A Tale of Two Countries: Spatial and Temporal Patterns of Rice Productivity in China and Brazil

This paper looks at differences in spatial and temporal variation of rice yields in China and Brazil. We find that rice yields in China have converged over time and that rice production has become more and more homogeneous. In contrast, rice yields in Brazil have diverged over time, primarily due to variations in upland rice yields. Three hypotheses are put forward to explain the different behaviour of rice yields in Brazil and China: (i) differences in production systems (i.e., irrigated in China versus upland in Brazil); (ii) changes in rainfall patterns and (iii) bias in agricultural R&D favouring irrigated rice. Our empirical analysis provides support to the first two hypotheses by establishing that upland rice is subjected to much greater variation in yields than irrigated rice and that changing rainfall patterns affect mostly upland rice. We also provide evidence of the bias towards irrigated systems by looking at the patterns of varietal release.rice productivity, spatial convergence, technology spillover, China, Brazil

A tale of two countries: Spatial and temporal patterns of rice productivity in China and Brazil

"This paper examines differences in the spatial and temporal variations of rice yields in China and Brazil. Our analysis indicates that, in China, rice yields have converged over time and rice production has become increasingly homogeneous. In contrast, rice yields in Brazil have diverged over time, primarily due to variations in upland rice yields. Three hypothetical explanations may account for the different behaviors of rice yields in Brazil and China, namely: 1) differences in production systems (i.e. irrigated in China vs. upland in Brazil); 2) changes in rainfall patterns; and 3) bias in agricultural research and development (R&D) towards irrigated rice. Our empirical analysis supports the first two hypotheses by establishing that: 1) upland rice shows much more variation in yields compared to irrigated rice; and 2) changing rainfall patterns have primarily affected upland rice. We also provide evidence of the bias towards irrigated systems by looking at the patterns of varietal release." from Author's AbstractRice productivity, Spatial convergence, Technology spillover, Agricultural research, Research and development,

Impacts of climate change on rice production in Africa and causes of simulated yield changes

This study is the first of its kind to quantify possible effects of climate change on rice production in Africa. We simulated impacts on rice in irrigated systems (dry season and wet season) and rainfed systems (upland and lowland). We simulated the use of rice varieties with a higher temperature sum as adaptation option. We simulated rice yields for 4 RCP climate change scenarios and identified causes of yield declines. Without adaptation, shortening of the growing period due to higher temperatures had a negative impact on yields (−24% in RCP 8.5 in 2070 compared with the baseline year 2000). With varieties that have a high temperature sum, the length of the growing period would remain the same as under the baseline conditions. With this adaptation option rainfed rice yields would increase slightly (+8%) but they remain subject to water availability constraints. Irrigated rice yields in East Africa would increase (+25%) due to more favourable temperatures and due to CO2 fertilization. Wet season irrigated rice yields in West Africa were projected to change by −21% or +7% (without/with adaptation). Without adaptation irrigated rice yields in West Africa in the dry season would decrease by −45% with adaptation they would decrease significantly less (−15%). The main cause of this decline was reduced photosynthesis at extremely high temperatures. Simulated heat sterility hardly increased and was not found a major cause for yield decline. The implications for these findings are as follows. For East Africa to benefit from climate change, improved water and nutrient management will be needed to benefit fully from the more favourable temperatures and increased CO2 concentrations. For West Africa, more research is needed on photosynthesis processes at extreme temperatures and on adaptation options such as shifting sowing dates

Stage-specific, Nonlinear Surface Ozone Damage to Rice Production in China.

China is one of the most heavily polluted nations and is also the largest agricultural producer. There are relatively few studies measuring the effects of pollution on crop yields in China, and most are based on experiments or simulation methods. We use observational data to study the impact of increased air pollution (surface ozone) on rice yields in Southeast China. We examine nonlinearities in the relationship between rice yields and ozone concentrations and find that an additional day with a maximum ozone concentration greater than 120 ppb is associated with a yield loss of 1.12% ± 0.83% relative to a day with maximum ozone concentration less than 60 ppb. We find that increases in mean ozone concentrations, SUM60, and AOT40 during panicle formation are associated with statistically significant yield losses, whereas such increases before and after panicle formation are not. We conclude that heightened surface ozone levels will potentially lead to reductions in rice yields that are large enough to have implications for the global rice market

The Application of Non-linear Cubic Regression in Rice Yield Predictions

The rice yields have fluctuated in Wonogiri Regency. This occasion happened in 2016-2018. Therefore, a prediction is needed to know whether rice yields will increase or decrease in the following year. The purpose of this study was to apply the polynomial non-linear regression method of third-degree in predicting rice yields. This study utilized the Unified Modeling Language (UML) as the system design, black-box testing as the functional testing, and MSE testing as the validity testing. The computed data was data of 2016-2018. The results showed that the prediction of 2017-2019 using the harvested area model produced more accurate calculations. The harvested area model produced the same MSE value in manual and application calculations, which were 405433,1349 in 2017, 312677,7798 in 2018, and 171183.6347 in 2019. The polynomial non-linear cubic regression is a solution to predict rice yields. The output of the application is the prediction information for rice yield

A calculation of potential rice yields.

Gross photosynthesis of rice cv. Tainan-3, Peta and BPI-76 was calculated using the model developed by de Wit [see FCA 19, 515] and the results used to calculate total DM production during 4 seasons in 1962-3 at Los Banos, Philippines. Grain yields were calculated on the basis of a tracer experiment on carbohydrate translocation [see FCA 20, 2384]. Calculated total DM yields, grain yields and grain:straw ratios were in acceptable agreement with the experimental results, provided that the dates when a closed stand was obtained and when the growth rate started to decrease were known. Data are given on potential average growth rates, total DM production and grain yields for the seasons when rice can be grown and for the entire year for a typical modern non-lodging cv. given adequate N and grown at 17 sites with widely differing climates. (Abstract retrieved from CAB Abstracts by CABI’s permission

Changes in rice yield in China under future climate scenarios

The Levinsohn-Petrin consistent semi-parametric estimation method was used to empirically analyze input-output panel data on rice yields in 30 Chinese provinces from 1990 to 2019 and to predict the level of rice yields at the end of the 21st century. The results show that, in addition to natural disasters and objective natural conditions, rice yields depend mainly on pesticide application, that China's current rice production and operation model is insufficient to match the rapidly growing level of agricultural mechanization, and that promoting large-scale production in rice fields is an effective way to address the waste of agricultural machinery resources. From the prediction results, the model has stronger prediction ability for the central-eastern and southern production areas of China, and very low prediction ability for the northern and western areas. The prediction of rice yield levels in China shows that rice yields in China at the end of the 21st century increase by 9.81% under the RCP8.5 climate scenario. This paper puts forward targeted suggestions for improving rice yields. The government should strengthen the promotion and training of agricultural technology and increase the channels for farmers to learn rice cultivation techniques; promote large-scale rice production and operation; and improve the education level of rice growers.Máster Universitario en Análisis Económico Aplicado (M148

Identification of socio-economic characteristics and farmers’ practices affecting rice (Oryza spp.) yields in Benin (West Africa)

Rice (Oryza spp.) is one of the major staple foods in Benin. Benin has increased rice production through the expansion of cultivation area rather than increasing rice yields. To better understand the factors affecting rice yields, a thorough understanding of the current rice production system characteristics and constraints is required. The present study identifies socio-economic characteristics and farmers’ practices affecting rice yields and suggests improved cultivation practices in the sector. Data were collected through semi-structured interviews, including socio-economic characteristics and rice cultivation practices from 230 randomly selected rice producers in North and Central Benin. Descriptive statistics and cluster analysis were used to group rice producers into different groups. Findings revealed that the proportion of rice producers having access to credit was low (33.5 %). Out of seventeen variables, only three (lowland rice cultivation, irrigated rice cultivation and total land cultivated area) discriminated best the rice producers in three (03) clusters with distinct characteristics in terms of socio-economics factors and cropping practices affecting rice yields. Most respondents (more than 70 %) did not practice crop rotation or fallow. This, together with low levels of chemical fertiliser applications and type of rice cultivation, explains poor rice production in particular in clusters 1 and 2. Yield enhancement is possible through the combination of lowland and irrigated cultivation performed by farmers in cluster 3 with the highest mean rice yield (3.8 t.ha-1). We suggest tackling the specific characteristics and needs of rice producers would more adequately help to improve rice yields. Interventions to enhance rice yields include training on best rice production practices, provision of input subsidies and access to irrigation tailored to the specific constraints and needs of each rice grower type. Finally, enabling access to credit will improve productivity of rice farmers in Benin

Application of Cubic Nonlinear Regression on the Effects of Rainfall on Rice Harvest Results

Sukoharjo rice yields fluctuate every year. There is no system used for predicting rice yields in the Sukoharjo region, this results in a lack of information to increase rice production in Sukoharjo Regency.The purpose of this study is to apply the Cubic Nonlinear regression method to predict rice yields in Sukoharjo Regency, taking into account the influence of average rainfall on the prediction of rice yields.The design method uses Unified Model Language (UML), the application is designed with the vb net programming language and sql server database system, testing the functionality using the Black Box Test and testing the validity using MAPE. The calculated data is the 2016 data. The results of the study show predictions in 2017 have a MAPE of . This shows the prediction error rate of Based on the results of the functionality test, 100% of the applications function

Chemical Properties of Inceptisol and Rice Yields Applied with Mixed Source Fertilizer (MSF)

One effort that can be done to improve soil fertility and crop yields is fertilization. Fertilization using a mixed source fertilizer (MSF) is an option to overcome the impact of inorganic fertilizer use and organic fertilizer drawbacks. This study aims to evaluate the effects of MSF application on the chemical properties of Inceptisol and rice yields. A field experiment was conducted using a completely randomized block design (RCBD) with two factors and three replications. The first factor was the three formulas of MSF (F1, F2, F3) and the second factor was MSF doses (0, 2.5, 5, 7.5, 10 Mg ha-1). The results show that there is no significant difference on the total soil N, available soil P, plant height and total number of tillers of rice plants applied with the three MSF formulas. The increased MSF doses applied significantly improve the soil chemical properties of Inceptisol and rice yields. The application of 10 Mg ha-1 MSF increases total- N (57.89%), available-P (29.13%), exchangeable-Ca and -Mg (117% and 250%, respectively), plant height (40%) and total number of tillers (43.2%) in comparison to those without MSF application. There are interaction effects between formulas and doses of MSF on the amount of exchangeable-K, organic-C content, and CEC of the soil and rice yields. The application of 10 Mg ha-1 MSF F3 results in better effects on the amount of exchangeable-K, organic-C content and CEC of the soil, and number of productive tillers and rice yields than the application of other MSF formulas. The MSF can be used as an alternatif fertilizer that can improve Inceptisol productivity