Effects of Land Use Land Cover and Slope Gradients on Soil Fertility at Kori Sub-Watershed, East Wollega, Ethiopia

BackgroundThe complex nature of the relationship and interaction between LULC and slope gradients resulted in the decline of soil fertility parameters, which aggravate the reduction of sustainable productivity in Ethiopia in general and the study area in particular. This study was aimed to determine the effects of land use land cover and slope gradients on the physicochemical properties of soil in study area A total of 27 composite soil samples were collected from 0-20cm depth under three dominant adjacent LULC across three slope with three replications. The collected soil samples were analyzed for selected soil physicochemical properties. Two-way ANOVA was used to test the mean differences of the soil fertility parameters. ResultThe mean values of soil physicochemical parameters showed that, SOC, TN, AvP, CEC, exchangeable bases (Ca2+ Mg2+, K+, and Na+), PBS, and percentage of clay contents of cultivated land and steep slope gradient (15-30%) were low and significantly different at (P≤0.05) than forest and grad grassland of the same slope gradient.. The gentle slope (3-8%) gradients of the forest lands had the lowest BD and high TP as compared to the others.ConclusionThe overall soil fertility status of the steep slope gradient (15-30%) of cultivated lands is lower than others and cultivating the steep slope is the cause for productivity loss in the study sub-watershed. Therefore, proper land-use planning and the use of integrated soil fertility management strategy give better production and keep the soil fertility status to a better level.

Does China’s Fertility Policy Induce Employment Discrimination Against Women? Evidence from a Nationwide Correspondence Experiment

We apply a two-wave nationwide correspondence experiment to assess the effects of the two-child and three-child policies in China. Using 13,751 observations collected through this experiment, we find that the announcement of the two-child policy led to a 4.9% decrease in total interview callbacks overall, and decreases of 4.3%, 5.7%, and 5.6% for single women, those married with no children, and those married with one child, respectively. The implementation of the three-child policy led to a 10.4% decrease, but only for married women with two children. The discrimination broadly affected all women, whether they disclose marriage and fertility status information or not, as we find their callback rates decreased by 4.5% under the universal two-child policy and 6.6% after the three-child policy.

Effect of Zinc Sources on Nutrient Content and Uptake in Soybean [Glycine max (L.) Merril] under the Acidic Soil Conditions of Nagaland

Background: Soybean is an important legume as well as oil seed crop grown in a varied range of climate and soils. Zinc is an important micronutrient required for plants, animals and human. Its deficiency in soil is a worldwide concern for production of food crops. Therefore two years reseach in two locations were conducted in 2019 and 2020 to study the nutrient content and uptake of NPK and Zn in soybean with zinc fertilization. Methods: A two years research was conducted in two locations under the acidic soil conditions of Nagaland. Nutrient content and uptake of N, P, K and Zn were recorded at first, second year and pooled. The location, climate, altitude and soil fertility status were recorded in both the sites. Altogether there were 13 treatments and 3 replications.The experimental design used was simple RBD. The datas were recorded, analysed and computed statistically. Result: The nutrient uptake of N, K and Zn except P in soybean were significantly found to be increased @ 5 kg ha-1 ZnSO4 H2O + RDF (T9) followed by T8 and T10 as compared to control in both the years and pooled.

Performance of Pigeon Pea (Cajanus cajan) Varieties under Different Soil Amendments in Ndokwa, Delta State, Nigeria

Background: Pigeon pea is an important legume worldwide that is not cultivated by the farmers in Ndokwa, Delta State. Hence, the study looked at the possibility of evaluating the potential of pigeon pea in Ogume, a community in Ndokwa. Methods: Top soils were collected from a fallowed land mixed thoroughly and filled into 4 kg bags and were divided into 3. The 1st was amended with poultry manure, 2nd was NPK 15:15:15 amended and 3rd was without amendment, tested with two varieties of Cajanus cajan. The experiment was a 2 by 3 factorial, in a completely randomized design with 3 replicates. Residual effects of the amendments were evaluated in 2020. Soil samples were taken to establish the fertility status before amendment and at harvest. Data were taken on the agronomic and yield parameters and were analyzed using ANOVA while means were separated using LSD at P≤0.05. Result: Result obtained showed that the tallest plants (9.83±0.51) were observed in the poultry manure in 2019 while the fallowed plots had the tallest plants (11.17±0.49) in 2020, while in both years, the number of pods and dry pod weight was insignificant among the treatments and varieties. This shows that farmers do not need to spend much finance in amending the soil for pigeon pea cultivation in Ndokwa community, Delta State.

The Automatic Classification of Pyriproxyfen-Affected Mosquito Ovaries

Pyriproxyfen (PPF) may become an alternative insecticide for areas where pyrethroid-resistant vectors are prevalent. The efficacy of PPF can be assessed through the dissection and assessment of vector ovaries. However, this reliance on expertise is subject to limitations. We show here that these limitations can be overcome using a convolutional neural network (CNN) to automate the classification of egg development and thus fertility status. Using TensorFlow, a resnet-50 CNN was pretrained with the ImageNet dataset. This CNN architecture was then retrained using a novel dataset of 524 dissected ovary images from An. gambiae s.l. An. gambiae Akron, and An. funestus s.l., whose fertility status and PPF exposure were known. Data augmentation increased the training set to 6973 images. A test set of 157 images was used to measure accuracy. This CNN model achieved an accuracy score of 94%, and application took a mean time of 38.5 s. Such a CNN can achieve an acceptable level of precision in a quick, robust format and can be distributed in a practical, accessible, and free manner. Furthermore, this approach is useful for measuring the efficacy and durability of PPF treated bednets, and it is applicable to any PPF-treated tool or similarly acting insecticide.

GIS-based Fertility Assessment and Mapping for Agricultural Research Station, Tandur, Telangana, India

This study was conducted to determine the soil fertility status of the Agricultural Research Station, Tandur of Professor Jayashankar Telangana State Agricultural University (PJTSAU), Vikarabad District, Telangana. To identify the soil sampling points, GPS device was used and collected total of 60 soil samples on grid-based method at a depth of 0–15 cm. The collected samples were analyzed for pH, EC, OC, N, P2O5, K2O, Zn, Cu, Fe and Mn status by following standard methods in the laboratory of Regional Agricultural Research Station, Palem, PJTSAU, Nagarkurnool District of Telangana, and Arc-GIS software was used further to prepare soil fertility maps. Around 37.5% of samples fall in neutral pH, whereas 62.5% samples were found as moderately alkaline reactions and entire farm soils were non-saline. Among the analyzed soil samples, 37.29% samples were in low organic carbon content, and rest of the samples i.e.,62.71% have medium organic carbon content and total samples were low in available N content (< 280 kg ha-1). The analyzed farm samples were medium to high in available phosphorus and potassium (28.67 & 71.33 % of P2O5 and 16.96 & 83.04 % of K2O respectively) content. In contrast, the micronutrients (Zn, Cu, Fe & Mn) exceeded their sufficiency level and suggested for amelioration measures to enhance research efficacy in the farm and to build future research strategies based on the determined soil fertility status.