Access Grid Nodes in Field Research

This article reports fieldwork with an Access Grid Node ('AGN') device, analogous to video teleconferencing but based on grid computational technology. The device enables research respondents to be interviewed at remote sites, with potential savings in travelling to conduct fieldwork. Practical, methodological and analytic aspects of the experimental fieldwork are reported. Findings include some distinctive features of AGN interviews relative to co-present interviews; overall, there were some benefits and some disadvantages to communication. The article concludes that this new research interview mode shows potential, particularly once the difficulties associated with a new research technology are resolved.Social Research Methods, Interview Methods, New Technologies for Social Research, Access Grid Nodes, Interview Communication, Witnesses at Court

Traditionally utilization of Selaginella; field research and literature review

Penelitian ini bertujuan untuk mengetahui manfaat Selaginella dalam pengobatan tradisional dan pemanfaatan lainnya, melalui penelitian lapangan dan telaah pustaka, khususnya di Jawa dan Kepulauan Nusantara. Sebanyak 200 dari 700-750 spesies Selaginella hadir di Kepulauan Nusantara. Secara tradisional Selaginella digunakan untuk mengobati luka, pendarahan, gangguan menstruasi dan kandungan, memperlancar peredaran darah, meningkatkan daya tahan tubuh, memperpanjang usia, mengobati sakit kepala dan lain-lain. Di samping itu beberapa jenis Selaginella juga digunakan sebagai sayuran (lalapan), tanaman hias, dan bahan baku kerajinan tangan. Pemanfaatan Selaginella sangat terbatas dibanding jumlah jenis dan potensi manfaat obatnya, sehingga diperlukan kajian etnobotani dan fitokimia lebih mendalam untuk meningkatkan pemanfaatannya. Kata kunci: obat tradisional, tanaman obat, etnobotani, Selaginella, Jawa

Field research 2012

Includes research reports from these locations: East Central Kansas Experiment Field, Kansas River Valley Experiment Field, and Western Kansas Agricultural Research Centers

Field research 2014

The research program at the East Central Kansas Experiment Field is designed to keep area crop producers abreast of technological advances in agronomic agriculture. Specific objectives are to (1) identify top performing varieties and hybrids of wheat, corn, soybean, and grain sorghum; (2) establish the amount of tillage and crop residue cover needed for optimum crop production; (3) evaluate weed and disease control practices using chemical, no chemical, and combination methods; and (4) test fertilizer rates, timing, and application methods for agronomic proficiency and environmental stewardship. Contributors: E.A. Adee, Assistant Professor, Kansas River Valley Experiment Field, Topeka I. Campitti, Assistant Professor, Dept. of Agronomy, K-State, Manhattan G. Cramer, Assistant Professor, South Central Experiment Field, Hutchinson E. DeWolf, Professor, Dept. of Plant Pathology, K-State, Manhattan B.J. Haverkamp, Graduate Student, Dept. of Agronomy, K-State, Manhattan J.D. Jennnings, Graduate Research Assistant, Dept. of Agronomy, K-State, Manhattan J. Kimball, Plant Science Tech, East Central Experiment Field, Ottawa K. Kusel, Research Assistant, Southeast Agricultural Research Center, Parsons C.R. Little, Associate Professor, Dept. of Plant Pathology, K-State, Manhattan C. Minihan, Assistant Scientist, Dept. of Agronomy, K-State, Manhattan S. Naeve, Associate Professor, Agronomy and Plant Genetics, University of Minnesota D.E. Peterson, Professor, Dept. of Agronomy, K-State, Manhattan P.V.V. Prasad, Professor, Crop Physiology, Dept. of Agronomy, K-State, Manhattan D. Presley, Associate Professor, Dept. of Agronomy, K-State, Manhattan C.B. Rajashekar, Professor, Dept. of Horticulture, Forestry, and Recreation Resources, K-State, Manhattan K.L. Roozeboom, Associate Professor, Cropping Systems, Dept. of Agronomy, K-State, Manhattan G. Sassenrath, Associate Professor, Southeast Agricultural Research Center, Parsons A. Schlegel, Professor, Southwest Research-Extension Center, Garden City D. Shoup, Extension Specialist, Crops and Soils, Southeast Area Office, Chanute J. Shroyer, Extension Specialist, Agronomy, K-State, Manhattan C.R. Thompson, Professor, Dept. of Agronomy, K-State, Manhattan E. Wilson, Graduate Student, Agronomy and Plant Genetics, University of Minnesot

Field Research: Poems

This thesis project discusses creative writing in poetry. The opening essay, through close readings of several poets, examines the idea of modernist conventions in poetry and the art as a “translation” of life. The discussion includes: T. S. Eliot with regard to the accessibility of poetry, William Stafford’s use of language, Sylvia Plath’s imagery, and Billy Collins authentic speaker or narrator. The remainder of the project is original poetry that covers diverse themes from nature to love and longing, from family to observational insight on the world

Vegetation and soils field research data base: Experiment summaries

Understanding of the relationships between the optical, spectral characteristics and important biological-physical parameters of earth-surface features can best be obtained by carefully controlled studies over fields and plots where complete data describing the condition of targets are attainable and where frequent, timely spectral measurement can be obtained. Development of a vegetation and soils field research data base was initiated in 1972 at Purdue University's Laboratory for Applications of Remote Sensing and expanded in the fall of 1974 by NASA as part of LACIE. Since then, over 250,000 truck-mounted and helicopter-borne spectrometer/multiband radiometer observations have been obtained of more than 50 soil series and 20 species of crops, grasses, and trees. These data are supplemented by an extensive set of biophysical and meteorological data acquired during each mission. The field research data form one of the most complete and best-documented data sets acquired for agricultural remote sensing research. Thus, they are well-suited to serve as a data base for research to: (1) quantiatively determine the relationships of spectral and biophysical characteristics of vegetation, (2) define future sensor systems, and (3) develop advanced data analysis techniques