The role of inventory adjustments in quantifying factors causing food price inflation

The food commodity price increases beginning in 2001 and culminating in the food crisis of 2007/08 reflected a combination of several factors, including economic growth, biofuel expansion, exchange rate fluctuations, and energy price inflation. To quantify these influences, the authors developed an empirical model that also included crop inventory adjustments. The study shows that, if inventory effects are not taken into account, the impacts of the various factors on food commodity price inflation would be overestimated. If the analysis ignores crop inventory adjustments, it indicates that prices of corn, soybean, rapeseed, rice, and wheat would have been, respectively, 42, 38, 52, and 45 percent lower than the corresponding observed prices in 2007. If inventories are properly taken into account, the contributions of the above mentioned factors to those commodity prices are 36, 26, 26, and 35 percent, respectively. Those four factors, taken together, explain 70 percent of the price increase for corn, 55 percent for soybean, 54 percent for wheat, and 47 percent for rice during the 2001-2007 period. Other factors, such as speculation, trade policy, and weather shocks, which are not included in the analysis, might be responsible for the remaining contribution to the food commodity price increases.Markets and Market Access,Economic Theory&Research,Food&Beverage Industry,Access to Markets,Currencies and Exchange Rates

Optimal Crop Plans for Sustainable Water Use in Punjab

A linear programming model has been formulated to suggest the optimal cropping pattern for maximizing net returns and ensuring significant savings of groundwater with the aim of sustaining groundwater use in the Punjab agriculture. The primary data obtained from the project, “Comprehensive scheme to study the cost of cultivation of principal crops in Punjab†for the year 2002-03 pertain to 170 farmers selected through three-stage stratified random sampling technique. As the period of transplantation of paddy has a significant bearing on the amount of groundwater used and its sustainability, the paddy crop has been further classified into Paddy 1 (transplanted before 10th June); Paddy 2 (transplanted during 11th June to 20th June) and Paddy 3 (transplanted after 20th June). At the existing level of water availability, the optimal crop plan has not revealed any significant changes in the production pattern. Restricting the availability of groundwater has resulted into a major shift in the cropping pattern. Such changes could ensure groundwater savings of almost 25 per cent, without any adverse impact on the net returns from crop production. Introduction of new crops in the production plan, such as Bt cotton, has further enhanced the returns from crop production by about 4 per cent along with groundwater savings of 26.55 per cent. The study has suggested that alternate wetting and drying, adoption of system of rice intensification (SRI), use of tensiometers and direct plantation of paddy are some of the other techniques which can save water.Agricultural and Food Policy,

Variabilidade espacial e temporal dos atributos do solo e sua relação com a produtividade agrícola, parâmetros topográficos e condutividade elétrica aparente (CEa) em lavouras de cana-de-açúcar

Orientador: Paulo Sérgio Graziano MagalhãesTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de AlimentosResumo: A produção de etanol no Brasil deverá ser de 54 bilhões de litros em 2030 para atender ao acordo firmado na COP21, o que representa o dobro da produção de etanol verificada em 2016. Do ponto de vista agronômico há duas alternativas: ou aumenta-se a área plantada com a cultura ou aumenta-se a produtividade por área. Ambientalmente não há dúvidas que o aumento da produtividade é a melhor alternativa, sendo que a agricultura de precisão (AP) será fundamental para contribuir com a sustentabilidade da produção. Atualmente a AP nas lavouras de cana-de-açúcar no Brasil está longe do potencial que as tecnologias disponíveis podem proporcionar para o manejo adequado da cultura. O principal objetivo da presente tese é demonstrar como as tecnologias de PA, mais especificamente, monitores de rendimento, parâmetros topográficos e sensores de condutividade elétrica aparente (CEa), podem ajudar os agricultores a gerenciar os campos de forma específica do local. Para tanto, os atributos do solo que impactam diretamente a produtividade das culturas foram avaliados espacial e temporalmente, associando esses elementos do solo com parâmetros topográficos e CEa. Os objetivos são fornecer indicadores qualitativos e quantitativos para uma caracterização espacial precisa dos campos, mostrando o potencial dos parâmetros topográficos e CEa para melhorar o manejo específico do local dos campos de cana-de-açúcar. Para aumentar a produtividade, os resultados mostraram que a matéria orgânica (MO) disponível no solo, teor de argila e capacidade de troca catiônica (CTC) são os fatores que impactam diretamente a produtividade da cana-de-açúcar. Além disso, a variabilidade temporal na produtividade foi causada principalmente pela variabilidade no pH do solo. Uma avaliação abrangente da variabilidade espacial dos atributos do solo relacionados aos parâmetros topográficos evidenciou padrões espaciais que foram temporalmente remanescentes. Os resultados mostraram que as classes morfométricas horizontais (HConv, HPlan e HDiv), associadas às áreas côncavas (Vconc), apresentaram maiores teores de MO, Soma de Bases (SB) e CTC, indicando que essas áreas apresentam maior fertilidade do solo, onde a formação VConcHDiv apresentou a maior fertilidade do solo. Para todas as classes morfométricas verticais (VConc, VRet e VConv), os níveis de pH do solo foram maiores quando associados a áreas divergentes (HDiv) e menores quando associados a áreas convergentes (HConv), sugerindo um manejo mais rigoroso da acidez do solo nas áreas HConv. As áreas VConvHConv, onde a menor fertilidade do solo foi observada, devem ser amostradas com maior acurácia para adequada caracterização espacial do solo, devido ao alto Coeficiente de Variação (CV) observado quando comparado a outras classes morfométricas avaliadas. Além disso, as classes de CEa, divididas pelo método do quantil, mostraram que os locais de menor condutividade elétrica apresentam menores teores de MO e CTC. As classes de CEa mais altas mostraram CV menor para todos os atributos do solo avaliados, ou seja, locais que podem ser caracterizados com menores quantidades de amostras para um mapeamento de solo adequado. A variabilidade do conteúdo de argila foi diretamente proporcional à variabilidade da CEa (R2 = 0,97). MO (R2 = 0,65) e CTC (R2 = 0,76) também apresentaram boa correlação com a variabilidade da CEa. Com alta estabilidade espacial e temporal, os parâmetros topográficos e da CEa são excelentes fontes de informação (economicamente viáveis e de fácil avaliação) para apoiar os processos de amostragem do solo e mapear as zonas de fertilidade nos camposAbstract: The ethanol production should be 54 billion liters in 2030, almost double of the current production. From the agronomic point of view, two alternatives are possible; increase the planted area and/or agricultural yield to reach the goals. Environmentally, increase the yield is a more sustainable option, and the adoption of Precision Agriculture (PA) will be essential. The current use of PA in Brazilian sugarcane industry is very far from its full potential. The main objective of the present thesis is to demonstrate how PA technologies, more specifically yield monitors, topographic parameters and apparent electrical conductivity (ECa) sensors, can help farmers to manage fields in a site-specific way. For this purpose, soil attributes that directly impact crop yield were spatially and temporally evaluated, associating these soil elements with topographic and ECa parameters. The aims are to provide qualitative and quantitative indicators for a precise soil spatial characterization of fields, showing the potential of topographic and ECa parameters to improve the site-specific management of sugarcane fields. To increase the yield, the findings showed that the amount of available soil organic matter (OM), clay content and cation exchange capacity (CEC) are important factors that directly impact sugarcane yield. Furthermore, the temporal variability in the yield is caused mainly by the variability in the soil pH. A comprehensive assessment of the spatial variability of soil attributes related to topographic parameters evidencing spatial patterns that were temporally remained. The results showed that the horizontal morphometric classes (HConv, HPlan and HDiv), associated with vertical concave areas (VConc), presented higher levels of OM, Sum of Bases (SB) and CEC, which indicated that these areas have higher soil fertility, where VConcHDiv showed the highest soil fertility. For all vertical morphometric classes (VConc, VRet and VConv), soil pH levels were higher when associated with horizontal divergent areas (HDiv) and lower when associated with convergent areas (HConv), suggesting that stricter soil acidity management was needed in the HConv areas. The VConvHConv areas, where the lower soil fertility was observed, should be sampled with greater accuracy for adequate soil spatial characterization due to the high CV observed when compared to other morphometric classes assessed. Furthermore, ECa classes, defined by quantil method, showed that the low electrical conductivity sites present lower OM and CEC contents. The higher ECa classes showed smaller CV for all soil attributes assessed, i.e., sites that can be characterized with smaller amounts of samples to an adequate soil mapping than lower ECa classes. The clay content variability was directly proportional to the ECa variability (R2 = 0.97). OM (R2 = 0.65) and CEC (R2 = 0.76) showed great correlation with ECa variability too. With high spatial and temporal stability, topographic and ECa parameters could be excellent (economically feasible and easily assessed) sources of information to support soil sampling processes and to map fertility zones within fieldsDoutoradoBioenergiaDoutor em Ciências2014/14965-0FAPES

Macro-micro feedback links of water management in South Africa : CGE analyses of selected policy regimes

The pressure on an already stressed water situation in South Africa is predicted to increase significantly under climate change, plans for large industrial expansion, observed rapid urbanization, and government programs to provide access to water to millions of previously excluded people. The present study employed a general equilibrium approach to examine the economy-wide impacts of selected macro and water related policy reforms on water use and allocation, rural livelihoods, and the economy at large. The analyses reveal that implicit crop-level water quotas reduce the amount of irrigated land allocated to higher-value horticultural crops and create higher shadow rents for production of lower-value, water-intensive field crops, such as sugarcane and fodder. Accordingly, liberalizing local water allocation in irrigation agriculture is found to work in favor of higher-value crops, and expand agricultural production and exports and farm employment. Allowing for water trade between irrigation and non-agricultural uses fueled by higher competition for water from industrial expansion and urbanization leads to greater water shadow prices for irrigation water with reduced income and employment benefits to rural households and higher gains for non-agricultural households. The analyses show difficult tradeoffs between general economic gains and higher water prices, making irrigation subsidies difficult to justify.Water Supply and Sanitation Governance and Institutions,Town Water Supply and Sanitation,Water Supply and Systems,Water and Industry,Water Conservation

Within-Field Yield Prediction for Sugarcane and Rice Focused on Precision Agriculture Applications

Food and energy security are two main topics when it comes to the on-growing world population. Rice and sugarcane play an important role in this scenario since sugarcane can be used for energy production and rice is one of major staple cereals. In this scenario, Precision Agriculture (PA) management strategies aims to improve productivity, efficiency, profitability, and sustainability, and can help agriculture to fulfill the needs of the growing population in a sustainable way. However, yield maps are essential for PA, but its adoption is still very low. Thus, the main objective of this study was to evaluate the potential of satellite imagery and machine learning to predict yield maps that could support the adoption of precision agriculture practices for rice and sugarcane. Consequently, a framework for the data processing, imagery acquisition and machine learning model generation, was proposed and tested. The results presented a high potential for the usage of those techniques, generating yield maps very similar to the ones obtained from yield monitors (RMSE for rice of 0.9Mg.ha-1 and for sugarcane 3.14Mg.ha-1). Also, in-season yield map prediction was evaluated for rice and sugarcane. Therefore, the prediction was performed for different growth stages by stacking all the images until a specific date. Sugarcane maps were obtained with a satisfactory accuracy early in the season (May-June) (no statistical significance when compared to the predicted maps of the end of the season) whilst for rice the yield maps with the lowest errors were only obtained late in the season. Therefore, sugarcane maps obtained early in the season could be used for in-season management of the crop. On the other hand, the in-season applicability for rice yield maps were limited since accurate maps were obtained at late ripening. However, this information could still be used for harvest planning and nitrogen application on the second harvest of Louisiana’s rice. In general, the framework proposed presented a high potential to be used for yield maps prediction. Furthermore, yield maps, an important tool for PA, were obtained with low errors RMSE of 0.83 and 3.14 Mg.ha-1 for rice and sugarcane, respectively

Conflict, food insecurity, and globalization:

"We explore how globalization, broadly conceived to include international humanrights norms, humanitarianism, and alternative trade, might influence peaceful and foodsecure outlooks and outcomes. The paper draws on our previous work on conflict as a cause and effect of hunger and also looks at agricultural exports as war commodities. We review studies on the relationships between (1) conflict and food insecurity, (2) conflict and globalization, and (3) globalization and food insecurity. Next, we analyze countrylevel, historical contexts where export crops, such as coffee and cotton, have been implicated in triggering and perpetuating conflict. These cases suggest that it is not export cropping per se, but production and trade structures and food and financial policy contexts that determine peaceful or belligerent outcomes. Export cropping appears to contribute to conflict when fluctuating prices destabilize household and national incomes and when revenues fund hostilities. Also, in these scenarios, governments have not taken steps to progressively realize the right to adequate food or to reduce hunger and poverty. We conclude by exploring implications for agricultural development, trade, and human rights policies." Authors' AbstractHunger, Conflict, war, Globalization, Crops, exports, coffee, Cotton, Human rights, Right to food, Fair trade,

Precision production environments for sugarcane fields

Sugarcane (saccharum spp.) in Brazil is managed on the basis of “production environments”. These “production environments” are used for many purposes, such as variety allocation, application of fertilizers and definition of the planting and harvesting periods. A quality classification is essential to ensure high economic returns. However, the classification is carried out by few and, most of the time, non-representative soil samples, showing unreal local conditions of soil spatial variability and resulting in classifications that are imprecise. One of the important tools in the precision agriculture technological package is the apparent electrical conductivity (ECa) sensors that can quickly map soil spatial variability with high-resolution and at low-cost. The aim of the present work was to show that soil ECa maps are able to assist classification of the "production environments" in sugarcane fields and rapidly and accurately reflect the yield potential. Two sugarcane fields (35 and 100 ha) were mapped with an electromagnetic induction sensor to measure soil ECa and were sampled by a dense sampling grid. The results showed that the ECa technique was able to reflect mainly the spatial variability of the clay content, evidencing regions with different yield potentials, guiding soil sampling to soil classification that is both more secure and more accurate. Furthermore, ECa allowed for more precise classification, where new “production environments”, different from those previously defined by the traditional sampling methods, were revealed. Thus, sugarcane growers will be able to allocate suitable varieties and fertilize their agricultural fields in a coherent way with higher quality, guaranteeing greater sustainability and economic return on their production