Evaluation of the Doraiswamy-Thompson winter wheat crop calendar model incorporating a modified spring restart sequence

The Robertson phenology was used to provide growth stage information to a wheat stress indicator mode. A stress indicator model demands two acurate predictions from a crop calendar: date of spring growth initiation; and crop calendar stage at growth initiation. Several approaches for restarting the Robertson phenology model at spring growth initiation were studied. Although best results were obtained with a solar thermal unit method, an alternate approach which indicates soil temperature as the controlling parameter for spring growth initiation was selected and tested. The modified model (Doraiswamy-Thompson) is compared to LACIE-Robertson model predictions

An evaluation of the signature extension approach to large area crop inventories utilizing space image data

The author has identified the following significant results. Two examples of haze correction algorithms were tested: CROP-A and XSTAR. The CROP-A was tested in a unitemporal mode on data collected in 1973-74 over ten sample segments in Kansas. Because of the uniformly low level of haze present in these segments, no conclusion could be reached about CROP-A's ability to compensate for haze. It was noted, however, that in some cases CROP-A made serious errors which actually degraded classification performance. The haze correction algorithm XSTAR was tested in a multitemporal mode on 1975-76 LACIE sample segment data over 23 blind sites in Kansas and 18 sample segments in North Dakota, providing wide range of haze levels and other conditions for algorithm evaluation. It was found that this algorithm substantially improved signature extension classification accuracy when a sum-of-likelihoods classifier was used with an alien rejection threshold

Small-scale farming diversity and bioeconomic environment variability : a modelling approach. Sub theme : 1.2. Integration of micro-strategies with macro-economic factors

Modelling is seen by many scientists as a powerful tool to assess the interaction between variability in the bioeconomic environment of small-scale farmers and their resource management strategies. Two case studies on small-scale farming in Mexican and Brazilian savannas are presented. On one hand, the effect of climate variability on crop yields is highly dependent of the managing techniques used. On the other hand, the variability of prices, resulting in Mexico's case from the establishment of NAFTA and, in the Brazilian case, from the "-plano Real," dramatically increases the uncertainty of the economic results linked to technical choices. Modelling the real conditions of such farmer decisions requires integrating of both biophysical and economical knowledge. This work analyses the characteristics required for such models and ways to integrate them. It appears that the building and scaling up of the models should be driven by results of a study on farming system diversity

Labor Cost and Value of Citrus Operations with Alternative Technology: Enterprise DCF Approach

The prospect of immigration policy reform has renewed growers’ concerns of serious labor shortages and cost increases given that a large portion of the workforce is unauthorized for U.S. employment. This concern of labor shortages and cost increases is more serious for specialty crop agriculture which is highly labor intensive. Specialty crop growers may address the problem in various ways, but likely options include adoption of mechanical harvesting. In the current paper we study the citrus industry case and estimate the value for two operational modes (hand and mechanical harvesting) using the enterprise discounted cash flow (DCF) approach. Further we implement a simulation to forecast how the value for each operational mode would change with a change in cost scenario.Value, Enterprise DCF approach, Labor cost, Citrus operations, Mechanization, Agricultural Finance, Labor and Human Capital, Q14, J43,

Plant Products as Biopesticides: Building On Traditional Knowledge of Vrkshayurveda: Traditional Indian Plant Science

Today there is a global search for alternatives to chemical pesticides and as part of this process there are various efforts to test the use and efficacy of natural products for pest control and crop protection. Our Centre has been involved in exploring the traditional knowledge regarding the use of natural products for pest control and crop protection. As part of this effort, we have looked at the traditional folk practices prevalent among farmers as well as information from classical literature on the subject drawn from Vrkshayurveda (traditional Indian plant science). Following this, we have carried out experiments for standardizing and field testing promising natural products by determining the precise range and kind of pests controlled by them, determining the optimum concentration where they can be effective against pests without being harmful to useful organisms and predators as well as studying their mode of action. Subsequently, we have also developed storage forms of various of these products by using methods based on Ayurveda. Studies on the stability and shelf life of these products are also being carried out through an insect rearing laboratory. Finally, we have also set up village based biopesticides units where a range of these products are being prepared thus providing valuable inputs to sustainable agriculture and a means of livelihood to rural women and farmers

Solar dryer with thermal storage and biomass-backup heater

An indirect type natural convection solar dryer with integrated collector-storage solar and biomass backup heaters has been designed, constructed and evaluated. The major components of the dryer are biomass burner (with a rectangular duct and flue gas chimney), collector-storage thermal mass and drying chamber (with a conventional solar chimney). The thermal mass was placed in the top part of the biomass burner enclosure. The dryer was fabricated using simple materials, tools and skills, and it was tested in three modes of operation (solar, biomass and solar-biomass) by drying twelve batches of fresh pineapple (Ananas comosus), with each batch weighing about 20 kg. Meteorological conditions were monitored during the dehydration process. Moisture and vitamin C contents were determined in both fresh and dried samples. Results show that the thermal mass was capable of storing part of the absorbed solar energy and heat from the burner. It was possible to dry a batch of pineapples using solar energy only on clear days. Drying proceeded successfully even under unfavorable weather conditions in the solar-biomass mode of operation. In this operational mode, the dryer reduced the moisture content of pineapple slices from about 669 to 11% (db) and yielded a nutritious dried product. The average values of the final-day moisture-pickup efficiency were 15, 11 and 13 % in the solar, biomass and solar-biomass modes of operation respectively. It appears that the solar dryer is suitable for preservation of pineapples and other fresh foods. Further improvements to the solar chimney design are suggested to avert reverse thermosiphoning at night or during periods of low insolation

Ethnobotanical survey of pesticidal plants used in South Uganda : case study of Masaka district

Use of synthetic pesticides in developing countries is not only limited by their being expensive but also the small (uneconomic) fields whose limited production costs cannot offset costs of agricultural implements like agro-chemicals. Subsistence farmers, therefore, have no choice but to use local methods of controlling pests, one of which is the use of traditional and of late introduced pesticidal plants' extracts. In this study, whose main objective was to record all pesticidal plants used in Southern Uganda, Masaka district, it was established that thirty four species belonging to eighteen families are currently used in traditional plant production. Most useful species were Azadirachta indica and Tagetes minuta while the most frequently cited families were Meliaceae and Euphorbiaceae. It was noted that of the plant species recorded, some plants like A. indica, Melia azedarach, and T. minuta are already scientifically established pesticidal plants whereas others like Euphorbia tirucalli, Bidens pilosa, Vernonia amygdalina may be known for other uses but not for this purpose and hence the need for their efficacy evaluation. Some important pesticidal plants like Abrus precatorius, Euphorbia candelabrum and Phoenix reclinata were reportedly becoming increasingly rare and would need conservation. The need to carry out such surveys in order to obtain inventories was observed and recording this knowledge before it disappears with the aging farmers was seen as urgent

Method and apparatus for bio-regenerative life support system

A life support system is disclosed for human habitation (cabin) which has a bioregenerative capability through the use of a plant habitat (greenhouse) whereby oxygen-rich air from the greenhouse is processed and used in the cabin and carbon dioxide-rich air from the cabin is used in the greenhouse. Moisture from the air of both cabin and greenhouse is processed and reused in both. Wash water from the cabin is processed and reused in the cabin as hygiene water, and urine from the cabin is processed and used in the greenhouse. Spent water from the greenhouse is processed and reused in the greenhouse. Portions of the processing cycles are separated between cabin and greenhouse in order to reduce to a minimum cross contamination of the two habitat systems. Other portions of the processing cycles are common to both cabin and greenhouse. The use of bioregenerative techniques permits a substantial reduction of the total consumables used by the life support system

Temporal and Spatial Data Mining with Second-Order Hidden Models

In the frame of designing a knowledge discovery system, we have developed stochastic models based on high-order hidden Markov models. These models are capable to map sequences of data into a Markov chain in which the transitions between the states depend on the \texttt{n} previous states according to the order of the model. We study the process of achieving information extraction fromspatial and temporal data by means of an unsupervised classification. We use therefore a French national database related to the land use of a region, named Teruti, which describes the land use both in the spatial and temporal domain. Land-use categories (wheat, corn, forest, ...) are logged every year on each site regularly spaced in the region. They constitute a temporal sequence of images in which we look for spatial and temporal dependencies. The temporal segmentation of the data is done by means of a second-order Hidden Markov Model (\hmmd) that appears to have very good capabilities to locate stationary segments, as shown in our previous work in speech recognition. Thespatial classification is performed by defining a fractal scanning ofthe images with the help of a Hilbert-Peano curve that introduces atotal order on the sites, preserving the relation ofneighborhood between the sites. We show that the \hmmd performs aclassification that is meaningful for the agronomists.Spatial and temporal classification may be achieved simultaneously by means of a 2 levels \hmmd that measures the \aposteriori probability to map a temporal sequence of images onto a set of hidden classes