Tillage and Weed Management Effect on Weeds, Non Target Toxicity ...

International Journal of Farming and Allied Sciences Available online at www.ijfas.com ©2014 IJFAS Journal-2014-3-9/962-969/ 30 September, 2014 ISSN 2322-4134 ©2014 IJFAS

Tillage and Weed Management Effect on Weeds, Non Target Toxicity in Soil and Yield of Soybean Masoumeh Younesabadi1*, TK Das1 and Sangeeta Paul2 1. Division of Agronomy, Indian Agricultural Research Institute, New Delhi 2. Division of Microbiology, Indian Agricultural Research Institute, New Delhi Corresponding author: Masoumeh Younesabadi ABSTRACT: In a field experiment conducted during rainy season 2010 and 2011, at Indian, Agricultural Research Institute, New Delhi, the effect of tillage and weed control measures was investigated on weeds, soil non-target toxicity and soybean growth and yield. The experiment was laid out in split plot design with three replications. The treatments comprised of conventional tillage (CT) and no-tillage (NT) as main plots, and 8 levels of weed control measures as sub-plots. Yearly as well as pooled density of grass, broadleaved and sedge weed density, and dry weight of broad-leaved and sedge was mostly significantly lower in no-tillage compared to conventional tillage, but reverse was true for grass dry weight. Soybean yield was not affected by tillage treatments, but all weed control treatments gave significantly higher soybean seed yield compared to weedy check. Pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha were comparable and weed-free check was superior to all other weed control treatments in this regard. Populations of fungi, bacteria and actinomycetes, and soil dehydrogenase activity (DH) and microbial biomass carbon (MBC) were significantly higher in no-tillage treatment in both years. Weedy check and weed-free check were comparable to each other, followed by pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha and pendimethalin 0.75kg/ha alone showed the highest value of these parameters. Keywords: Actinomycetes, Bacteria, Dehydrogenase activity, Fungi, Microbial biomass carbon, Soybean, Weed, Yield INTRODUCTION Environmental risk assessment of pesticides is a major challenge arising from the intensive production and use of numerous substances considered as potential pollutants. This is particularly the case for herbicides, which are used in large amounts in agricultural, urban and domestic applications (Bonnet, 2007). Bunce (1993) wrote “It is useful to keep in mind the concept that a pollutant is a substance in the wrong place, at the wrong time, or in the wrong amount”. While herbicides are very important to agriculture, under certain circumstances they may act as pollutants that can deteriorate soils, ground and surface waters (Zabaloy, 2011). Therefore, we need to use them judiciously, preferably at lower dose by mixing one or two compatible herbicides which augment the herbicidal activity of both the partner herbicides. Stable and sustainable soils are defined as those with high level of biological activity, high microbial diversity, and capability to release nutrients from soil organic matter (Smith, 1990; Friedel and Gabel, 2001; Friedel .1996). Since microbes play a critical role in carbon (C) and nutrient transformations, any change in their populations and activities may affect cycling of nutrients as well as availability of nutrients, thus, indirectly affecting plant growth and other soil functions (Wang, 2009). An accurate and consistent evaluation of soil quality may be accomplished by indicators such as microbial biomass (Santos, 2006). Differences in soil microbial biomass and activity can directly affect crop nutrient availability. Thus, soil MBC is an effective indicator to predict overall fertility and productivity of a cropping system (Nair, 2012). Since, dehydrogenase activity (DH) is present only in viable cells, it is thought to reflect the total range of oxidative activity of soil micro-flora, and consequently may be

Intl J Farm & Alli Sci. Vol., 3 (9): 962-969, 2014

considered to be a good indicator of microbial activity too (Nannipieri, 2003and Nannipieri, 1990). Therefore, this study has focused on potential impact of herbicide tank-mixes on weed control, growth and yield of soybean as well as soil non-target toxicity under tillage and no-tillage conditions. MATERIALS AND METHODS Field Experiment A field experiment was conducted during rainy season (Kharif) 2010 and 2011 to evaluate the tillage and weed management effect on weeds, soybean growth and yield, and soil microbial activity and microorganism populations at Division of Agronomy, Indian, Agricultural Research Institute, New Delhi. Soybean ‘Pusa 9712’ was sown in a sandy loam soil with pH 7.6, with a seed rate 75 kg/ha in row spaced at 40 cm. The experiment was laid out in split plot design with three replications. The experiment comprised of two levels of tillage in main plots, and 8 levels of weed control measures as sub-plots (treatments mentioned in Tables 1-5). Population and dry weight of weeds were recorded at 30 DAS by placing a quadrat of 50×50 cm randomly in each plot. Soybean leaf area index (LAI) was determined using Licor-3100 leaf area meter 30 DAS. Data on seed yield were recorded from the net plot and plant height from five randomly selected plants at harvest. Observation on Soil Micro-Flora At 30 DAS, 4 to 5 soil cores from the top soil (0-15 cm depth) were collected from each plot. The soil samples were air-dried and sieved through a 2.0 mm width mesh. Quantitative estimation of fungi, bacteria and actinomycetes per gram of soil were made by serial dilution and agar/pour plate techniques described by Parkinson . (1971). Nutrient agar medium (Allen, 1953) for bacteria, Martin Rose Bengal agar medium (Martin,1950) for fungi, and Ken Knight’s medium (Subba Rao,1977) for actionmycetes were used. After spreading the soil solution on respective plates, the dishes were incubated at 25±10C for fungi and 30±10C for bacteria and actinomycetes. The microbial colonies were counted after 2, 5 and 7 days of incubation for bacteria, actinomycetes and fungi, respectively. DH-activity was determined as per Casida . (1964). Microbial biomass carbon (MBC) was analyzed following chloroform fumigation extraction method as described by Jenkinson and Ladd (1981) and Paul . (2009). Statistical Analysis Data generated from the study were subjected to analysis of variance (ANOVA) using the PROC GLM procedure of SAS (SAS Institute, 2003). Weed population and dry weight data were subjected to square-root(√𝑥 + 0.5 ) transformation before analysis of variance. Dependent variable means that were significantly influenced by main and sub-treatments and interactions were compared using LSD test at 5% probability. RESULTS AND DISCUSSION Weed Growth A perusal of data noted that no-tillage (NT) was superior to conventional tillage (CT) for reduction of grass, broadleaved and sedge density and dry weight of broad-leaved and sedge (Table 1& 2; Figures 1 & 2). Norsworthy and Oliveira (2007) had similar observations in which, no-tilled soybean resulted in reduction of common cocklebur emergence by 59 to 69% compared with tillage. Anderson (2009) also observed that NT was superior to CT on the reduction of weed infestation and soybean yield loss. The lowest grass density and dry matter belonged to weedfree check followed by pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha in both years. However this trend was observed on broad-leaved weeds in 2010 as well as pooled data, but broad-leaved density and dry weight was lowest in metribuzin 0.3 kg/ha + chlorimuron 0.009 kg/ha in 2011. Pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha was the best treatment for weed control in both years. Better efficacy of pendimethalin followed by post application of imazethapyr has been already reported by Taylor-Lovell . (2002). This trend was also observed on broad-leaved density and dry weight in 2010 as well as pooled data but not in 2011 where broad-leaved density and dry weight was lowest in metribuzin 0.3 kg/ha + chlorimuron 0.009 kg/ha. This is in conformity with Tuti and Das (2011). Metribuzin 0.3 kg/ha + imazethapyr 0.075 kg/ha had the lowest sedge density in both years. Tuti and Das (2011) also showed that Cyperus rotundus was not controlled by any herbicide except metribuzin 0.5 kg/ha pre-emergence. In this study, sedge density was higher in some treatments than weedy check. Higher grass and broad-leaved pressure in weedy check may be a reason for reduction of sedges growth and germination. Higher sedges density in another treatment might have accrued from greater control of grass and broad-leaved weeds. A herbicide efficacy depend on chemical nature, dose and time of application of herbicides, weed species, their age and tolerance as

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well as soil and climate condition (Das, 2008). As expected tank-mix application of pendimethalin and metribuzin with imazethapyr and chlorimuron showed a lot of difference in their performance on weed categories. Metribuzin treatments were more successful in sedges and broad-leaved weeds control but pendimethalin treatment were better in grass weeds control, however, pendimethalin + imazethapayr was the best treatment in control of broad-leaved as well as grass weeds. Total weed density particularly sedge density was slightly lower in second year that may be contributed to less rainfall in second year, however reverse was true for weed dry weight. Weed's tolerance to many adverse weather and soil condition make them superior to crop plants under stressed situation. Competition for rainfall/water is critical under rainfed or semi-arid/arid environment, while the same becomes negligible or mitigated by irrigation in irrigated or humid situation (Das, 2008). So, higher weed dry weight in second year in this experiment may be related to intensity/amount, duration and frequency of rainfall. Table 1. Grass and broad-leaved weed density as influenced by tillage and herbicide application Treatment

Grass density(no.m2) 30 DAS 2010 2011 _ _

pooled 4.9(33.1)

Sedge density(no.m2) 30 DAS 2010 2011 _ _

_

_

4.08(28.8)

_

_

_

_

0.08(1.1)

_

_

_

_

_

_

7.95(106.0 ) 0.08(3.18)

LSD(P=0.05) Conventional tillage(CT) NoTillage(NT) SEm ±

_ 8.4(122.7)*

_ 9.0(134.3)

NS 8.7(128.5)

_ 6.4(52.3)

_ 5.5(39.4)

NS 6.0(45.9)

_ 7.8(69.8)

_ 3.7(19.4)

pooled 7.01(58.0 ) 3.07(14.2 ) 0.07(1.72 ) 0.4(10.4) 5.8(44.6)

7.8(71.5)

6.9(77.6)

7.4(74.6)

3.3(13.8)

2.7(18.2)

3.0(16.0)

6.2(47.2)

2.4(9.1)

4.3(27.6)

0.1(3.2)

0.05(3.1)

0.2(2.2)

0.04(0.5)

0.08(1.1)

0.02(0.4)

0.07(0.8)

0.04(0.5)

LSD(P=0.05) Pendimethali n 0.75 kg/ha Pendimethali n 0.5 kg/ha+ imazethapyr 0.075 kg/ha Pendimethali n 0.5 kg/ha + chlorimuronp-ethyl 0.009 kg/ha Metribuzin 0.3 kg/ha + imazethapyr 0.075 kg/ha Metribuzin 0.3 kg/ha + chlorimuronp-ethyl 0.009 kg/ha Pendimethali n 0.75 kg/ha +hand weeding at 30 DAS Weedy check

0.7(19.3) 7.6(58.0)

0.3(18.6) 6.9(47.3)

0.06(2.241 ) 0.2(8.6) 7.2(52.7)

0.9(13.2) 5.9(36.7)

0.3(3.0) 5.2(32.7)

0.3(4.4) 5.6(34.7)

0.4(5.1) 7.5(58.7)

0.2(1.9) 8.9(83.7)

3.4(18.7)

3.1(9.3)

3.2(14.0)

2.6(7.3)

2.4(7.3)

2.5(7.3)

0.1(2.6) 10.3(108.7 ) 7.1(50.7)

2.7(10.7)

4.9(30.7)

5.6(35.3)

7.7(60.3)

6.7(47.8)

4.9(28.0)

3.8(16.0)

4.3(22.0)

8.3(68.0)

2.8(8.3)

5.5(38.2)

11.0(130.0 )

8.2(71.5)

9.6(100.8)

4.9(28.7)

2.5(9.3)

3.7(19.0)

5.7(34.7)

2.1(4.7)

3.9(19.7)

12.2(150.0 )

7.2(57.3)

9.7(103. 7)

4.6(27.3)

1.9(4.7)

3.7(16.0)

8.0(67.3)

2.4(5.7)

5.2(36.5)

7.0(52.7)

6.2(38.5)

6.6(45.6)

5.8(35.8)

4.5(25.5)

5.2(30.7)

8.9(80.7)

4.8(22.7)

6.8(51.7)

17.5(332.0 ) 0.7(0.0)

23.5(563.3 ) 0.7(0.0)

20.5(444.7 ) 0.7(0.0)

9.5(100.7 ) 0.7(0.0)

11.6(134.8 ) 0.7(0.0)

10.6(117.8 ) 0.7(0.0)

7.3(54.0)

1.7(3.3)

4.5(28.7)

0.7(0.0)

0.7(0.0)

0.7(0.0)

0.35(6.75)

0.24(9.48)

0.21(6.03)

0.17(1.94)

0.21(1.84)

0.28(4.81)

1.0(19.5)

0.7(27.4)

0.6(17.0)

0.42(3.08 ) 1.2(8.9)

0.5(5.6)

0.6(5.2)

0.8(13.9)

0.17(1.49 ) 0.5(4.3)

0.18(2.52 ) 0.5(7.1)

First year (2010) Second year (2011) SEm ±

Weed-free check SEm ± CD(P=0.05)

*Data were transformed through square root (

pooled 8.11(97.1)

Dicot density(no.m2) 30 DAS 2010 2011 _ _

) method, figure in the parentheses are original value.

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Intl J Farm & Alli Sci. Vol., 3 (9): 962-969, 2014 Table 2. Grass and broad-leaved weed and sedge dry weight as influenced by tillage and herbicide application Treatment

First year (2010) Second year (2011) SEm ± LSD(P=0. 05) Conventio nal tillage(CT ) NoTillage(N T) SEm ± LSD(P=0. 05) Pendimet halin 0.75 kg/ha Pendimet halin 0.5 kg/ha+ imazetha pyr 0.075 kg/ha Pendimet halin 0.5 kg/ha + chlorimur on-p-ethyl 0.009 kg/ha Metribuzi n 0.3 kg/ha + imazetha pyr 0.075 kg/ha Metribuzi n 0.3 kg/ha + chlorimur on-p-ethyl 0.009 kg/ha Pendimet halin 0.75 kg/ha +hand weeding at 30 DAS Weedy check Weedfree check SEm ± CD(P=0.0 5)

Dry weight of grass (g/m2) (30DAS) 2010 2011 _ _

pooled 7.02(70.26)

Dry weight of dicot (g/m2) (30DAS) 2010 2011 _ _

_

_

8.38(109.1 1)

_

_

_ _

_ _

0.5(10.4) NS

_ _

_ _

4.91(36.11) *

6.99 (85.97)

5.95(61.04)

3.41(18.0 3)

5.29(41.68)

9.14(104.4 2)

9.79(132.2 4)

9.45(118.3 3)

1.74(5.35)

0.16(3.30) 0.96(20.03)

1.02(23.32) NS

0.52(11.80) 2.01(46.07)

7.59(75.40)

8.75(106.0 2)

4.33(31.60)

pooled 2.57(11.6 9) 4.27(30.7 5)

Dry weight of sedge (g/m2) (30DAS) 2010 2011 pooled _ _ 3.25(16.1 9) _ _ 4.07(25.5 1)

0.2(1.9) 1.05(11.5 8) 4.35(29.8 6)

_ _

_ _

0.2(2.07) NS

4.53(27.6 9)

5.81(42.4)

5.17(35.0 5)

3.24(19.82)

2.49(12.5 0)

1.96(4.69)

2.32(8.62)

2.14(6.66)

0.09(0.78) 0.52(4.73)

0.05(2.89) 0.32(17.51)

0.05(1.50) 0.2(5.85)

2.74(11.4 0)

7.32(56.07)

5.03(33.7 3)

0.29(3.26) 1.77(19.7 5) 7.05(57.8 5)

0.16(1.90) 0.64(7.43)

8.16(90.71)

3.05(1.95) 0.87(11.8 3) 6.22(45.2 7)

4.92(59.43)

4.6345.51)

0.71(0.00)

3.90(17.73)

2.31(8.87)

3.27(12.0 7)

4.77(29.6 4)

4.02(20.8 5)

7.94(68.67)

7.74(64.25)

7.84(66.46)

2.77(8.70)

2.49(7.90)

2.63(8.30)

2.55(9.47)

3.40(18.3 5)

2.97(13.9 1)

6.10(45.2)0

9.92(116.8 2)

8.00(81.01)

1.70(3.47)

1.47(2.83)

1.38(3.15)

2.39(5.53)

4.26(22.2 5)

3.33(13.8 9)

8.95( 90.13)

7.09(51.67)

8.02(70.90)

2.14(5.23)

0.87(0.37)

1.5(2.80)

3.05(9.20)

2.92(10.3 2)

2.98(9.76)

7.56( 75.12)

8.67(103.7 4)

8.12(89.43)

2.73(11.0 3)

7.36(56.37)

5.05(33.7 0)

6.24(45.3 3)

7.02(57.1 6)

6.63(51.2 5)

13.03(176. 0) 0.71( 0.0)

19.22(370. 9) 0.71(0.0)

16.13(273. 5) 0.71(0.0)

7.10(53.7)

8.57(79.2)

1.55(2.7)

2.41(8.5)

1.98(5.6)

0.71(0.0)

10.04(104. 7) 0.71(0.0)

0.71(0.0)

0.71(0.0)

0.71(0.0)

0.71(0.0)

0.5(10.3) 1.33(30.03)

1.0(20.5) 2.77(59.36)

0.5(11.5) 1.50(32.53)

0.2(1.5) 0.49(4.40)

0.4(6.5) 1.24(18.75)

0.2(3.3) 0.65(9.42)

0.1(2.1) 0.41(5.95)

0.5(4.8) 1.41(13.9 9)

0.3(2.6) 0.72(7.43)

6.63(51.5 6)

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Figure 1. Effect of tillage (left) and weed control treatments (right) on total weed density in soybean field at 30 DAS

Figure 2. Effect of tillage (left) and weed control treatments (right) on total weed dry weight in soybean field at 30 DAS

Microbial Enumeration Populations of fungi, bacteria and actinomycetes and, soil DH- activity and MBC (Table 4) were significantly higher in no-tillage treatment in both years. This result is in conformity with Sharma . (2012). Soil microbes typically are Climited (Smith, 1990) and lower microbial biomass in soils can be explained with low organic C in the soil (Mathew, 2012). In no-till soils, the accumulation of crop residues on the soil surface results in enrichment of soil organic matter in the surface layer and as a consequence increased abundance of microorganisms (Mathew, 2012). Positive correlation between microbial biomass and SOM has been already reported (Nair, 2012 &Fliebach, 2007). Weedy check and weed-free check being comparable with each other had the highest populations of fungi, bacteria and actinomycetes followed by pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha and pendimethalin 0.75kg/ha alone. Soil DH-activity and MBC followed the similar trend. Wardle . (1999) also showed that in perennial crops, high weed biomass caused large increases in microbial biomass and respiration after yr 3, and microbial biomass was positively correlated with weed biomass and negatively with crop plant biomass due to the high decomposability of weed residues relative to those from crop plants. Sebiomo . ( 2011) observed that herbicide treatment resulted in a significant drop in DH- activity. Perucci and Scarponi (1993) showed that 10- and 100-fold higher herbicide concentrations of imazethapyr reduced microbial biomass and activity of dehydrogenase enzyme in soils. In contrast in this study, mixture of recommended dose of imazethapayr 0.075 kg/ha with pendimethalin 0.5 kg/ha increased the soil DH-activity and MBC. Mixture of metribuzin 0.3 kg/ha + chlorimuron-p-ethyl 0.009 kg/ha resulted in reduction of fungi, bacteria and actinomycetes populations, and soil DH-activity and MBC. Generally, herbicides tended to reduce the total number of soil microorganisms 7 to 30 days after application (Milosevic and Govedarica, 2000) and higher concentrations of herbicides treatments resulted in much lower microbial counts when compared to soils treated with recommended doses ( Sebiomo ., 2011; Ayansina and Oso, 2006; Sofia, 2012). Reduction in soil microorganism population by atrazin herbicide family has been already reported by Das . (2010); Sofia . (2012); Sebiomo . (2011) which, corroborated our findings in this regard. Mixture of metribuzin 0.3 kg/ha and chlorimuron 0.009 kg/ha resulted in reduction of soil DH-activity and MBC, the reason could be chlorimuron which, is sulfonylurea herbicide having

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slightly toxic effect on soil micro-flora at recommended dose (Sofia ., 2012). Sebiomo . (2011) showed that, generally, mixed pesticide combinations resulted in reduced microbial population compared to soils treated with single herbicide. Year-wise as well as pooled data showed non significant increase in microbial populations and MBC in second year (2011), however DH-activity was significantly increased in second year. However there is no universal pattern of herbicidal effect on the soil microorganisms but, it is believed that herbicide decreases the abundance, activity and diversity of soil microorganisms (Das ., 2010; Radivojevic ., 2004). We also observed that some herbicide treatments were toxic to fungi, bacteria and actinomycetes however the treatments containing metribuzin in their mixture were more toxic than other treatments. The pendimethalin treatment showed lower toxicity than the other treatments particularly when it mixed with imazethapyre. However negative effect of atrazin and pendimethalin on fungi has been already reported (Martin-Laurent ., 2003; Balasubramanian and Sankaran, 2001). Table 3. Microbial population as influenced by tillage and herbicide application Treatment First year (2010) Second year (2011) SEm ± LSD(P=0.05) Conventional tillage(CT) No-Tillage(NT) SEm ± LSD(P=0.05) Pendimethalin 0.75 kg/ha Pendimethalin 0.5 kg/ha+ imazethapyr 0.075 kg/ha Pendimethalin 0.5 kg/ha + chlorimuron-p-ethyl 0.009 kg/ha Metribuzin 0.3 kg/ha + imazethapyr 0.075 kg/ha Metribuzin 0.3 kg/ha + chlorimuron-p-ethyl 0.009 kg/ha Pendimethalin 0.75 kg/ha +hand weeding at 30 DAS Weedy check Weed-free check SEm ± CD(P=0.05)

Fungi (CFU*×103 /g dry soil) 2010 2011 pooled _ _ 24.9 _ _ 25.5 _ _ 0.5 _ _ NS 21.5 21.5 21.5 28.4 29.4 28.9 0.09 0.4 0.2 1.6 7.2 1.2 28.8 29.5 29.1 30.8 30.8 30.8 27.0 29.0 28.0 18.5 14.5 16.5 9.3 14.3 11.8 15.5 13.5 14.6 37.0 36.0 36.5 34.5 34.3 34.4 1.45 2.7 1.6 4.4 8.3 4.5

Bacteria (CFU ×107 /g dry soil) 2010 2011 pooled _ _ 5.9 _ _ 6.4 _ _ 0.2 _ _ NS 4.5 4.1 4.3 7.3 8.7 8.0 0.04 0.1 0.05 0.8 1.9 0.3 5.9 7.1 6.5 6.6 7.4 7.0 1.0 2.8 1.9 2.5 1.3 1.9 1.0 2.1 1.6 5.0 4.5 4.8 13.3 13.4 13.3 12.0 12.6 12.3 0.4 0.14 0.3 1.2 1.2 0.8

Actinomycetes (CFU×104 /g dry soil) 2010 2011 pooled _ _ 21.6 _ _ 22.1 _ _ 0.73 _ _ NS 16.9 14.4 15.7 26.2 29.8 28.0 0.4 0.4 0.3 7.3 7.47 1.8 18.8 22.0 20.4 23.8 26.6 25.3 15.7 17.8 16.7 15.0 17.8 16.4 14.0 14.1 14.0 20.8 21.0 20.9 33.5 33.0 33.3 31.3 24.3 27.8 1.6 2.4 1.5 4.9 7.4 4.2

Table 4. Soil dehydrogenase activity and microbial biomass carbon (MBC) as influenced by tillage and herbicide application Treatment First year (2010) Second year (2011) SEm ± LSD(P=0.05) Conventional tillage(CT) No-Tillage(NT) SEm ± LSD(P=0.05) Pendimethalin 0.75 kg/ha Pendimethalin 0.5 kg/ha+ imazethapyr 0.075 kg/ha Pendimethalin 0.5 kg/ha + chlorimuron-p-ethyl 0.009 kg/ha Metribuzin 0.3 kg/ha + imazethapyr 0.075 kg/ha Metribuzin 0.3 kg/ha + chlorimuron-p-ethyl 0.009 kg/ha Pendimethalin 0.75 kg/ha +hand weeding at 30 DAS Weedy check Weed-free check SEm ± CD(P=0.05)

TPF (μg/ g dry soil/day) 2010 2011 pooled _ _ 154.65 _ _ 185.94 _ _ 1.65 _ _ 10.02 148.29 169.97 159.13 161.01 201.90 181.46 6.22 3.21 3.50 NS 19.47 13.7 168.79 182.56 175.67 158.91 196.25 177.58 148.06 166.59 157.32 145.35 163.39 154.37 140.38 156.81 148.59 149.78 197.61 173.70 169.77 212.33 191.05 156.17 211.97 184.07 7.61 7.00 5.18 21.99 20.22 14.61

MBC (μg C/ g dry soil) 2010 2011 pooled _ _ 222.21 _ _ 235.77 _ _ 13.71 _ _ NS 102.91 179.24 171.08 281.50 292.29 286.9 4.22 11.26 5.83 53.68 NS 35.37 295.38 311.68 303.53 268.28 283.43 275.86 157.25 161.96 159.60 157.75 170.90 64.33 90.00 103.85 96.72 219.50 240.57 230.03 303.00 313.28 308.14 286.50 300.85 293.53 9.98 19.0 10.75 30.26 57.58 31.06

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The lowest yield after weedy check observed in pendimethalin 0.75 kg/ha may be due to higher weed pressure in this treatment. Inspite of better sedge killing effect of metribuzin 0.3 kg/ha + imazethapyr 0.075 kg/ha, its yield was lower than most of all other treatments. It seemed that metribuzin 0.3 kg/ha and imazethapyre 0.075 kg/ha tank mixture caused small stress on crop plant so that increase in height, LAI and totally vegetative growth could be attributed to plant reaction against this stress. Mutual shading of leaves and overlapping of canopies as indicated by higher LAI might be reason for lower photosynthesis and lowered yield. This result is in conformity with Poston . (2008) who, showed 13 and 8% soybean yield reductions by using 694 g/ha metribuzin in 2001 and 2002 and in conformity with Newsom and Shaw (1992) who, reported yield reductions with chlorimuron or imazethapyr application under certain conditions, however, some researchers have reported no loss in yield with chlorimuron or imazethapyr application Papiernik, (2005). CONCLUSION Out of this two years studies, it may be concluded that irrespective of weed species pendimethalin 0.5 kg/ha + imazethapyr 0.075 kg/ha having better weed control, less impact on soil micro-flora and microbial activity, resulted in higher yield of soybean comparable with weed-free check. Therefore, it may be recommended for better weed control and higher soybean yield. 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