Weed Suppression by Deleterious Rhizobacteria is Affected by Formulation and Soil Properties

A field experiment was conducted at Agronomy Field Laboratory, Patuakhali Science and Technology University, Dumki, Patuakhali from July 2018 to November 2018 to evaluate the effect of sunflower residues and herbicides on the yield and economic performance of transplanted Aman rice. Weed control methods tested were T1 = weedy check (Unweeded control), T2 = Weed-free check by hand weeding twice, T3 = Pendimethalin, T4 = Pretilachlor, T5 = Butachlor, T6 = Pyrazosulfuron ethyl, T7 = Bensulfuron methyl + Acetachlor, T8 = Bispyriback sodium, T9 = 2,4-D amine, T10 = MCPA, T11 = Sunflower residues, T12 = Sunflower residues + 100% Pyrazosulfuron ethyl, T13 = Sunflower residues + 75% Pyrazosulfuron ethyl, T14 = Sunflower residues + 50% Pyrazosulfuron ethyl. The experiment was laid out in a randomized complete block design with fourteen treatments replicated thrice. Weedy check registered significantly the highest total weed density (354.67 m-2) and total weed dry matter (51.81 g-2) while weed-free treatment by hand weeding twice recorded significantly the lowest total weed density (6.67 m-2) and total weed dry matter 0.49 g-2) . Weedy check produced the highest weed index (34.24%) and hand weeding produced the lowest. Among different herbicides applied alone, butachlor had the lowest total weed density (15 m-2) and total weed dry matter (6.43 g-2) after hand weeding. Hand weeding recorded the highest grain yield (5.14 t ha-1) which was statistically similar to pendimethalin, pretilachlor, butachlor, bensulfuron methyl + acetachlor and sunflower residues + 100% pyrazosulfuron ethyl. Higher grain yield was attributed to a higher number of panicle m-2, number of filled grains panicle-1 and 1000-grain weight. The highest gross margin (22955 Tk. ha-1) and benefit-cost ratio (1.32) were obtained from butachlor. Integration of sunflower residues with pyrazosulfuron ethyl produced effective weed suppression and satisfactory yield comparable to butachlor. Although the integration is less profitable than butachlor the farmers can use this technology as a feasible and environmentally sound approach in transplanted Aman rice field. Bangladesh Agron. J. 2020, 23(1): 47-58

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Effect of Methods and Interval Irrigation in Addition Soil Surface Mulching on Some Soil Properties and Production of Date Palm Phoenix dactylifera L. in South of Basrah 1- Moisture content and salt distribution in the soil

Basrah Journal of Agricultural Sciences ◽

10.33762/bagrs.2016.116191 ◽

2016 ◽

Vol 29 (1) ◽

pp. 154-171

Author(s):

Abdulrahman D. S. Alhamd ◽

Ali .H. Theyab

Keyword(s):

Moisture Content ◽

Soil Properties ◽

Date Palm ◽

Soil Surface ◽

Phoenix Dactylifera ◽

Phoenix Dactylifera L ◽

Salt Distribution

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Applying the Method of Lagrange Multipliers to Derive an Estimator for Unsampled Soil Properties

Scientific Research Journal ◽

10.24191/srj.v11i1.5416 ◽

2014 ◽

Vol 11 (1) ◽

pp. 15

Author(s):

Set Foong Ng ◽

Pei Eng Ch’ng ◽

Yee Ming Chew ◽

Kok Shien Ng

Keyword(s):

Soil Properties ◽

Lagrange Multipliers ◽

Unbiased Estimator ◽

Soil Property ◽

Minimum Variance ◽

Distance Method ◽

True Value ◽

A Site ◽

Method Of Lagrange Multipliers ◽

Inverse Distance

Soil properties are very crucial for civil engineers to differentiate one type of soil from another and to predict its mechanical behavior. However, it is not practical to measure soil properties at all the locations at a site. In this paper, an estimator is derived to estimate the unknown values for soil properties from locations where soil samples were not collected. The estimator is obtained by combining the concept of the ‘Inverse Distance Method’ into the technique of ‘Kriging’. The method of Lagrange Multipliers is applied in this paper. It is shown that the estimator derived in this paper is an unbiased estimator. The partiality of the estimator with respect to the true value is zero. Hence, the estimated value will be equal to the true value of the soil property. It is also shown that the variance between the estimator and the soil property is minimised. Hence, the distribution of this unbiased estimator with minimum variance spreads the least from the true value. With this characteristic of minimum variance unbiased estimator, a high accuracy estimation of soil property could be obtained.

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