Yield gap analysis and assessment of climate-induced yield trends of irrigated rice in selected provinces of the Philippines

This study describes a combined empirical/modeling approach to assess the possible impact of climate variability on rice production in the Philippines. We collated climate data of the last two decades (1985-2002) as well as yield statistics of six provinces of the Philippines, selected along a North-South gradient. Data from the climate information system of NASA were used as input parameters of the model ORYZA2000 to determine potential yields and, in the next steps, the yield gaps defined as the difference between potential and actual yields. Both simulated and actual yields of irrigated rice varied strongly between years. However, no climate-driven trends were apparent and the variability in actual yields showed no correlation with climatic parameters. The observed variation in simulated yields was attributable to seasonal variations in climate (dry/wet season) and to climatic differences between provinces and agro-ecological zones. The actual yield variation between provinces was not related to differences in the climatic yield potential but rather to soil and management factors. The resulting yield gap was largest in remote and infrastructurally disfavored provinces (low external input use) with a high production potential (high solar radiation and day-night temperature differences). In turn, the yield gap was lowest in central provinces with good market access but with a relatively low climatic yield potential. We conclude that neither long-term trends nor the variability of the climate can explain current rice yield trends and that agroecological, seasonal, and management effects are over-riding any possible climatic variations. On the other hand the lack of a climate-driven trend in the present situation may be superseded by ongoing climate change in the future.

Avaliação, empregando simulação, da diferença na produtividade (yield gap) do milho em Minas Gerais.

2016

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.

Probabilistic simulations of crop yield over western India using the DEMETER seasonal hindcast ensembles

Process-based integrated modelling of weather and crop yield over large areas is becoming an important research topic. The production of the DEMETER ensemble hindcasts of weather allows this work to be carried out in a probabilistic framework. In this study, ensembles of crop yield (groundnut, Arachis hypogaea L.) were produced for 10 2.5 degrees x 2.5 degrees grid cells in western India using the DEMETER ensembles and the general large-area model (GLAM) for annual crops. Four key issues are addressed by this study. First, crop model calibration methods for use with weather ensemble data are assessed. Calibration using yield ensembles was more successful than calibration using reanalysis data (the European Centre for Medium-Range Weather Forecasts 40-yr reanalysis, ERA40). Secondly, the potential for probabilistic forecasting of crop failure is examined. The hindcasts show skill in the prediction of crop failure, with more severe failures being more predictable. Thirdly, the use of yield ensemble means to predict interannual variability in crop yield is examined and their skill assessed relative to baseline simulations using ERA40. The accuracy of multi-model yield ensemble means is equal to or greater than the accuracy using ERA40. Fourthly, the impact of two key uncertainties, sowing window and spatial scale, is briefly examined. The impact of uncertainty in the sowing window is greater with ERA40 than with the multi-model yield ensemble mean. Subgrid heterogeneity affects model accuracy: where correlations are low on the grid scale, they may be significantly positive on the subgrid scale. The implications of the results of this study for yield forecasting on seasonal time-scales are as follows. (i) There is the potential for probabilistic forecasting of crop failure (defined by a threshold yield value); forecasting of yield terciles shows less potential. (ii) Any improvement in the skill of climate models has the potential to translate into improved deterministic yield prediction. (iii) Whilst model input uncertainties are important, uncertainty in the sowing window may not require specific modelling. The implications of the results of this study for yield forecasting on multidecadal (climate change) time-scales are as follows. (i) The skill in the ensemble mean suggests that the perturbation, within uncertainty bounds, of crop and climate parameters, could potentially average out some of the errors associated with mean yield prediction. (ii) For a given technology trend, decadal fluctuations in the yield-gap parameter used by GLAM may be relatively small, implying some predictability on those time-scales.

Yield potential and resource-use efficiency of maize systems in the western U.S. Corn Belt

Maize demand for food, livestock feed, and biofuel is expected to increase substantially. The Western U.S. Corn Belt accounts for 23% of U.S. maize production, and irrigated maize accounts for 43 and 58% of maize land area and total production, respectively, in this region. The most sensitive parameters (yield potential [YP], water-limited yield potential [YP-W], yield gap between actual yield and YP, and resource-use efficiency) governing performance of maize systems in the region are lacking. A simulation model was used to quantify YP under irrigated and rainfed conditions based on weather data, soil properties, and crop management at 18 locations. In a separate study, 5-year soil water data measured in central Nebraska were used to analyze soil water recharge during the non-growing season because soil water content at sowing is a critical component of water supply available for summer crops. On-farm data, including yield, irrigation, and nitrogen (N) rate for 777 field-years, was used to quantify size of yield gaps and evaluate resource-use efficiency. Simulated average YP and YP-W were 14.4 and 8.3 Mg ha-1, respectively. Geospatial variation of YP was associated with solar radiation and temperature during post-anthesis phase while variation in water-limited yield was linked to the longitudinal variation in seasonal rainfall and evaporative demand. Analysis of soil water recharge indicates that 80% of variation in soil water content at sowing can be explained by precipitation during non-growing season and residual soil water at end of previous growing season. A linear relationship between YP-W and water supply (slope: 19.3 kg ha-1 mm-1; x-intercept: 100 mm) can be used as a benchmark to diagnose and improve farmer’s water productivity (WP; kg grain per unit of water supply). Evaluation of data from farmer’s fields provides proof-of-concept and helps identify management constraints to high levels of productivity and resource-use efficiency. On average, actual yields of irrigated maize systems were 11% below YP. WP and N-fertilizer use efficiency (NUE) were high despite application of large amounts of irrigation water and N fertilizer (14 kg grain mm-1 water supply and 71 kg grain kg-1 N fertilizer). While there is limited scope for substantial increases in actual average yields, WP and NUE can be further increased by: (1) switching surface to pivot systems, (2) using conservation instead of conventional tillage systems in soybean-maize rotations, (3) implementation of irrigation schedules based on crop water requirements, and (4) better N fertilizer management.

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.

An application of the DEA double bootstrap to examine sources of efficiency in Bangladesh rice farming

In this article we examine sources of technical efficiency for rice farming in Bangladesh. The motivation for the analysis is the need to close the rice yield gap to enable food security. We employ the DEA double bootstrap of Simar and Wilson (2007) to estimate and explain technical efficiency. This technique overcomes severe limitations inherent in using the two-stage DEA approach commonly employed in the efficiency literature. From a policy perspective our results show that potential efficiency gains to reduce the yield gap are greater than previously found. Statistically positive influences on technical efficiency are education, extension and credit, with age being a negative influence.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.

The geography of large-scale land acquisitions: Analysing socio-ecological patterns of target contexts in the global South

This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

Photosynthetic responses of four tropical tree species grown under gap and understorey conditions in a semi-deciduous forest

Leaf CO2 assimilation (A) as a function of photosynthetic photon flux density (Q) or intercellular CO2 concentration (Ci) and chlorophyll fluorescence measurements were carried out on four tropical woody species growing in forest gap and understorey (Bauhinia forficata Link. and Guazuma ulmifolia Lam. as pioneers, and Hymenaea courbaril L. and Esenbeckia leiocarpa Engl. as non-pioneers). Chlorophyll fluorescence indicated similar acclimation capacities of photochemical apparatus to contrasting light environments irrespective to plant species. Maximum CO2 assimilation and quantum yield derived from A/Q curves indicated higher photosynthetic capacity in pioneer than in non-pioneer species in forest gap. However, the differences among species did not show a straightforward relation with their successional status regarding data derived from A/Q curves under understorey conditions. Both successional groups are able to sustain positive carbon balance under contrasting natural light availabilities, modifying photochemical and biochemical photosynthetic traits with similar phenotypic plasticity capacity.

Effects of Organic and Inorganic Fertilizers on Growth and Yield of Banana (Musa AAA cv. Malindi) in Oman

The Sultanate of Oman is located on the south-eastern coast of the Arabian Peninsula, which lies on the south-western tip of the Asian continent. The strategic geographical locations of the Sultanate with its many maritime ports distributed on the Indian Ocean have historically made it one of the Arabian Peninsula leaders in the international maritime trade sector. Intensive trading relationships over long time periods have contributed to the high plant diversity seen in Oman where agricultural production depends entirely on irrigation from groundwater sources. As a consequence of the expansion of the irrigated area, groundwater depletion has increased, leading to the intrusion of seawater into freshwater aquifers. This phenomenon has caused water and soil salinity problems in large parts of the Al-Batinah governorate of Oman and threatens cultivated crops, including banana (Musa spp.). According to the Ministry of Agriculture and Fisheries, the majority of South Al-Batinah farms are affected by salinity (ECe > 4 dS m-1). As no alternative farmland is available, the reclamation of salt-affected soils using simple cultural practices is of paramount importance, but in Oman little scientific research has been conducted to develop such methods of reclamation. This doctoral study was initiated to help filling this research gap, particularly for bananas. A literature review of the banana cultivation history revealed that the banana germplasm on the Arabian Peninsula is probably introduced from Indonesia and India via maritime routes across the Indian Ocean and the Red Sea. In a second part of this dissertation, two experiments are described. A laboratory trial conducted at the University of Kassel, in Witzenhausen, Germany from June to July 2010. This incubation experiment was done to explore how C and N mineralization of composted dairy manure and date palm straw differed in alkaline non-saline and saline soils. Each soil was amended with four organic fertilizers: 1) composted dairy manure, 2) manure + 10% date palm straw, 3) manure + 30% date palm straw or 4) date palm straw alone, in addition to un-amended soils as control. The results showed that the saline soil had a lower soil organic C content and microbial biomass C than the non-saline soil. This led to lower mineralization rates of manure and date palm straw in the saline soil. In the non-saline soil, the application of manure and straw resulted in significant increases of CO2 emissions, equivalent to 2.5 and 30% of the added C, respectively. In the non-amended control treatment of the saline soil, the sum of CO2-C reached only 55% of the soil organic C in comparison with the non-saline soil. In which 66% of the added manure and 75% of the added straw were emitted, assuming that no interactions occurred between soil organic C, manure C and straw C during microbial decomposition. The application of straw always led to a net N immobilization compared to the control. Salinity had no specific effect on N mineralization as indicated by the CO2-C to Nmin ratio of soil organic matter and manure. However, N immobilization was markedly stronger in the saline soil. Date palm straw strongly promoted saprotrophic fungi in contrast to manure and the combined application of manure and date palm straw had synergistic positive effects on soil microorganisms. In the last week of incubation, net-N mineralization was observed in nearly all treatments. The strongest increase in microbial biomass C was observed in the manure + straw treatment. In both soils, manure had no effect on the fungi-specific membrane component ergosterol. In contrast, the application of straw resulted in strong increases of the ergosterol content. A field experiment was conducted on two adjacent fields at the Agricultural Research Station, Rumais (23°41’15” N, 57°59’1” E) in the South of Al-Batinah Plain in Oman from October 2007 to July 2009. In this experiment, the effects of 24 soil and fertilizer treatments on the growth and productivity of Musa AAA cv. 'Malindi' were evaluated. The treatments consisted of two soil types (saline and amended non-saline), two fertilizer application methods (mixed and ring applied), six fertilizer amendments (1: fresh dairy manure, 2: composted dairy manure, 3: composted dairy manure and 10% date palm straw, 4: composted dairy manure and 30% date palm straw, 5: only NPK, and 6: NPK and micronutrients). Sandy loam soil was imported from another part of Oman to amended the soil in the planting holes and create non-saline conditions in the root-zone. The results indicate that replacing the saline soil in the root zone by non-saline soil improved plant growth and yield more than fertilizer amendments or application methods. Particularly those plants on amended soil where NPK was applied using the ring method and which received micronutrients grew significantly faster to harvest (339 days), had a higher average bunch weight (9.5 kg/bunch) and were consequently more productive (10.6 tonnes/hectare/cycle) compared to the other treatments.

Photoinduced hole-transfer in semiconducting polymer/low-bandgap cyanine dye blends: evidence for unit charge separation quantum yield

Power-conversion efficiencies of organic heterojunction solar cells can be increased by using semiconducting donor-acceptor materials with complementary absorption spectra extending to the near-infrared region. Here, we used continuous wave fluorescence and absorption, as well as nanosecond transient absorption spectroscopy to study the initial charge transfer step for blends of a donor poly(p-phenylenevinylene) derivative and low-band gap cyanine dyes serving as electron acceptors. Electron transfer is the dominant relaxation process after photoexcitation of the donor. Hole transfer after cyanine photoexcitation occurs with an efficiency close to unity up to dye concentrations of similar to 30 wt%. Cyanines present an efficient self-quenching mechanism of their fluorescence, and for higher dye loadings in the blend, or pure cyanine films, this process effectively reduces the hole transfer. Comparison between dye emission in an inert polystyrene matrix and the donor matrix allowed us to separate the influence of self-quenching and charge transfer mechanisms. Favorable photovoltaic bilayer performance, including high open-circuit voltages of similar to 1 V confirmed the results from optical experiments. The characteristics of solar cells using different dyes also highlighted the need for balanced adjustment of the energy levels and their offsets at the heterojunction when using low-bandgap materials, and accentuated important effects of interface interactions and solid-state packing on charge generation and transport.

Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: Model description, evaluation and application.

Reducing the gap between water-limited potential yield and actual yield in oil palm production systems through intensification is seen as an important option for sustainably increasing palm oil production. Simulation models can play an important role in quantifying water-limited potential yield, and therefore the scope for intensification, but no oil palm model exists that is both simple enough and at the same time incorporates sufficient plant physiological knowledge to be generally applicable across sites with different growing conditions. The objectives of this study therefore were to develop a model (PALMSIM) that simulates, on a monthly time step, the potential growth of oil palm as determined by solar radiation and to evaluate model performance against measured oil palm yields under optimal water and nutrient management for a range of sites across Indonesia and Malaysia. The maximum observed yield in the field matches the corresponding simulated yield for dry bunch weight with a RMSE of 1.7 Mg ha?1 year?1 against an observed yield of 18.8 Mg ha?1. Sensitivity analysis showed that PALMSIM is robust: simulated changes in yield caused by modifying the parameters by 10% are comparable to other tree crop model evaluations. While we acknowledge that, depending on the soils and climatic environment, yields may be often water limited, we suggest a relatively simple physiological approach to simulate potential yield, which can be usefully applied to high rainfall environments and is considered as a first step in developing an oil palm model that also simulates water-limited potential yield. To illustrate the application possibil- ities of the model, PALMSIM was used to create a potential yield map for Indonesia and Malaysia by sim- ulating the growth and yield at a resolution of 0.1?. This map of potential yield is considered as a first step towards a decision support tool that can identify potentially productive, but at the moment degraded sites in Indonesia and Malaysia. ?