Automatic Identification and Monitoring of Plant Diseases Using Unmanned Aerial Vehicles: A Review

Disease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and architectures of machine learning models are used to classify and detect plant diseases. These models help in image segmentation and feature extractions to interpret results. Researchers also use the values of vegetative indices, such as Normalized Difference Vegetative Index (NDVI), Crop Water Stress Index (CWSI), etc., acquired from different multispectral and hyperspectral sensors to fit into the statistical models to deliver results. There are still various drifts in the automatic detection of plant diseases as imaging sensors are limited by their own spectral bandwidth, resolution, background noise of the image, etc. The future of crop health monitoring using UAVs should include a gimble consisting of multiple sensors, large datasets for training and validation, the development of site-specific irradiance systems, and so on. This review briefly highlights the advantages of automatic detection of plant diseases to the growers

Efficacy and Timing of Application of Fungicides, Biofungicides, Host-Plant Defense Inducers, and Fertilizer to Control Phytophthora Root Rot of Flowering Dogwoods in Simulated Flooding Conditions in Container Production

Phytophthora root rot caused by Phytophthora cinnamomi Rands is one of the major diseases of flowering dogwoods (Cornus florida L.). The severity of root rot disease increases when the plants are exposed to flooding conditions. A study was conducted to determine the efficacy and timing of application of different fungicides, biofungicides, host plant defense inducers, and fertilizer to manage Phytophthora root rot in month-old seedlings in simulated flooding events for 1-, 3-, and 7- days. Preventative treatments were drench applied 3 weeks and 1 week before flooding whereas curative treatments were applied 24 hrs. after flooding. Dogwood seedlings were inoculated with P. cinnamomi 3 days before the flooding. Plant height and width were recorded at the beginning and end of the study. At the end of the study, plant total weight and root weight were recorded and disease severity in the root was assessed using a scale of 0-100%. Root samples were plated using PARPH-V8 medium to determine the percentage recovery of the pathogen. Empress Intrinsic, Pageant Intrinsic, Segovis, and Subdue MAXX, as preventative and curative applications, were able to suppress the disease severity compared to the inoculated control in all flooding durations. All treatments, with the exception of Stargus as preventative application 3 weeks before flooding and Orkestra Intrinsic as curative application, were able to suppress the disease severity compared to the inoculated control for 1-day flooding event. Aliette and ON-Gard were effective in the first trial when applied preventatively in both 1 week and 3 weeks before flooding but not in the second trial. Signature Xtra was effective as preventative application but not as a curative application. Interface was effective as curative application but not as preventative application. The findings of this study will help nursery growers to understand the performance of fungicides, biofungicides, host-plant defense inducers, and fertilizer in different time intervals and repeated applications to manage Phytophthora root rot in flooding conditions

Causes and Impacts of Geotechnical Problems on Bridge and Road Construction Projects

Changes during the construction phase generate cost growth, schedule delays, and claims in any project. However, the impact of geotechnical problems on construction costs, schedules, and claims in bridge and road projects had not been investigated in depth. The major objectives of this study were to determine the geotechnical-related causes of cost and schedule growth and claims as well as their impacts on the bridge and pavement projects’ performance. This study also identifies mitigation measures to avoid cost and schedule growth and claims in these projects. A survey was conducted with 53 engineers from state Department of Transportations (DOTs) and 43 engineers from design consultant firms. It was found that the geotechnical-related causes that most impacted the costs, schedules, and claims of bridge projects were lack of boring locations and misclassified subgrade. The majority of the respondents stated that these geotechnical-related causes had negative impacts on cost and schedule growth and the number of claims for bridge projects during construction. When asked about pavement projects, the respondents stated that the significant problems to impact the cost and schedule growth and claims were misclassified subgrade and a level of groundwater table higher than expected. The results regarding the impact of these geotechnical-related causes on project performance were similar to those of bridge projects. The survey results also showed three major preventive measures to reduce these cost overruns, schedule growth, change orders, and claims were: the designer having detailed knowledge about the project site’s geotechnical information, a detailed site investigation with a well-experienced consultant, and the development and implementation of minimum standards for subsurface investigation and site characterization

Domestic and foreign institutional investors' investment in IPOs

The regulatory provisions in India ensure that IPO investors are able to observe the participation levels of other subscribers prior to their own subscription decisions. This should reduce the information asymmetry between the foreign institutional (FIIs) and domestic institutional investors (DIIs). We argue that because of this setting we should observe less difference in their investment patterns and performance. Our results, however, show that (a) FIIs subscribe to IPOs more aggressively than DIIs; (b) DIIs have better IPO selection ability than FIIs; and (c) in the post-listing period, FIIs reduce their IPO holdings more extensively than DIIs. FIIs reduce their post-listing holdings especially in firms that are smaller, younger, have higher stock volatility while increasing on stocks with higher returns, indicating that FIIs chase hot markets. Overall, in spite of transparency-enhancing regulations, the investment patterns of FIIs and DIIs differ significantly

A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations

We present a novel dynamic recommendation model that focuses on users who have interactions in the past but turn relatively inactive recently. Making effective recommendations to these time-sensitive cold-start users is critical to maintain the user base of a recommender system. Due to the sparse recent interactions, it is challenging to capture these users' current preferences precisely. Solely relying on their historical interactions may also lead to outdated recommendations misaligned with their recent interests. The proposed model leverages historical and current user-item interactions and dynamically factorizes a user's (latent) preference into time-specific and time-evolving representations that jointly affect user behaviors. These latent factors further interact with an optimized item embedding to achieve accurate and timely recommendations. Experiments over real-world data help demonstrate the effectiveness of the proposed time-sensitive cold-start recommendation model.Comment: 7 pages, conferenc

International equity portfolio allocations and stock market development

This paper examines whether the widely reported phenomena of home and foreign biases (i.e. sub-optimal international equity portfolio diversification) hold any ramifications for the development of stock markets. The results, analysed using macro- and micro-level data, support the view that stock markets that are characterised by a higher degree of home bias are associated with lower levels of development. On the other hand, markets where foreign investors show a higher degree of allocation preference, relative to the prescribed benchmark (foreign bias), are found to be more developed. The results, which are robust to the use of shock based identification strategy, indicate that policy measures that promote optimal international equity portfolio diversification could be crucial in developing the depth and breadth of domestic stock markets

Effects of integrated nutrient management in early season cauliflower production and its residual effects on soil properties

This experiment was conducted in the farmer’s field at Khajrauta, Gadhawa-4, Dang, Nepal to evaluate the effect of integrated nutrient management on growth and yield of cauliflower as well as their residual effects on soil properties. The cauliflower variety silvercup-60 was grown under eight different treatments; T1: 50% N through RDF + 50% N through FYM; T2: 50% N through RDF + 50% N through PM; T3: 50% N through RDF + 50% N through VC, T4: 50% N through RDF + 25% N through FYM + 25% N through PM; T5: 50% N through RDF + 25% N through VC + 25% N through PM; T6: 50% N through RDF + 25% N through VC + 25% N through FYM; T7: 50% N through RDF + 25% N through  VC +25% N through FYM; T8: 50% N through RDF + 50% N  through FYM,VC and poultry manure. The experiment was laid out in RCB design with three replications. The result revealed that the  highest plant height (36.40 cm), number of leaves (15), plant spread (31.72 cm), leaf area (526.5 cm2), curd weight (207.3g) and curd yield (12.85 t/ha) were found under 50% N through RDF +50% N through VC. The root length, root diameter and root density were better under all INM treatments as compared to 100% N through RDF. INM treatments showed lesser bulk density, lesser particle density, greater infiltration rate and greater organic matter content than application of 100% N through RDF. Soil total nitrogen was increased in all INM treatments while soil available phosphorus decreases in all treatments except 100% N trough RDF and 50% N through RDF +50% N through PM. Thus, farmers are suggested to apply 50% N through VC along with 50% N through RDF to increase cauliflower yield.  &nbsp