genetic improvement to make better use of alkaline and salinized soils (Wang & Li, 2011). Wild soybean (Glycine soja) is the ancestor of cultivated soybean (Duanmu et al., 2015). In comparison with cultivated species, wild soybean relatives have greater genetic diversity and greater resistance and tolerance to various biotic and abiotic stresses, respectively (Xue et al., 2014). Therefore, studies to compare the stress response in both wild and cultivated accessions are of the utmost importance, to improve abiotic stress tolerance and hence the adaptability of cultivated soybean genotypes.
Soil salinity is a global environmental problem that can severely affect plant and crop growth (Munns, 2002). The problem of salinity is increasing rapidly and it has been estimated that more than 50% of the cultivated land will be salinized by the year 2050 (Wang, Vinocur & Altman, 2003). Neutral salt stress is caused by neutral salts (such as NaCl and Na 2 SO 4 ), where as alkaline salt stress is caused by alkaline salts (including NaHCO 3 and Na 2 CO 3 ) (Shi & Sheng, 2005). Together, both salt stresses affect ∼932 million hectares of land worldwide (Rao et al., 2008). Soil salinity usually causes osmotic changes, cellular ion imbalance, photosynthetic inhibition, reduced nutrient acquisition, membrane disorganization, oxidative stress, metabolic toxicity, and membrane leakage (Munns & Tester, 2008).
In this context, plant-based solutions are needed and the analysis of traits related to salt tolerance is essential, to develop crops which survive in salt-affected soils (Ashrafi et al., 2014). Usually, plants cope with salt stress by synthesizing certain organic compatible solutes such as betaine, soluble sugars, and amino acids. These compatible solutes possess osmoprotectant properties which can help plants to survive extreme osmotic stress (Negrao, Schmockel & Tester, 2017). Therefore, studying photosynthesis and nitrate assimilation under salt stress assumes critical importance in plant stress physiology. Photosynthesis is a vital physiological process that supplies fixed carbon and chemical energy. Glucose and sucrose accumulation is an adaptive response to salt stress and plays a significant role in the normalization of plant metabolism by facilitating protein turnover and compatible solute production (Singh et al., 2015).
Salt stress usually affects the ribulose biphosphate carboxylase-oxygenase activity, photosystem II light-capturing efficiency and electron transport ability (Sivakumar, Sharmila & Saradhi, 2000;Yang et al., 2006), as well as photosynthetic gas exchange parameters in various crop plants (James et al., 2002;Lawlor & Tezara, 2009). The harmful effects of salinity are mainly associated with toxic accumulations of Na + and Cl − concentration which can inhibit the process of photosynthesis (Teakle & Tyerman, 2010). Na + accumulation appears to be more toxic for G. soja (Luo, Yu & Liu, 2005), whereas Cl − accumulation is more toxic for G. max (Chen & Yu, 2007). Salt ions also interfere with plant nitrogen assimilation (Debouba et al., 2006;Queiroz, Sodek & Haddad, 2012), by inhibiting NO 3 − reduction and NH 4 + assimilation, and affecting the activities of nitrate reductase (NR), (Debouba et al., 2006;Bybordi & Ebrahimian, 2011;Gao et al., 2013;Shao et al., 2015;Meng et al., 2016), glutamine synthetase (GS) and glutamate synthase (GOGAT) enzymes (Kwinta & Cal, 2004;Debouba et al., 2006;Wang et al., 2012;Shao et al., 2015;Meng et al., 2016;Liu & Von Wirén, 2017). In contrast, salt stress usually stimulates both the aminating and deaminating reactions of the glutamate dehydrogenase (GDH) enzyme. Deaminating glutamate dehydrogenase (NADH-GDH) can incorporate NH 4 + into glutamate and plays a crucial role in ammonium detoxification (Wang et al., 2014). Aminating glutamate dehydrogeanse (NAD-GDH) triggers the oxidation of glutamate to 2-oxoglutarate and delivers carbon skeletons under stress conditions (Liu & Von Wirén, 2017). Glutamine and glutamate are precursors for the biosynthesis of other amino acids and further nitrogenous compounds (Forde & Lea, 2007;Kusano et al., 2011). Aspertate aminotransferase (AspAT) and alanine aminotransferase (AlaAT) catalyze the reversible transfer of an amino group between glutamate and oxaloacetate/pyruvate, leading to the formation of 2-oxoglutarate and aspartate/alanine, respectively (Forde & Lea, 2007). Salt ions usually induce the activities of both the AspAT and AlaAT enzymes (Surabhi et al., 2008;Gao et al., 2013). The reversible reactions of aminotransferases convert ketoacids to amino acids and maintain the correct carbon to nitrogen ratio. It is important for plants to maintain a correct C: N ratio for adjustment and adaptation to various abiotic stresses, including salt stress (Coruzzi & Zhou, 2001). However, the adaptability of coupled carbon and nitrogen metabolism to saline/alkaline stress in soybean seedlings is unknown. Therefore, the aim of this study was (a) to analyze and compare the changes in growth, photosynthetic ability, ion accumulation and nitrogen metabolism in wild and cultivated soybeans under different saline and alkaline stresses, (b) to unravel the physiological stress tolerance mechanisms, and (c) to provide a scientific basis for the breeding of new salt-tolerant soybean varieties.

Plant materials and salt treatments
The experiment was conducted outdoors and the pots were sheltered from rain, at Northeast Normal University Changchun, Jilin, Northeast China (43 • 05 ∼45 • 15 N, 124 • 18 ∼127 • 05 E).The mean ± standard error (SE) temperature was 18.5 ± 1.5 • C at night and 26 ± 2 • C in the daytime, and the humidity was 60% ±5%. The seeds of the wild soybean genotype (W; Huinan 06116) and the cultivated soybean accession (C; Jinong 24) were provided by Jilin Province Crop Breeding Center of New Varieties. The seeds were sown in plastic pots (15 cm in diameter) with a hole in the bottom ( two cm in diameter) and filled with 2.5 kg of thoroughly washed sand. Initially, the seedlings were watered with full-strength Hoagland solution every morning. At the third compound leaf stage, thirty-five pots of uniform seedlings were selected and split into seven sets (per accession) for stress treatment: three sets of five pots each for saline stress (NaCl and Na 2 SO 4 , at a 1:1 molar ratio), three sets of five pots each for alkaline stress three (Na 2 CO 3 and NaHCO 3 , at a 1:1 molar ratio) and one set of five pots for the positive control (untreated). Both saline and alkaline stresses consisted of three concentrations (10, 20 and 30 mmol L −1 , n = 5). All solutions were prepared in 1×Hoagland solution. The stress was gradually implemented with 10 mmol L −1 of saline or alkaline stress solution for the first two days to allow the seedlings to adapt to salt stress, followed by the respective treatments, i.e., 10, 20 or 30 mmol L −1 for two weeks. The leaves of the two soybean accessions were then harvested from three randomly selected pots per treatment and immediately frozen in liquid nitrogen and stored at −80 • C for further analysis (see below).

Growth parameters
After the soybean seedlings were harvested, shoot height, root length, shoot and root fresh weight, and shoot and root dry weight were measured (Shao et al., 2016).

Gas exchange parameters
After two weeks of stress treatment, gas exchange parameters of fully expanded leaves were measured at photosynthetically active radiation (PAR) of 1,200 ± 50 µmolm −2 s −1 , using a portable open flow gas exchange system LI-6400 (LI-COR, USA) at 11:00 am. The concentration of CO 2 in the atmosphere was 380 ± 5 cm 3 m −1 . Air humidity and temperature were about 50% and 24 • C, respectively. The results for net CO 2 assimilation rate (P n ), transpiration rate (E), stomatal conductance (G s ) and ratio of sub-stomatal to atmospheric CO 2 concentration (C i /C a ) were expressed in units of µmol CO 2 m −2 s −1 , µmol H 2 O m −2 s −1 , mol m −2 s −1 , and cm 3 m −3 , respectively. The water-use efficiency parameter (WUE) was calculated as the ratio of P n /E. Measurements were carried out for each treatment from each of three replicate pots and the mean values were recorded.

Measurement of photosynthetic pigments
Dry leaf samples (0.1 g) were immersed in 80% acetone/anhydrous ethanol mixture (1:1) to extract the photosynthetic pigments completely. Photosynthetic pigments were determined using a spectrophotometer (Type UV-754; Shanghai Accurate Scientific Instrument Co., China) to measure absorbance at 440, 645 and 663 nm.

Nitrate reductase (NR) activity
NR activity was determined by the sulfamate colorimetric method (Cruz & Martins Loução, 2002). The reaction mixture, containing 200 mM KNO 3 , 5 mM EDTA, and 0.15 mM NADH in 100 mM phosphate buffer (pH 7.5) was incubated for 1 h at 30 • C. Then two mL of sulfanilamide and two mL of α-naphthylamine reagents were added and the absorbance was read at 540 nm. The enzyme activity was expressed in units of µmol g −1 protein.

Glutamine synthetase (GS) activity
GS activity was assayed according to the method of Oaks et al. (1980). The reaction mixture, which included 100 mM Tris-HCl buffer (pH 7.4), 80 mM MgSO 4 , 20 mM sodium glutamate, 20 mM cysteine, 2 mM EGTA, ATP solution (0.7 mL) and enzyme extract, was incubated for 30 min at 37 • C . Then, one mL of ferric chloride reagent (0.37 M FeCl 3 and 0.2 M trichloroacetic acid in 0.5 M HCl) was added and centrifuged at 5,000× g for 10 min at 4 • C. The absorbance was read at 540 nm and enzyme activity was expressed in units of µmol g −1 protein.

Glutamine synthase (GOGAT) activity
GOGAT activity was assayed according to the method of Rachim & Nicholas (1985). The reaction mixture contained 20 mM L-glutamine, 100 mM α-ketoglutaric acid, 10 mMKCl, and 3 mM NADH in 25 mM Tris-HCl (pH 7.6). The reaction was started by adding the enzyme extract. The NADH oxidation was monitored by continuously recording the absorbance at 340 nm. The oxidation of 1 µmol NADH per min was considered to be an enzyme unit (µmol g −1 protein).

Glutamate dehydrogenase (GDH) activities
Aminating glutamate dehydrogenase (NADH-GDH) activity was evaluated according to the method of Groat & Vance (1981). For deaminating glutamate dehydrogenase (NAD-GDH) activity, the reaction mixture consisted of 23.1 mM α-ketoglutaric acid, 231 mM NH4Cl, 30 mM CaCl2, and 6 mM NADH in 100 mM Tris-HCl buffer (pH 8.0), and the reaction was started by adding the enzyme extract. The reaction mixture for NAD-GDH consisted of 100 mM L-glutamic acid, and 1 mM NAD in 100 mM Tris-HCl buffer (pH 8.8), plus the enzyme extract. The NADH oxidation (NADH-GDH) or NAD reduction (NAD-GDH) activity was measured spectrophotometrically at 340 nm. The enzyme activity was expressed in units of µmol g-1 protein.

Aminotransferase activities
The alanine aminotransferase (AlaAT) and aspartate aminotransferase activities were measured spectrophotometrically at 340 nm in the alanine-pyruvate/aspartate-oxaloacetate directions coupled with oxidation of NADH by lactate dehydrogenase and malate dehydrogenase, respectively (De Sousa & Sodek, 2003). For AlaAT assay, the enzyme extract was mixed with a buffer solution of 500 M L-alanine, 15 mM α-oxoglutarate, 0.15 mM NADH and 5 units of lactate dehydrogenase in 100 mM Tris-HCl buffer (pH 7.5) (De Sousa & Sodek, 2003). The reaction mixture for AspAT consisted of 200 M L-aspartate, 5 mM EDTA, 12 mM 2-oxoglutarate, 0.15 mM NADH, and five units of malate dehydrogenase in 100 mM Tris-HCl buffer (pH 7.2), to which was added the enzyme extract (De Sousa & Sodek, 2003). The aminotransferases were measured using the absorption coefficient for NADH (ε = 6.22 mM −1 cm −1 ). They were expressed in units expressed in µmol g −1 protein.

Protein determination
Protein concentration was measured following the method of Bradford (1976), using bovine serum albumin as the standard.

Data analysis
All measurements were repeated three times, and the data organized in Microsoft Excel 2007. The data values are presented as mean ± standard error (SE). The data were analyzed statistically by two-way analysis of variance (ANOVA) in SPSS (v.13.0;IBM, Armonk, NY, USA) and significant differences among treatment means were detected at P < 0.05 by pairwise multiple comparisons, using Duncan's multiple range test. Sigma Plot 10.0. was used to draw the figure graphics, all of which show data points and error bars as the mean ± SE. To aid interpretation, principal component analysis (PCA) of the ionome variation analysis, photosynthetic parameters and nitrogen assimilation enzyme activities were performed for both species.

Changes in plant growth performance
The growth performances of the seedlings of the wild and cultivated soybean accessions exhibited obvious differences in response to stress treatment (Tables 1 and 2). In response to increasing concentrations of either salt treatment, the shoot and root fresh and dry weights of both soybean accessions all decreased significantly. The two stresses significantly reduced shoot and root length in both the wild and cultivated accessions (Tables 1 and  2; P < 0.05). Growth reduction was greater in the cultivated soybean accession than in the wild soybean accession, and the negative impact of alkaline stress was more obvious than that of saline stress, i.e 12.67% decrease (in 30 mmol L −1 saline stress) and 18.17% decrease (in 30 mmol L −1 alkaline stress) in the wild accession, compared with 34.96% (in 30 mmol L −1 saline stress) and 34.96% (in 30 mmol L −1 alkaline stress) in the cultivated soybean accession. Root length in the wild soybean accession increased significantly by 1.99% under 10 and 20 mmol L −1 saline stress, relative to the unstressed control (Tables 1  and 2).

Analysis of the ionome
PCA showed different responses to saline and alkaline salt stress with respect to the accumulation of ions by roots of the two soybean accessions (Figs. 1A-1D). The Na + concentration in both soybean accessions showed trends of significant increases in response to increases in the concentrations of either stress. Wild soybean roots accumulated significantly (P < 0.05) more Na + than did cultivated soybean roots, i.e., 238.77% relative to CK versus 196.90%, respectively, for 30 mmol L −1 alkaline stress and 144.00% versus 111.72%, respectively, for 30 mmol L −1 saline stress (Table 3). For both stresses, Ca 2+ , K + , Mg 2+ and P 3+ concentrations in the roots of both species showed trends of significant decreases in response to increasing stress, in comparison with the control (Table 3, P < 0.05). A more pronounced decrease in Ca 2+ , K + , Mg 2+ and P 3+ concentrations was observed in plants subjected to alkali stress (38.20, 29.96, 26.20 and 46.48%, respectively, in wild soybean and 55.53, 51.17, 42.54 and 51.50%, respectively, in cultivated soybean under 30 mmol L −1 alkaline stress), than in plants subjected to saline stress (20.29, 15.45, 15.66 and 21.03%, respectively, in wild and 38.74, 35.95, 30.20 and 41.77%, respectively, in cultivated soybean under 30 mmol L −1 saline stress). Both salt stresses significantly increased B 3+ concentration in the roots of the two accessions (Table 4, P < 0.05). The 10 and 20 mmol L −1 concentrations of both stresses exhibited similar increases in B + concentration in both soybean accessions. A more pronounced increase was observed in plants subjected to 30 mmol L −1 alkaline stress (81.55% in wild Table 1 Changes in shoot height, shoot fresh and dry weight of wild sand cultivated soybeans under control and salt stress conditions. The values are shown as mean ± SE. Different letters (A-G and a-g) mark significantly different values at P < 0.05 according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS, and H-NS represent low (10 mmol L ), medium(20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively.     soybean and 63.01% in cultivated soybean) than in plants subjected to 30 mmol L −1 saline stress (58.68% in wild soybean and 52.24% in cultivated soybean). Low saline and alkaline stress concentrations (10 mmol L −1 ) significantly increased Fe 3+ concentrations in roots of both accessions, whereas medium (20 mmol L −1 ) and high (30 mmol L −1 ) saline or alkaline concentrations significantly increased Fe 3+ concentration in wild soybean roots but significantly reduced them in cultivated soybean roots (Table 4, P < 0.05). The Zn 2+ and Mn 2+ concentrations in the roots of both soybean accessions showed significant decreasing trends in response to increasing concentrations of either salt treatment (Table 4). The root Zn 2+ and Mn 2+ concentrations of both soybean accessions showed significant decreasing trends under both salt treatments (Table 4, P < 0.05). The concentrations of Zn 2+ and Mn 2+ decreased more in plants subjected to 30 mmol L −1 alkaline stress (28.74% and 25.86% in wild soybean, respectively, and 40.86% and 50.45% in cultivated soybean, respectively) than in plants subjected to 30 mmol L −1 saline stress (29.51% and 20.98% in wild soybean, respectively, and 36.38% and 32.71% in cultivated soybean, respectively). With increasing concentrations of both stresses, the root Cu 2+ concentration increased in both soybean accessions, significantly so in the case of wild soybean, where the increase for alkali stress was significantly greater than that for saline stress (Table 4, P < 0.05).

Variety
With respect to changes in anion concentration in response to salt stress, the Cl − concentration increased significantly in salt-treated roots of both soybean accessions, with the increase in wild soybean roots being clearly greater (P < 0.05) than in cultivated soybean roots under the same level of saline stress (Table 4, P < 0.05). Similarly, the NO 3 − Table 3 Changes in Na + , Ca 2+ , K + , Mg 2+ and P 3+ contents of wild and cultivated soybean roots under control and salt stress conditions. The values are shown as mean ± SE. Different letters (A-G and a-g) mark significantly different values at P < 0.05according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS, and H-NS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively.

contents of wild and cultivated soybean roots under control and salt stress conditions.
The values are shown as mean ± SE. Different letters (A-G and a-g) mark significantly different values at P < 0.05 according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS, and H-NS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively. (0.78, 6.81 and 13.03%, relative to that of the control) under 10, 20 and 30 mmol L −1 saline stress, respectively. When subjected to alkaline stress, SO 4 2− concentration in wild soybean increased at low alkaline stress (10 mmol L −1 ) by 1.47% whereas it decreased by 0.47% and 10.25% at medium and high alkaline stress (10 and 20 mmol L −1 ), respectively (Table 4). Additionally, the C 2 O 4 2− concentration accumulated significantly in roots of both soybean accessions exposed to salt stress, with a greater increase in plants subjected to alkaline stress than to saline stress. The wild soybean accession accumulated significantly more C 2 O 4 2− than did the cultivated soybean accession under all concentrations of both stresses,with a more pronounced increase in plants subjected to 30 mmol L −1 alkaline stress (80.85% in wild soybean and 36.23% in cultivated soybean) than in plants subjected to 30 mmol L −1 saline stress (9.66% in wild soybean and 5.26% in cultivated soybean) ( Table 5) (Dataset S1 and Dataset S2).

Changes in photosynthesis parameters
PCA showed an obvious distinction between the photosynthetic capacities of the two soybean species in response to increasing salt and alkali concentrations ( Figs. 2A-2D).
Concentrations of photosynthetic pigments (Chla, Chlb, and Chl t) of both accessions showed significantly decreasing trends in response to increasing salt stress (Table 6, P < 0.05). The decrease was significantly higher in cultivated soybean than wild soybean, particularly in plants subjected to alkaline stress. Moreover, significant decreasing trends were also observed in the Car concentrations of cultivated and wild soybean under both salt and alkaline stress, respectively (Table 4, P < 0.05).The Car concentration in wild soybean did not increase significantly under saline stress. Similarly, photosynthetic gaseous exchange parameters of the two soybean accessions responded differently to the two salt stresses. The P n , G s , C i / C a and E in cultivated soybean showed significant decreasing trends in response to increasing salt stress (Table 7, P < 0.05), while water-use efficiency (WUE) did not decrease significantly under both stresses, regardless of the level of stress (Table 7). Table 6 Changes in photosynthetic pigments of wild sand cultivated soybean leaves under control and salt stress conditions. The values are shown as mean ± SE. Different letters (A-G and a-g) mark significantly different values at P < 0.05 according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS, and H-NS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively. The wild soybean accession showed significantly higher P n and G s at 10, 20 and 30 mmol L −1 saline stress, higher WUE at 10, 20 and 30 mmol L −1 saline stress and higher E at 10 mmol L −1 saline stress, relative to that of the control (Table 7, P < 0.05) (Dataset S1 and Dataset S2).

Changes in nitrogen assimilation enzyme activities
PCA and Loading plot results (Figs. 3A-3D) showed different responses of nitrogen assimilation enzyme activities exhibited by roots of the two soybean species exposed to saline/alkaline stresses. In comparison with the control, nitrate reductase (NR) activity in leaves of the cultivated soybean accession decreased significantly in response to stress by 14.02, 32.14 and 44.02% in plants subjected to 10, 20 and 30 mmol L −1 alkaline stress, respectively) and by 8.62, 19.61 and 32.15% in plants subjected to 10, 20 and 30 mmol L −1 saline stress, respectively (Fig. 4, P < 0.05). In the wild accession NR activity increased by 6.02% at 10 mmol L-1 saline stress but decreased at 20 and 30 mmol L −1 saline stress by 0.62% and 8.40%. The NR activity in the wild soybean also decreased in response to 10, 20 and 30 mmol L −1 alkaline stress, by 3.74%, 12.51% and 21.06%, respectively, compared with the unstressed control (Fig. 4).
In response to increasing concentrations of either salt treatment, glutamine synthetase/glutamine synthase (GS/GOGAT ) activities decreased significantly in leaves of both accessions (Figs. 5A, 5B; P < 0.05). The decrease was clearly greater in the cultivated soybean than in the wild soybean. The decrease in GS and GOGAT activities was more pronounced in plants subjected to 30 mmol L −1 alkali stress (33.96% and 41.18%, respectively, in the wild soybean and 48.84% and 60.87%, respectively, in the cultivated soybean) than in the corresponding plants subjected to saline stress (16.22% and 29.41%, Table 7 Changes in gas exchange parameter of wild and soybean leaves under control and salt stress conditions. The values are shown as mean ± SE. Different letters (A-G and a-g) mark significantly different values at P < 0.05 according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS, and H-NS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively.

Figure 3 Changes in NAD-GDH (A) and NADH-GDH (B) activities of wild and cultivated soybean leave under control and salt stress treatments.
Bars indicate SE of mean, n = 3 and different letters (A-G and a-g) above the columns indicate significant differences at P < 0.05 according to Duncan's method. W, wild soybean; C, cultivated soybean; CK, Control; L-NS, M-NS and H-NS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of saline salt stress, respectively; while L-AS, M-AS and H-AS represent low (10 mmol L −1 ), medium (20 mmol L −1 ) and high (30 mmol L −1 ) concentrations of alkaline salt stress, respectively. Full-size DOI: 10.7717/peerj.8191/ fig-3 fructan inhibition, accumulation of organic acids (Guo et al., 2010), root membrane disorganization, depletion of root oxygen, mineral nutrient deficiency as well as ion imbalance between root cells and the surrounding environment. Such salt-mediated effects seriously reduce plant growth and metabolism (Yang et al., 2007). The adaptation of seedlings to alkaline stress also needs more nutrients and energy than does adaptation to saline stress (Jiao et al., 2018). In the present study, growth inhibition in plants subjected to alkali salt stress was more pronounced than that of plants subjected to saline stress, probably due to the high pH induced by alkaline stress (Wang & Li, 2011). The wild soybean accession showed greater photosynthetic adaptation to saline and alkaline stresses by retaining more photosynthetic pigments than did the cultivated soybean as in consistent with previous study (Shi et al., 2015). Moreover, the salt-treated wild soybean accession exhibited higher Car concentration, which is considered to be an adaptive evolutionary trait of plants to cope with salt stress, as Car is an auxiliary pigment that can dissipate excess light energy (Duan et al., 2012). Wild soybean showed high E values at 10 mmol L −1 saline stress, high P n and G s , at 10, 20 and 30 10 mmol L −1 saline stress and high WUE at 20 and 30 mmol L −1 saline stress (relative to that of the control) as supported by our previous study (Shao et al., 2016;Jiao et al., 2018). Such photosynthetic adaptations under high salinity levels are frequently observed in halophytes in which photosynthesis remains normal or even increases under salt stress (Rabhi et al., 2012). Thus, wild soybean seems to be able to adjust the photosynthetic machinery to adapt to saline stress. It should be noted that the wild soybean accession in the current study also had a significantly higher photosynthetic rate than did the cultivated accession under normal conditions, which might have been a beneficial trait for stress acclimation.
On the other hand, the levels of E, G s , and C i /C a decreased in cultivated soybean in response to increasing concentrations of both stresses and in wild soybean under increasing concentrations of alkaline stress. Additionally, the decrease in Chlt and Car concentrations was higher in cultivated soybean than in wild soybean. These findings indicate that the decrease in photosynthetic rate was limited by both photosynthetic and stomatal factors in the cultivated accession, but by only stomatal factors in the wild soybean genotype (Zheng, Xiao & Jin, 2013). The decrease in WUE was clearly greater for cultivated soybean than for wild soybean. The salt tolerance of a plant is associated with high water-use efficiency ( Paridaa & Dasa, 2005). Thus the increased WUE in wild soybean at 10 and 20 mmol L −1 saline stress might have been beneficial with respect to stress acclimation.
The root system plays a key role in plant salt tolerance through a series of adaptative mechanisms in response to various adverse conditions (Yang et al., 2017). Na + and Cl − are extremely toxic to plants (Teakle & Tyerman, 2010). They accumulated in the roots of both soybean accessions, which might have been beneficial to stress acclimation by reducing their transport to aerial plant parts and hence protecting leaves from the salt damage, leaving the important process of photosynthesis unaffected. Their accumulation was higher in the roots of the wild soybean accession than in the cultivated soybean. Thus, wild soybean seems to better able to regulate ions to adapt to salt stress (Jiao et al., 2018). Plants usually avoid excessive Na + build-up by accumulating anions (Yang et al., 2007;Munns & Tester, 2008) rather than by synthesizing organic osmoprotectant compounds, as the synthesis of organic compounds is expensive in terms of materials and energy (Munns, 2002). High C 2 O 4 2− concentration accumulated in the roots of both soybean species in response to stress, with greater accumulation occurring in plants subjected to alkaline stress, and this might have been one of the reasons for the marked decrease in growth of both soybean accessions (Yang et al., 2007). The wild soybean accumulated C 2 O 4 2− markedly under alkaline stress as consistent to previous study (Yang et al., 2007) as well as showing better maintenance of inorganic ions under both stresses. These might have been adaptative strategies beneficial to stress acclimation by minimizing and alleviating ion toxicity (Jiao et al., 2018). For both stresses, the NO 3 − and Cl − content in roots of both soybean accessions showed antagonistic interactions as consistent with previous studies (Abdelgadir, Oka & Fujiyama, 2005). The decrease in NO 3 − uptake might have decreased nitrogen assimilation and the synthesis of amino acids and proteins, resulting in a greater reduction in dry weight of both soybean accessions, relative to that of the control (Queiroz, Sodek & Haddad, 2012). Moreover, both salt stresses greatly reduced the activities of enzymes of leaf nitrogen assimilation in both soybean species. The nitrate reductase (NR) activity in leaves of cultivated soybean decreased with increasing concentrations of both stresses, but only under alkaline stress for the wild soybean, with the corresponding reductions being greater in cultivated than in wild soybean. Thus, decreased NR activity seems to be the result of decreased NO 3 − absorption rather than the direct effect of salt stresses (Abdelgadir, Oka & Fujiyama, 2005;Meng et al., 2016). Our findings support those reported from other studies (Bybordi & Ebrahimian, 2011;Shao et al., 2015;Meng et al., 2016).
The glutamine synthetase/glutamine synthase (GS/GOGAT) cycle links plant nitrogen and carbon assimilation by binding inorganic nitrogen (NH 4 + ) to the carbon skeleton, a step necessary for plant growth and development (Forde & Lea, 2007). In response to either stress, GS/GOGAT activities decreased significantly in leaves of both soybean accessions, which indicates their inability to incorporate NH 4 + properly, to fill the glutamate pool necessary for proline biosynthesis (Wang et al., 2007). Previous studies had shown that the toxic Na + and Cl − accumulation in rice plants subjected to salt stress damaged the chloroplasts and photorespiration, resulting in decreased GS/GOGAT activities (Meng et al., 2016).
GS/GOGAT activities were higher in leaves of the wild soybean accession following exposure to stress.Thus, the wild soybean seems to have synthesized more nitrogencontaining compounds than has the cultivated soybean, an adaptation which might have been beneficial to stress acclimation (Lancien, Gadal & Hodges, 2000). The salt-induced reductionin the GS/GOGAT cycle was previously reported for different crop plants (Sahu, Sahoo & Sahoo, 2001;Wang et al., 2007;Shao et al., 2015;Meng et al., 2016). Moreover, the high aminating glutamate dehydrogenase (NADH-GDH) activity in leaves of both soybean species has accompanied the reduced GS/GOGAT cycle by incorporating NH 4 + directly onto glutamate (Wang et al., 2007;Wang et al., 2014). Glutamate is a key intermediate of nitrogen metabolism and a substrate for the synthesis of amino acids, nucleotides, glutathione and chlorophyll (Forde & Lea, 2007;Martinez-Andujar et al., 2013). The affinity of NADH-GDH for NH 4 + is usually very low, compared with the GS enzyme (Wang et al., 2007), so that the increased NADH-GDH activity in stressed plants reflects the presence of high concentrations of NH 4 + in both soybean accessions following stress exposure. Moreover, it can also be concluded that the GS/GOGAT cycle might have been inhibited due to the damaging effect of salt stress rather than to substrate limitation. The accumulation of NH 4 + ions reflects reduced nitrogen assimilation and decreased plant growth (Wang et al., 2007).The salt-induced increase in NADH-GDH activity was previously reported from different crop plants (Kwinta & Cal, 2004;Wang et al., 2007;Gao et al., 2013;Naliwajski & Skłodowska, 2018).
The deamination of glutamate to 2-oxoglutarate and NH 4 + ions is very important under stress conditions (Bechtold, Pahlich & Lea, 1998). The high deaminating glutamate dehydrogenase (NAD-GDH) activity in both soybean accessions might be a source of 2-oxoglutarate and NH 4 + ions. The high NAD-GDH activity testified to its roles in the catabolism of carbohydrates, through the supply of 2-oxoglutarate for the Krebs cycle as well as that of reduction force in the shape of NAD(P)H, necessary for many metabolic processes (El-Shora & Abo-Kassem, 2001;Kwinta & Cal, 2004;Liu & Von Wirén, 2017). The increased NAD-GDH activity might play an important role in replenishing the reduced carbon pool in both soybean accessions (Naliwajski & Skłodowska, 2018). Both aminating and deaminating activities of GDH were higher in leaves of wild soybean, relative to that of the cultivated soybean, on exposure to stress. Thus, wild soybean seems to have developed a strong compensatory mechanism of delivering carbon sources and incorporating NH 4 + to avoid a shortage of amino acids necessary for osmotic adjustments of the cell. High alanine aminotransferase (AlaAT) activity in both soybean accessions reflects the disturbed Krebs cycle and activation of the reversible reaction of pyruvate and glutamate to alanine and 2-oxoglutarate.Therefore, this effect seems to have facilitated ATP production Van Dongen et al., (2011). The transamination of aspartate to oxaloacetate by the aspertate aminotransferase (AspAT) enzyme is an important physiological anaplerotic reaction of the Krebs cycle (Van Dongen et al.,, 2011). The increased activities of AlaAT, AspAT, and NADH-GDH enzymes in both soybean accessions might have been attributed to the high glutamate demand and maintenance of Krebs cycle to achieve correction of the carbon:nitrogen ratio under stress conditions (Forde & Lea, 2007;Naliwajski & Skłodowska, 2018). Increased AlaAT and AspAT activities under salt stress have previously been reported for different crop plants (Surabhi et al., 2008;Gao et al., 2013;Naliwajski & Skłodowska, 2018).

CONCLUSIONS
Both saline and alkaline stresses had negative impact on the growth and metabolism of the wild and cultivated soybean species, as indicated by decreased growth and photosynthetic parameters, ion regulation and decreased activity of enzymes involved in nitrogen assimilation, with greater decreases in plants subjected to alkaline stress than in plants subjected to saline stress. The aminating glutamate dehydrogenase (NADH-GDH) played a complementary role in NH 4 + assimilation of both soybean accession in response to stress. Moreover, increased activities of alanine aminotransferase (AlaAT), aspertate aminotransferase (AspAT), and NADH-GDH in stressed plants reflect the high glutamate demand and maintenance of the Krebs cycle for the correction of the carbon: nitrogen ratio in both soybean accessions. The activities of these enzymes were higher in wild soybean than in cultivated soybean in response to increasing concentrations of both stresses. In the presence of salt stress, the wild soybean better regulated the physiological mechanism of photosynthesis and nitrate assimilation than did the cultivated soybean. The present study provides a theoretical basis to screen and utilize wild soybeans for the breeding of new stress-tolerant soybean varieties.


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Evaluation of Sterilant Effect on In-vitro Culture Establishment in Sugarcane Variety Co 0118

Sugarcane is an economically important cash crop and used as one of the principal sources of sugar, ethanol, and jaggery in Indian subcontinent (Gallo-Meagher et al., 2000). It is widely grown crop in tropical and subtropical regions of the world contributing about 70% of the world sugar production (Chatenet et al., 2001). Worldwide, sugarcane is cultivated over 110 countries with an area of 25.98 million ha, and production of 1841.52 million metric tonnes. India is the second largest producer of sugarcane occupies 4.39 International Journal of Current Microbiology and Applied Sciences ISSN: 2319-7706 Volume 8 Number 07 (2019) Journal homepage: http://www.ijcmas.com

Introduction
Sugarcane is an economically important cash crop and used as one of the principal sources of sugar, ethanol, and jaggery in Indian subcontinent (Gallo-Meagher et al., 2000). It is widely grown crop in tropical and subtropical regions of the world contributing about 70% of the world sugar production (Chatenet et al., 2001). Worldwide, sugarcane is cultivated over 110 countries with an area of 25.98 million ha, and production of 1841.52 million metric tonnes. India is the second largest producer of sugarcane occupies 4.39 million ha area with the production of 306.07 million tonnes (FAOSTAT, 2017). The usefulness of this crop makes it unique for intensive and extensive field plantation.
Generally, sugarcane is propagated through multiple cuttings of stalks. The vegetative cultivation practices are results in low multiplication rate and facilitate the source of survival for many pathogens in sugarcane setts (Schenck and Lehrer, 2000;Sengar et al., 2011). Sugarcane production is negatively affected by diseases mainly due to its vegetative propagation. Now days, in-vitro propagation through tissue culture has been established as an efficient and reliable strategy. Tissue culture not only reduces the time of multiplication but also produce trueto-type plants and can be used an alternative for rapid propagation of sugarcane (Jalaja, 2008;Sengar et al., 2012). Thus, propagation procedure of sugarcane through tissue culture should be developed in more advanced and efficient to get higher establishment.
The plants brought from the field in laboratory have high number of contaminations on their surface. These contaminants have a negative effect on explants survival and compete with in-vitro plantlets for nutrition if the proper treatment not given for their removal. Microbial contaminations reduce the mortality of in-vitro cultures and cause necrosis. The explants propagation without using any sterilant results in very less culture survival sometimes no culture survival. The prevalence of contamination makes culture establishment vulnerable in achieving goal. In successfulness of in-vitro culture establishment primary consideration given to explants selection and secondary to the suitable sterilizing agents. The chemical agent selection should of be the type that could remove contamination properly (Panhwar, 2005), and ensure higher survival rate after treatment. Development of aseptic culture protocol is a critical step to avoid the invasion and growth of contaminants. However, many protocols had been established for in-vitro propagation of sugarcane varieties (George and Tripepi, 2001;Sawant and Tawar, 2011;Ghatge et al., 2014;Belete andKalu, 2015: Thorat et al., 2016) but looking for better optimization of sterilant combination is mandatory to achieve sustainable micropropagation. Thus present study was conducted to optimize surface sterilization for in-vitro establishment of sugarcane through meristem tip culture.

Experimental plants and protocol
The present investigation was conducted at Tissue culture laboratory, Department of Agricultural Biotechnology, College of Agriculture, SVPUA&T, Meerut. The explants were collected from nine month old sugarcane plants Co 0118 in the form of upper tops from ShriRam Sugarcane Research Farm, Modipuram, Meerut, UP, India. MS (Murashige and Skoog) basal medium was prepared by supplementing 3% sucrose, 300mg/L PVP, 100 mg/L myo-inositol, agar (8g/L) as solidifying agent along with 0.5 mg/L each of BAP and Kn and pH adjusted to 5.8, autoclaved at 121°C and 15 lbs (101kpa) for 20 minutes before 3 days of inoculation. The autoclaved media was poured into presterilized culture tubes (150×25 mm). After 3 days media was screened to check any contamination.

Explant sterilization and sterilants
The collected sugarcane tops were excised into 6-8 cm long spindles containing apical meristem shoot tip and thoroughly washed under running tap water for 30 min. Initially these segments were treated with Lavolene (5% Calcium Hypochlorite) for 10 min and rinsed with water to remove any traces of detergent. Then these segments were dipped into 0.1% Polyvinyl pyrilidone (PVP) solution and further surface sterilization treatments were given under laminar air flow hood. The explants were treated with various concentrations and combination of sterilants viz. Bavistin TM (0.01, 0.05, 0.1, 0.2 and 04%), Mercuric chloride (0.01, 0.05, 0.1, 0.2 and 0.4%), Sodium hypochlorite (2, 4, 6, 8 and 10%) and Ethanol (60, 70, 80, 90 and 100%) to optimize minimum contamination, explant survival and culture establishment ( Table 1). The explants were washed three times with autoclaved de-ionized water after each treatment. The explants were prepared by carefully removing upper extended outer leaf sheaths and excised without disturbing upper meristematic shoot bud using scalpel blade in 1.5-2.0 cm. The prepared explants were immediately inoculated on semisolid MS medium containing 0.5 mg/L of each BAP and Kn and incubated in culture room under white fluorescent light intensity of 4000 lux, 16 h of light and 8 h of dark photoperiod, 50-60% RH and 25±2ºC temperature. The cultures were observed on regular interval of 3 days for contamination for four weeks and data was collected for contaminated, survived cultures.
Culture survival percent was calculated as per the formula:

Statistical analysis
The data was analyzed using SPSS (computer software package version 20.0) and one way ANOVA was applied to test mean differences among all treatments followed by Tukey's-b multiple range test and represented as mean±SE. The value p≤0.05 was considered statistically significant in each case.

Results and Discussion
In-vitro culture establishment is primarily dependant of sterilization procedures. The explants collected from field contain many microbes on their surface because plant faces every type of situation in field condition. The culture medium used in the tissue culture is most suitable for microbial growth thus, surface sterilization of collected explants is necessary. Under present study, various concentrations of sterilants and their combination had been optimized for higher culture survival and establishment (Table 1).
Bavistin, a fungicide widely used as sterilant in plant tissue culture studies (Altan et al., 2010;Khatun et al., 2016) has been used under study in different concentrations for 10 min for explants surface sterilization. Analysis of variance indicates culture survival percent range from 26.8 to 55.4% (Table 1 and Fig. 1).
A significantly (p<0.05) higher culture survival percent (55.4%) and healthy uniform shoots growth as compared to other Bavistin treatments was observed in explants treated with 0.1% Bavistin. However, the culture survival percent did not differ significantly (p>0.05) in explants treated with 0.05 and 0.1% Bavistin. A significantly (p<0.05) lesser survival percent was to be noted in explants treated with 0.01% Bavistin and significantly (p<0.05) lesser contamination was recorded to be 0.2 % treated explants but shoot induction was found to be impaired.
Mercuric Chloride (HgCl 2), a corrosive chemical compound used as disinfectant and had been reported as sterilant in plant tissue culture studies by many researchers (Preethi et al., 2011;Anburaj et al., 2011).  Fig. 1). The explants treated with 0.1% HgCl 2 for 5 min showed a significant (p<0.05) increase in culture survival percent (73.2%) with healthy and uniform shoot growth in comparison to other treatments. Similar findings were reported by Sawant and Tawar (2011). Babaei et al., (2013) and Tiwari et al., (2012) also reported the 0.1% HgCl 2 for 5 min as effective treatment for explant surface sterilization with minimum tissue necrosis. However, explants treated with 0.05% HgCl 2 also showed higher culture survival as compared to other HgCl 2 treatments but a microbial growth after one week was observed. The significantly (p>0.05) lesser culture survival percent sometimes no shoot induction was obtained in explants treated with 0.4% HgCl 2 . Increase in HgCl 2 % found to be resulted in deleterious effect on explants survival, explants turned into brownish black and failed to proliferate during incubation as a result of tissue necrosis. It may me the results of bleaching action of two chloride atoms and ions that combine strongly with proteins and cause necrosis to plant tissues. The findings of this study are in agreement with earlier researcher reports of Johnson et al., (2011) andWesely et al., (2011).
Sodium hypochlorite (NaOCl) is a compound effectively used for water purification as disinfectants also used in various concentrations to show the effect on explant sterilization. The culture survival was found to be ranged from 32.6 to 65.6% (Table 1 and Fig. 1) under studied concentrations of NaOCl. The explants treated with 6% NaOCl for 10 min showed a significantly (p<0.05) higher culture survival percent (66%) and uniform shoot growth as compared to other NaOCl treatments. However, culture survival percent was significantly (p>0.05) in explants treated with 4 and 6% NaOCl. A significant (p<0.05) lesser culture survival percent was shown to be in explants treated with 2% NaOCl. A significant (p<0.05) increase in culture survival percent was shown with increasing NaOCl concentration but shoot growth was non-uniform. Similar findings also reported by Reda et al., (2004) and suggested sodium hypochlorite as an effective surface sterilant for sterilization. Wlodkowski and Rosenkranz (1975) and Danso et al., (2011) reported NaOCl diluted with water lead to formation of HClO and resulted in lethal DNA damage (Dukan et al., 1999).
Ethanol is used as strong phytotoxic sterilizing agent. Earlier researchers also reported that alcohols have higher bactericidal activity as compared to other bacteriostatic agents against bacterial vegetative cells but do not destroy spore cells (Bloomfield, 1978). In present study, various concentration of ethanol had been used to determine its effectiveness on explant sterilization that found to be ranged from 33 to 51.6% (Table 1 and Fig. 1). The explants treated with 70% ethanol for 1min showed a significantly (p<0.05) higher survival percent (51.6%) with healthy and uniform shoot growth as compared to other EtOH treatments but shoot induction was slower. However, minimum culture survival percent and non-uniform shoot growth was to be noted in explants treated with 100% of Ethanol.
A significantly (p<0.05) higher culture survival percent (85.4%) with vigorous shoot growth as compared to other treatments was observed in explants treated with a combination of 0.1% Bavistin for 10 min followed by 0.1% HgCl 2 for 5 min, 6% NaOCl for 10 min and 70% EtOH for 1 min with subsequent three washing of de-ionized water after each treatment (Table 1 and Fig.  1). The regenerated shoots were healthy and green coloured and aseptic tissue growth was observed and media was apparent clear with no turbidity. However, treatment with single sterilant resulted in good shoot proliferation but subsequently failed to control microbial contamination in second week (Fig. 2). No survival was observed in explants inoculated without any sterilant treatment. The results under study also indicate that contamination percent was reduced when explants were treated with either of 0.2% Bavistin, 0.2% HgCl 2 or 8% NaOCl alone but at the same time there was adverse effect on tissue growth was to be seen due to increased necrosis leading to failure of shoot induction. The Variations in shoot induction and proliferation was the result of sterilant impact and damage to the explants during treatment.
In present study, each sterilant differed in its activity on explants surface sterilization that suggest sterilization process differs with tissue and type of explant. The sterilants combination used under study was found to me more effective for meristem shoot tip explants sterilization and culture establishment in sugarcane variety Co 0118.