Spatio-temporal variability of sugarcane yield efficiency in the state of Sao Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of Sao Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of Sao Paulo.

Spatio-temporal variability of sugarcane yield efficiency in the state of São Paulo, Brazil

The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

Approach to the potential production of giant reed in surplus saline lands of Spain

Growing energy crops on marginal land has been promoted as a way of ensuring that biomass production involves an acceptable and sustainable use of land. Saline and saline-prone agricultural lands represent an opportunity for growing energy crops avoiding the displacement of food production and contributing to restoration of degraded land. Giant reed (Arundo donax L.) is a perennial grass that has been proposed as a promising energy crop for lignocellulosic biomass production while its tolerance to salinity has been proved. In this work, the identification of surplus saline lands that could be irrigated with saline waters for growing tolerant-energy crops (giant reed) in the mainland of Spain and the assessment of the agronomically attainable yield in these limiting growing conditions were undertaken. To this purpose, a GIS analysis was conducted using geodatabases related to saline areas, agro-climatic conditions, irrigation water requirements, agricultural land availability, restrictions regarding the range of electrical conductivity tolerated by the crop, competition with agro-food crops and irrigation water provisions. According to the approach developed, the irrigated and saline agricultural area available and suitable for biomass production from giant reed amounted up to 34 412 ha. The agronomically attainable yield in these limiting conditions was estimated at 12.7 – 22.2 t dm ha−1 yr−1 and the potential production of lignocellulosic biomass, 597 338 t dm yr−1. The methodology followed in this study can be applied to other target regions; it allows the identification of this type of marginal lands, where salinity-tolerant plant species could be grown for bioenergy purposes, avoiding competition with agro-food crops, and where soil restoration measurements should be undertaken.

El Niño influence on potential maize yield in Iberian Peninsula

El Niño phenomenon is the leading mode of sea surface temperature interannual variability. It can affect weather patterns worldwide and therefore crop production. Crop models are useful tools for impact and predictability applications, allowing to obtain long time series of potential and attainable crop yield, unlike to available time series of observed crop yield for many countries. Using this tool, crop yield variability in a location of Iberia Peninsula (IP) has been previously studied, finding predictability from Pacific El Niño conditions. Nevertheless, the work has not been done for an extended area. The present work carries out an analysis of maize yield variability in IP for the whole twenty century, using a calibrated crop model at five contrasting Spanish locations and reanalyses climate datasets to obtain long time series of potential yield. The study tests the use of reanalysis data for obtaining only climate dependent time series of crop yield for the whole region, and to use these yield to analyze the influences of oceanic and atmospheric patterns. The results show a good reliability of reanalysis data. The spatial distribution of the leading principal component of yield variability shows a similar behaviour over all the studied locations in the IP. The strong linear correlation between El Niño index and yield is remarkable, being this relation non-stationary on time, although the air temperature-yield relationship remains on time, being the highest influences during grain filling period. Regarding atmospheric patterns, the summer Scandinavian pattern has significant influence on yield in IP. The potential usefulness of this study is to apply the relationships found to improving crop forecasting in IP.

Yield-factor volatility models

The term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve. In this paper, we develop a comprehensive model for volatility dynamics in the level, slope, and curvature of the yield curve that simultaneously includes level and GARCH effects along with regime shifts. We show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant GARCH effects present even after including a level effect. Further, we find that allowing for regime shifts in the factor volatilities dramatically improves the model’s fit and strengthens the level effect. We also show that a regime-switching model with level and GARCH effects provides the best out-of-sample forecasting performance of yield volatility. We argue that the auxiliary models often used to estimate term structure models with simulation-based estimation techniques should be consistent with the main features of the yield curve that are identified by our model.

Cultivar-specific effects of pathogen testing on storage root yield of sweet potato, Ipomoea batatas (L.) Lam.

The accumulation and perpetuation of viral pathogens over generations of clonal propagation in crop species such as sweet potato, Ipomoea batatas,inevitably result in a reduction in crop yield and quality. This study was conducted at Bundaberg, Australia to compare the productivity of field-derived and pathogen-tested (PT)clones of 14 sweet potato cultivars and the yield benefits of using healthy planting materials. The field-derived clonal materials were exposed to the endemic viruses, while the PT clones were subjected to thermotherapy and meristem-tip culture to eliminate viral pathogens. The plants were indexed for viruses using nitrocellulose membrane-enzyme-linked immunosorbent assay and graft-inoculations onto Ipomoea setosa. A net benefit of 38% in storage root yield was realised from using PT materials in this study.Conversely, in a similar study previously conducted at Kerevat, Papua New Guinea (PNG), a net deficit of 36% was realised. This reinforced our finding that the response to pathogen testing was cultivar dependent and that the PNG cultivars in these studies generally exhibited increased tolerance to the endemic viruses present at the respective trial sites as manifested in their lack of response from the use of PT clones. They may be useful sources for future resistance breeding efforts. Nonetheless, the potential economic gain from using PT stocks necessitates the use of pathogen testing on virus-susceptible commercial cultivars.

Manufacturing Yield Improvement by Clustering

Dealing with product yield and quality in manufacturing industries is getting more difficult due to the increasing volume and complexity of data and quicker time to market expectations. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large databases. Growing self-organizing map (GSOM) is established as an efficient unsupervised datamining algorithm. In this study some modifications to the original GSOM are proposed for manufacturing yield improvement by clustering. These modifications include introduction of a clustering quality measure to evaluate the performance of the programme in separating good and faulty products and a filtering index to reduce noise from the dataset. Results show that the proposed method is able to effectively differentiate good and faulty products. It will help engineers construct the knowledge base to predict product quality automatically from collected data and provide insights for yield improvement.