Detection of bifenthrin, bifenazate, etoxazole resistance in Tetranychus urticae collected from mint fields and hop yards using targeted sequencing and TaqMan approaches

Tetranychus urticae (Koch) is an economically important pest of many agricultural commodities in the Pacific Northwest. Multiple miticides are currently registered for control including abamectin, bifenazate, bifenthrin, and extoxazole. However, populations of Tetranychus urticae have developed miticide resistance through multiple mechanisms, in many different growing regions. Producers of agricultural commodities where Tetranychus urticae infestations are problematic rely on integrated pest management tools to determine optimal control methods. Within this species multiple single nucleotide polymorphisms have been documented in different genes which are associated with miticide resistance phenotypes. The detection of these mutations through TaqMan qPCR has been suggested as a practical, quick, and reliable tool to inform agricultural producers of miticide resistance phenotypes present within their fields and have potential utility for making appropriate miticide application and integrated pest management decisions. Within this investigation we examined the use of a TaqMan qPCR-based approach to determine miticide resistance genotypes in field-collected populations of Tetranychus urticae from mint fields and hop yards in the Pacific Northwest of the United States and confirmed the results with a multiplex targeted sequencing. The results suggest the TaqMan approach accurately genotypes Tetranychus urticae populations collected from agricultural fields. The interpretation of the results, however, provide additional challenges for integrated pest management practitioners, including making miticide application recommendations where populations of Tetranychus urticae are a mix of resistant and wildtype individuals.

Analysis of Soil Primary Macro Nutrient Status in Agricultural Land, Tabundung District, East Sumba Regency

Agricultural land is land that can affect agricultural productivity. Land, which is part of land resources, is the main component in the production of agricultural commodities. In supporting the productivity of agricultural commodities, there must be sufficient nutrients in the soil. Tabundung sub-regency is a producer of food crops, livestock and fisheries. As the main producer in the agricultural sector, the production of agricultural crops is not proportional to the total area of harvested land, meaning that the productivity of agricultural crops is not optimal if it is based on harvested area. The study was conducted in Tarimbang Village, Proud Watu and Tapil Regency of Tabundung. The method used in this research was survey technique and soil sampling was carried out in a composite manner. Soil samples were analyzed at the Nusa Cendana University Laboratory, Kupang. Primary data analyzed were elements of nitrogen (N), phosphorus (P), potassium (K), organic carbon (C), cation exchange capacity (CEC), and pH. The results showed that the overall nutrient status of N, P, and K were in the medium, high and very high categories, but there were some sample points that were in the low category for macronutrients N and P. While the concentrations of organic C, CEC and pH were overall generally in pretty good condition. This condition indicates that the research area provides sufficient nutrients for plant cultivation during the growth and yield of plants, but improvements are needed to overcome macronutrient deficiencies in several observation locations.

Introduction

India has come a long way from being a food scarce nation in the 1960s to a food surplus nation thereafter. The remarkable transformation of the agricultural sector was the result of massive improvements in productivity level owing to the Green Revolution in the case of cereals and the breakthrough that followed in few other agricultural commodities, most notably, dairying. Today, India is the largest producer of milk, pulses, banana, mango, pomegranate, papaya, lemon, okra, ginger and non-food crops like cotton and jute; the second-largest producer of rice, wheat, fruits and vegetables, tea and one of the leading producers of eggs and meat in the world. India produced 281.8 million tonnes of food grains, 307.7 million tonnes of horticulture crops, 176.5 million tonnes of milk, 96 billion eggs and 7.7 million tonnes of meat during TE 2018–19.

IDENTIFIKASI KENDALA PEMBIAYAAN KOMODITAS PERTANIAN SISTEM RESI GUDANG DI INDONESIA

Abstrak Pembiayaan komoditas pertanian sistem resi gudang belum berlangsung sesuai harapan di Indonesia. Hal tersebut menurut beberapa studi karena masih banyak permasalahan penghambat. Studi ini mengidentifikasi kendala pembiayaan komoditas pertanian sistem resi gudang di Indonesia. Penelitian dilakukan melalui wawancara mendalam terhadap responden tertentu yang memiliki pengetahuan atau pengalaman pada pembiayaan komoditas pertanian berbasis sistem resi gudang yang diimplentasikan terhadap komoditas pertanian seperti kopi, lada, beras dan jagung. Data yang dikumpulkan diidentifikasi, dikelompokkan dan diklasifikasikan secara terstruktur di dalam pola berfikir strategis dan dianalisa secara analisa deskriptif. Penelitian ini berhasil menemukan faktor penghambat pembiayaan komoditas pertanian sistem resi gudang di Indonesia antara lain: ketidaksesuaian nilai manfaat yang dibangun dengan karakteristik petani di Indonesia khususnya petani kecil; keterbatasan sumber layanan, ketidakcocokan skema dan fitur pembiayaan, harga pembiayaan dan skala ekonomi petani, suplai informasi yang memengaruhi kesadaran pada pembiayaannya. Permasalahan tersebut harus dapat diminimalisasi sehingga meningkatkan aksesibilitas dan kelangsungan pembiayaan sistem SRG pada petani di Indonesia. Kata kunci: Pembiayaan Komoditas Pertanian, Kendala, Sistem Resi Gudang Abstract Agricultural commodity financing in the warehouse receipt system has not performed as expected in Indonesia. According to several studies, it is due to many obstacles hindering the system to grow. This study identifies the constraints on agricultural commodities financing on the warehouse receipt system. The research was conducted through in-depth interviews with certain respondents who have knowledge or experience in agricultural commodities financing based on a warehouse receipt system implemented on agricultural commodities such as coffee, pepper, rice, and maize. The collected data are identified, grouped, and classified in a structured manner in the pattern of strategic thinking and analyzed by descriptive analysis. The study succeeded to identify the barriers that hindering agricultural commodities financing in warehouse receipt system to grow in Indonesia: the incompatibility of the value built with the characteristics of agriculture business, especially for small farmers; limited financing sources, incompatibility of financing schemes and features, financing prices and farmer economies of scale and supply of information that affects awareness of financing. These problems must be minimized to encourage the accessibility and continuity of financing on WRS for farmers in Indonesia. Keywords: Agricultural Commodity Financing, Contraints, Warehouse Receipt System JEL Classification: D46, F6, F61, F65, Q14

Commodity Shocks and Incumbency Effects

Why do incumbents enjoy an electoral advantage in some political settings but suffer from a disadvantage in others? We propose a novel explanation linking variation in incumbency effects with exogenous commodity shocks. While voters attempt to sanction incumbents for economic performance, changes in commodity prices affect their evaluations and condition the electoral fortunes of incumbents vis-à-vis challengers. We test our argument in Brazilian municipalities, combining a plausibly exogenous measure of variation in commodity prices with a close election regression discontinuity design. Our results show that increases in the price of agricultural commodities greatly enhance the prospects of incumbents, while negative shocks exacerbate their incumbency disadvantage, especially in rural municipalities. Further investigation suggests that commodity shocks do not operate via voter learning about candidate quality, changes in the pool of candidates, shifts in voter preferences, or strategic elite investments. Instead, we find suggestive evidence that commodity shocks affect voters' evaluations through their effect on local economic growth.

Prediction of Agricultural Commodities Futures Prices: A DQN-LSTM Method

This paper combines deep Q network (DQN) with long and short-term memory (LSTM) and proposes a novel hybrid deep learning method called DQN-LSTM framework. The proposed method aims to address the prediction of five Chinese agricultural commodities futures prices over different time duration. The DQN-LSTM applies the strategy enhancement of deep reinforcement learning to the structural parameter optimization of deep recurrent networks, and achieves the organic integration of two types of deep learning algorithms. The new framework has the capacity of self-optimization and learning of parameters, thus improving the performance of prediction by its own iteration, which shows great prospects for future application in financial prediction and other directions. The performance of the proposed method is evaluated by comparing the effectiveness of the DQN-LSTM method with that of traditional predicting methods such as auto-regressive integrated moving average (ARIMA), support vector machine (SVR) and LSTM. The results show that the DQN-LSTM method can effectively optimize the traditional LSTM structural parameters through policy iteration of the deep reinforcement learning algorithm, which contributes to a better long and short-term prediction accuracy. In particular, the longer the prediction period, the more obvious the advantage of prediction accuracy of a DQN-LSTM method.