我国农产品物流存在的问题与发展对策

伴随农业经济的快速发展,我国农产品物流规模急剧扩大。在快速增长的过程中,我国农产品物流存在着体制不完善、决策不科学、技术水平低和地域差异大等问题,需要通过制定发展规划、提高技术水平、树立现代物流观念等措施来促进我国农产品物流的发展。     

吉林省农产品包装发展阶段初探

吉林省农产品包装伴随着农产品的商业化、产业化、品牌化进程而发展,大体经历了原始单一、推出商标、品牌纷繁、整合归一四个发展阶段.本文总结了吉林省农产品包装过去三十年的发展道路,同时指出了吉林省农产品包装未来的发展方向.     

干旱灾害成灾过程数值模拟研究

以有限区域大气运动模式和土壤水热传导模式为基础,采用地表水分蒸发、地表水渗透、植被的蒸腾作用与根系吸水作用、地面风场4种过程作为模型的耦合方案,建立了用于干旱灾害成灾过程数值模拟的数学耦合模型.利用该数学模型模拟计算了1995年7月1～30日发生在长江中下游地区的干旱灾害,其干旱过程可分为土壤可供水量满足农作物需水量阶段、根系层土壤供水量小于农作物需水量阶段、农作物干旱阶段3个阶段,实践证明该模型对干旱灾害的发生发展过程具有很好的模拟能力.     

喷洒有效微生物群对玉米抗旱性的影响

采用孕穗期干旱处理前喷施有效微生物群（ＥＭ）研究干旱对玉米叶片膜脂过氧化和抗性酶及产量的影响。结果表明：ＥＭ能明显降低ＭＤＡ含量，提高ＳＯＤ和ＣＡＴ活性，增强玉米的抗旱性并提高产量。     

Optimal classification methods for mapping agricultural tillage practices

The classification of agricultural tillage systems has proven challenging in the past using traditional classification methods due to the similarity of spectral reflectance signatures of soils and senescent crop residues. In this study, five classification methods were examined to determine the most suitable classification algorithm for the identification of no-till (NT) and traditional tillage (TT) cropping methods: minimum distance (MD), Mahalanobis distance, Maximum Likelihood (ML), spectral angle mapping (SAM), and the cosine of the angle concept (CAC). A Landsat ETM+ image acquired over southern Michigan and northern Indiana was used to test these classification methods. Each classification method was validated with 293 ground truth sampling locations collected commensurate with the satellite overpass. Classification accuracy was then assessed using error matrix analysis, Kappa statistics, and tests for statistical significance. The results indicate that of the classification routines examined, the two spectral angle methods were superior to the others. The cosine of the angle concept algorithm outperformed all the other classification routines for tillage practice identification and mapping, yielding an overall accuracy of 97.2% (Kappa=0.959).     

Optimal design of integrated agricultural water networks

This paper presents a mathematical programming model for the optimal design of water networks in the agriculture. The proposed model is based on a new superstructure that includes all configurations in terms of use, reuse and regeneration of water in a field constituted by a number of croplands. The model also includes the allocation of pipelines, pumps and storage tanks in different irrigation periods. The objective function consists in maximizing the annual profit that is formed by the economic incomes owing to the crop sell minus the costs for fresh water, fertilizer, storage tanks, treatment units, piping and pumping. The proposed multi-period optimization problem is formulated as a mixed integer non-linear programming formulation, which was applied to a case study to demonstrate the economic, environmental and social benefits that can be obtained.     

Finding Order in a Chaotic World

Abstract

The World Wide Web (WWW) has a decentralized information environment and a non-linear (hypertext) information structure. This non-linear structure allows users to retrieve information at many different levels but also increases the difficulty of information retrieval. Unlike a well-developed CD-ROM database, the WWW does not have a controlled searching environment and information can be indexed in many different ways. It takes a well planned search strategy to perform an effective search in the labyrinth of the WWW. The SIRO (Systematic Information Retrieval/Organization) model offers a research planning process designed specifically for information seekers in the agricultural disciplines. The intention is to enhance search results and organize retrieved information. This process starts with the identification of the information structure on the WWW, then proceeds by organizing and analyzing information in a visual diagram or a “thinking map.” This process leads searchers to logical sources on the WWW and a systematic analysis of the result.     

New innovations in agricultural biotech: Consumer acceptance of topical RNAi in rice production

To test the market viability of a non-GMO topical RNAi insect control, we conducted a Willingness-To-Pay (WTP) survey in the USA, Canada, Australia, France, and Belgium to elicit whether consumers need a premium or discount for: (1) a hypothetical GMO rice variety using the Bacillus thuringiensis (Bt) gene for insect control; and (2) a hypothetical non-GMO rice variety using topical RNAi spray for insect control. The survey was designed based on a Multiple Price List (MPL) format where respondents selected their preferred insect control technology; i.e., conventional, GMO Bt, or non-GMO RNAi, at different prices. Participants' responses were analyzed using an interval regression model to generate WTP premiums and discounts for each country with control variables for demographic influences. Further, we asked consumers their Willingness-To-Consume (WTC) food produced with GM and RNAi technologies respectively and evaluated WTC differences using a McNemar matched pairs test in each country. The results from our study clearly show that: (1) consumers in the USA, Canada, Australia, and France still require a discount for rice produced with topical RNAi compared to conventionally-produced rice (p < 0.05), (2) consumers in the USA, Canada, Australia, France, and Belgium would need an additional 30–40% discount to purchase Bt rice over rice produced with topical RNAi (p < 0.05), and (3) consumers in all countries were more willing to consume rice produced with non-GM RNAi than with GM Bt technology (p < 0.05). These findings suggest consumers differentiate among biotechnology solutions and consumers may prefer topical RNAi insect control to transgenic GMO insecticides.     

Internet of Things for the Future of Smart Agriculture: A Comprehensive Survey of Emerging Technologies

This paper presents a comprehensive review of emerging technologies for the internet of things (IoT)-based smart agriculture. We begin by summarizing the existing surveys and describing emergent technologies for the agricultural IoT, such as unmanned aerial vehicles, wireless technologies, open-source IoT platforms, software defined networking (SDN), network function virtualization (NFV) technologies, cloud/fog computing, and middleware platforms. We also provide a classification of IoT applications for smart agriculture into seven categories: including smart monitoring, smart water management, agrochemicals applications, disease management, smart harvesting, supply chain management, and smart agricultural practices. Moreover, we provide a taxonomy and a side-by-side comparison of the state-of-the-art methods toward supply chain management based on the blockchain technology for agricultural IoTs. Furthermore, we present real projects that use most of the aforementioned technologies, which demonstrate their great performance in the field of smart agriculture. Finally, we highlight open research challenges and discuss possible future research directions for agricultural IoTs.