The electrical conductivity of a saturated paste extract of soil (ECe) is a standard measurement of soil salinity, which may adversely effect the environment and plants. This study aimed to develop a precise linear regression relationship between ECe and electrical conductivity (EC) of different (1:5, 1:2.5, 1:1) soil-water ratios based on soil texture (represented by an index Txw) for the ease and rapid monitoring of soil salinity in an area. Surface (0–20 cm) soil samples (n = 150) from the coastal zone of Bangladesh were analyzed for particle size distribution, and EC by various methods. Entire soil samples were equally divided into two textural groups (finer and coarser) based on Txw values. Necessary statistical treatments were performed to satisfy the conditions of linear regression analysis. Significant correlations (r = −0.44** to −0.56**) were found between Txw and the EC values of various methods within the whole dataset. Derived general (not Txw-assisted, i.e., all data) and specific (Txw-assisted groups) equations followed the model ECe = $10^{[\mathrm{a}\left(\mathrm{L}\mathrm{o}\mathrm{g}\mathrm{E}{\mathrm{C}}_{\mathrm{S}\mathrm{o}\mathrm{i}\mathrm{l}:\mathrm{w}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{r}}\right)+\mathrm{b}]}$. Almost all specific equations showed improved coefficient of determinations (mean of all r² = 0.86; all p < .0001) compared to general ones (mean of all r² = 0.81; all p < .0001). While validation, corresponding errors (RMSE and/or ME) were found less in the specific equations than the general ones in predicting ECe. Therefore, soil texture (Txw)-based derived equations can preferably be used to predict ECe using other methods for the monitoring of soil salinity in an area.

Soil texture is an independent and innate soil property and other dynamic soil properties such as electrical conductivity (EC), organic carbon (OC) content and cation exchange capacity (CEC) are mostly dependent on it. An attempt was made to develop a model for numerically simulating soil texture and also to construct relationships of the developed model with other soil properties. Hypothetical data of particle size distribution and our data were used to justify and validate the newly defined indices. Scatter diagrams showed good association between the indices and hypothetical data of soil separates. Moreover, similar trends were observed between the line charts of USDA soil textural class codes and the indices. Strong correlations (r = 0.78–0.96) were found between the indices and soil separates (sand, silt and clay) for our data. However, the indices demonstrated moderate correlations (r = –0.34 to –0.55) with EC and OC of the soils. Strong nonlinear relationships were found between CEC and the three indices (R2 = 0.699, R2 = 0.732 and R2 = 0.672 (all P < 0.001). Furthermore, the variability of EC, OC and CEC within a single USDA textural class and customised textural index groups were described using the developed model. The developed indices showed excellent fitness for simulation of soil texture and demonstrated an extended applicability in terms of their relationships with soil properties related to soil texture, which will help in constructing digital soil maps.

Irrational applications of insecticides on vegetable crops are very common in Bangladesh, resulting in harmful consequences for the environment and human health. Therefore, a study was conducted to evaluate the efficacy of biological and botanical insecticides on okra shoot and fruit borer grown in open fields. Four insecticides were used in this study, namely Bacillus thuringiensis (Bt), Spinosad 45 SC, Abamectin 1.8 EC, and Azadirachtin 1% EC an untreated control. The experiment used a randomized complete block design (RCBD) with three replications. The results showed that the rate of shoot infestation was the lowest in the Spinosad-treated plot (3.80%), and the highest was in the control (20.67%). The lowest fruit infestation (3.56%) was recorded in the treated plot of Spinosad. The rate of reduction of fruit infestation over control was 80.69, 60.14, 56.45, and 55.58% in the plots treated with Spinosad, Bt, Azadirachtin, and Abamectin, respectively. Consequently, the Spinosad-treated plot attained the highest yield (8.65 t ha⁻¹), which was followed by the plots treated with Azadirachtin (6.74 t ha⁻¹), Bt (6.28 t ha⁻¹), and Abamectin (6.12 t ha⁻¹). The highest net return and benefit–cost ratio (BCR) were 542.36 US$ and 2.64, obtained respectively from the Spinosad-treated plot. The second highest BCR (1.70) was obtained from the Azadiratin-treated plot, and the lowest BCR (1.18) was recorded in the Abamectin-treated plot. Therefore, the studied insect management practices could be incorporated to attain higher yields and economic benefits for growing okra in Bangladesh.

Soil salinity expressed by electrical conductivity is a threat to crop production. The study aims were to establish relationships of electrical conductivity with its relevant soil properties, and analyze variability of soil salinity in the coastal zone of Bangladesh. A total of 150 geo-referenced saline soil samples from three coastal districts (Khulna, Satkhira and Bhola) of Bangladesh were analyzed for electrical conductivity of saturated paste extract (ECe), salt cations and other soil properties related to salinity. Statistical and geostatistical analyses were done as required. Moderate to strong significant regression relationships (R 2 =0.42 to 0.94) were found between ECe and salt cations (ECe=43.12*Na 2 -46.36*Na+13.97; ECe=12.26*K-2.5;ECe=1.16*Ca-1.97; ECe=0.32*Mg 2 -1.60*Mg+3.53) of the soils. On the contrary, weak relationships (R 2 =0.05 to 0.21) were found between ECe and other soil properties (ECe=4.41*organic carbon-0.56; ECe=-1.71*Txw (soil texture)+3.98;ECe=0.35*cation exchange capacity-1.98; ECe=0.06*specific surface area-0.55). Khulna soils (CV=65.99%) showed lower statistical variations while Satkhira (CV=97%) and Bhola (CV=105%) soils showed higher statistical variations for ECe. In contrast, Khulna, Satkhira and Bhola soils showed strong, moderate and weak spatial dependency for ECe, respectively. Interpolated spatial distribution maps of ECe showed variations in individual districts of study areas. The findings would assist soil scientists or farm managers to understand and/or manage saline soils, specially the soils of coastal zone of Bangladesh.