Factors affecting farmland prices in Finland

The purpose of the study was to analyse factors affecting the differences in land prices between regions. The key issue was to find out the policy effects on farmland prices. In addition to comprehensive literature review, a theoretical analysis as well as modern panel and spatial econometric techniques were utilized. The study clearly pointed out the importance of taking into account the possible spatial dependence. The data were exceptionally large, comprising more than 6 000 observations. Thus, it allowed a thorough econometric estimation including the possibility to take into account the spatial nature of the data. This study supports the view that there are many other factors that affect farmland prices besides pure agricultural returns. It was also found that the support clearly affects land prices. However, rather than assuming the discount rates for support and market returns to be similar, the rough analysis refers to the discount rate for support being a little lower. If this were true it would indicate that farmers rely more on support income than market returns. The results support the view presented in literature that land values are more responsive to government payments when these payments are perceived to be permanent. An important result of this study is that the structural differences between regions and the structural change in agriculture seemed to have a considerable role in affecting land prices. Firstly, the present structure affects the competition in the land market: the more dense farms are in the region the more there are potential buyers, and the land price increases. Secondly, the change in farm structure (especially in animal husbandry) connected to the policy changes that increase area-based support affects land prices. The effect comes from two sources. Growing farms need more land for the manure, and the proportion of retiring farmers may be lower. The introduction of the manure density variable proved to be an efficient way to aggregate the otherwise very difficult task of taking into account the environmental pressure caused by structural change in animal husbandry. Finally, infrastructure also has a very important role in determining the price level of agricultural land. If other industries are prospering in the surrounding area, agricultural viability also seems to improve. The non-farm opportunities offered to farm families make continuing and developing farming more tempting.

Rural Income Generation and Diversification : A Case Study in Eastern Zambia

Rural income diversification has been found to be rather the norm than the exception in developing countries. Smallholder households tend to diversify their income sources because of the need to manage risks, secure a smooth flow of income, allocate surplus labour, respond to various kinds of market failures, and apply coping strategies. The Agricultural Household Model provides a theoretical rationale for income diversification in that rural households aim at maximising their utility. There are several elements involved, such as agricultural production for their own consumption and markets, leisure activities and income from non-farm sources. The aim of the present study is to enhance understanding of the processes of rural income generation and diversification in eastern Zambia. Specifically, it explores the relationship between household characteristics, asset endowments and income-generation patterns. According to the sustainable- rural-livelihoods framework, the assets a household possesses shape its capacity to seize new economic opportunities. The study is based on two surveys conducted among rural smallholder households in four districts of Eastern Province in Zambia in 1985/86 and 2003. Sixty-seven of the interviewed households were present in both surveys and this panel allows comparison between the two points of time. The initial descriptive analysis is complemented with an econometric analysis of the relationships between household assets and income sources. The results show that, on average, 30 per cent of the households income originated from sources outside their own agriculture. There was a slight increase in the proportion of non-farm income from 1985/86 to 2003, but total income clearly declined mainly on account of diminishing crop income. The land area the household was able to cultivate, which is often dependent on the available labour, was the most significant factor affecting both the household-income level and the diversification patterns. Diversification was, in most cases, a coping strategy rather than a voluntary choice. Measured as income/capita/day, all households were below the poverty line in 2003. The agricultural reforms in Zambia, combined with other trends such as changes in rainfall pattern, the worsening livestock situation and the incidence of human disease, had a negative impact on agricultural productivity and income between 1985/86 and 2003. Sources of non-farm income were closely linked to agriculture either upstream or downstream and the income they generated was not enough to compensate for the decline of agricultural income. Household assets and characteristics had a smaller impact on diversification patterns than expected, which could reflect the lack of opportunities in the remote rural environment.

O uso de planilha eletrônica na administracão rural: um modelo de custos de producão.

Planilha eletronica; O modelo "custo de producao".

Do Integrated Arable Farming Systems provide a more sustainable form of agricultural production: the UK case

Integrated Arable Farming Systems (IAFS) projects utilise a range of novel and different farming techniques, often associated with optimising or reducing the use of inputs. Here, data is presented from the LINK-IFS project which suggests that, although input levels are being reduced, the overall profitability of the system can be maintained. The effect of thus reduction in inputs, however, in terms of impact on key environmental indicators is unclear.

The Nebraska Agricultural Outlook for 1938

Each year the federal government gathers data relating to agriculture through the various departments of the United States Department of Agriculture. These data are classified and analyzed by the Bureau of Agricultural Economics at Washington and all information which may be helpful to farmers is published. For several years it has been the policy of the Department of Rural Economics and the Agricultural Extension Service of the College of Agriculture, Lincoln, to select from the federal information facts which may be especially helpful to Nebraska farmers. These facts and other economic conditions in Nebraska are published this year as the Agricultural Outlook for Nebraska, 1938. The Outlook should be helpful in the marketing of the crops and livestock on hand. It should also be helpful in making farm plans for 1938.

EC94-852 Cash Flow Planning Form

This extension circular covers the following areas of a cash flow planning form: Beginning Cash Balance, Operating Sales (crop and hay, market livestock, livestock product, custom work); Capital Sales (breeding livestock, machinery and equipment); Personal Income (wages, interest); Operating Expenses (car/truck, chemicals, conservation, custom hire, feed purchased, fertilizers and lime, freight and trucking, gasoline, fuel and oil, insurance, labor hired, rents and leases, repairs and maintenance, seeds and plants, storage, warehousing, supplies, taxes, utilities, veterinary, breeding fees and medicine, feeder livestock); Capital Purchases (breeding livestock, machinery and equipment, family living withdrawals, personal investments, income and social security, term loan payments); Net Cash Available (operating loan borrowings, operating loan payments); and Ending Operating Loan Balance. Along with the Cash Flow Planning Form is a Projected Income Statement Form which covers Projected Business Income (operating sales, breeding livestock, estimated cash income adjustments, estimated gross revenues, estimated value of production); Project Business Expenses (cash operating, esimated operating, prepaid and supplies, cash investment in growing crops, accounts payable); Projected Net Income Summary (estimated net income from operations, estimated net business income, estimated net income after taxes, estimated earned net worth change); and a Physical Inventory Flows Worksheet.

Optimization of bioenergy solutions at different farm scales

RAF is a bio-energetic descriptive model integrates with MAD model to support Integrated Farm Management. RAF model aimed to enhancing economical, social and environmental sustainability of farm production in terms of energy via convert energy crops and animal manure to biogas and digestate (bio-fertilizers) by anaerobic digestion technologies, growing and breeding practices. The user defines farm structure in terms of present crops, livestock and market prices and RAF model investigates the possibilities of establish on-farm biogas system (different anaerobic digestion technologies proposed for different scales of farms in terms of energy requirements) according to budget and sustainability constraints to reduce the dependence on fossil fuels. The objective function of RAF (Z) is optimizing the total net income of farm (maximizing income and minimizing costs) for whole period which is considered by the analysis. The main results of this study refers to the possibility of enhancing the exploitation of the available Italian potentials of biogas production from on-farm production of energy crops and livestock manure feedstock by using the developed mathematical model RAF integrates with MAD to presents reliable reconcile between farm size, farm structure and on-farm biogas systems technologies applied to support selection, applying and operating of appropriate biogas technology at any farm under Italian conditions.

Amadir: Livelihood and Resource Management in an Eritrean Highland Community: A development baseline

This publication presents the results of a study conducted in 2003 in Amadir, a village in the Central Highlands of Eritrea. It gives an overview of the natural resource base, livelihoods, farm management, and institutions that are important to the local community. The report concludes with a chapter on options for development as discussed with the village community and local administration. This report supports Eritrea's efforts to promote rural development. It contains an extensive summary in Tigrinya, as well as a large-scale satellite image and a large-scale land use map of the study area. The appendix presents a summary of the methods used in the study.

Non invasive moisture measurement in agricultural fiel using a rolling spherical robot

Irrigation management in large crop fields is a very important practice. Since the farm management costs and the crop results are directly connected with the environmental moisture, water control optimization is a critical factor for agricultural practices, as well as for the planet sustainability. Usually, the crop humidity is measured through the water stress index (WSI), using imagery acquired from satellites or airplanes. Nevertheless, these tools have a significant cost, lack from availability, and dependability from the weather. Other alternative is to recover to ground tools, such as ground vehicles and even static base stations. However, they have an outstanding impact in the farming process, since they can damage the cultivation and require more human effort. As a possible solution to these issues, a rolling ground robot have been designed and developed, enabling non-invasive measurements within crop fields. This paper addresses the spherical robot system applied to intra-crop moisture measurements. Furthermore, some experiments were carried out in an early stage corn field in order to build a geo-referenced WSI map.

Farm shop equipment : its usefulness on California farms /

Mode of access: Internet.

FM.

Title from cover.

Suggestions for analyzing farm enterprises and jobs,

Mode of access: Internet.

A guide in farm organization and operation,

Blank sheets included in pagination, are provided for notes.