Rice Plots Research Articles

Estimation of Soil Nitrogen Content Influenced by Different Nitrogen-Based Management Practices within Rice-Based Cropping Using Diffuse Reflectance Spectroscopy and Machine Learning

ABSTRACT Reflectance spectroscopy has been widely utilized by researchers to characterize and predict soil nitrogen (N). This study explores the potential of reflectance spectroscopy combined with machine learning to estimate soil N levels under different N-based management practices in rice-based cropping systems. A five-year field experiment (2015–2020) was conducted at Kalyani D Block Farm, Bidhan Chandra Krishi Viswavidyalaya, Nadia, West Bengal, India, testing rice-rice, rice-wheat, and rice-potato systems with N treatments: control (N₀), 100% Neem Coated Urea (NCU), 75% NCU with 25% organics, 100% Polymer Sulfur Coated Urea (PSCU), and 75% PSCU with 25% organics. Soil samples from 0 to 15 cm depth were collected post-harvest of rabi crops (wheat and potato) and summer rice for analysis, revealing the highest available N (AN) (189.6 kg ha− 1) in PSCU-treated summer rice plots, with maximum AN in wheat (290.6 kg ha− 1) and potato (431.4 kg ha− 1) found in 75% NCU + 25% organic plots. Rice yield reached a high of 5.58 t ha− 1 with PSCU treatment, while wheat and potato produced 3.87 and 16.07 t ha− 1 with NCU + vermicompost (VC), respectively. Spectral reflectance measurements were conducted in a controlled lab environment using the ASD Field Spec 4 spectroradiometer, showing significant variability in soil spectral behavior with soil organic carbon (SOC) and N levels. Pre-processing techniques, including first-order derivation (FOD), log (1/R) transformation, and continuum removal (CR), were applied to enhance spectral data quality. Machine learning models, Support Vector Machine Regression (SVMR) and Partial Least Squares Regression (PLSR) were used to estimate SOC, AN and total N (TN) from spectral data (350–2500 nm range). Results showed that SVMR consistently outperformed PLSR for all soil properties, with continuum-removed spectra achieving R2 values of 0.98, 0.97, and 0.92, and RMSEs of 0.02%, 37.1, and 948.8 kg ha− 1 for SOC, AN and TN, respectively. This study highlights the value of integrating spectral data with machine learning for rapid, accurate soil N estimation, enabling optimized fertilizer applications to enhance crop yields and reduce environmental impact.

Estimating Total Rice Biomass and Crop Yield at Field Scale Using PlanetScope Imagery Through Hybrid Machine Learning Models

Near real-time crop monitoring has been a challenging due to the lack of high-resolution remote sensing images suitable for agricultural applications. The PlanetScope constellation, comprising approximately 130 Dove satellites, collects images of the entire Earth daily, with a resolution of 3.7 m. The high-resolution images from the PlanetScope satellite, along with vegetation indices, geo-environmental data, and soil and crop parameters, were utilized and analysed using machine learning models to enhance the accuracy of predicting total biomass and rice crop yield at the field scale. The study area, covering nearly 214 sample rice plots, was located in the Tarekswar block of Hooghly, West Bengal, India. Alongside ten vegetation indices and three Principal Component Analysis (PCA) soil nutrient levels, approximately thirty-six factors were analyzed to predict rice total biomass and crop yield using ten machine learning (ML) models, namely Random forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machine (SVM), Bagging Tree (Treebag), Generalized Additive Models (gamSpline), Elastic Net (enet), Ordinary regression with LASSO penalty (rqlasso), Tree Models from Genetic Algorithm (evtree), Bayesian Regularized Neutral Networks (brnn), cubist models, and there hybrid of ensembles. Boruta and multi-collinearity analysis were also conducted for the selected factors to explore their influence levels. The study area exhibited robust rice yields ranging from 5 to 10 t/ha, accompanied by healthy biomass growth. Four ML models ─cubist, random forest, enet, and the hybrid model—showed promising predictions with R2 > 0.88. Most models classified less than 20 ha of the study area as falling into the “very-low suitable class”, showing the region’s suitability for rice cultivation due to its highly fertile alluvial soil. Boruta sensitive analysis revealed that nearly 24 individual factors significantly influenced the final crop yield including, organic carbon (OC), phosphorus (P), electrical conductivity (EC), mechanization level, and the majority of the vegetation indices. A critical analysis carried out through the Map query tool showed that five vegetation indices estimated via PlanetScope displayed strong correlations (exceeding 89%) in identifying areas with high to very high rice yields. The study can serve as a guideline for near-real-time crop monitoring in the near future, using high-resolution PlanetScope images.

Optimizing fertilizer use by providing soil quality information: experimental evidence from Madagascar

BackgroundImproving food security in sub-Saharan Africa (SSA) requires increasing agricultural productivity. The increased and effective use of chemical fertilizers is widely recognized as one of the key strategies for achieving this goal. However, many smallholder farmers in SSA still grow crops without using fertilizer, and even when they do use fertilizer, the amount applied is often less than the recommended level. In addition to various constraints related to input markets and farmers’ socioeconomic characteristics, uncertainty about crop yield response is known to discourage fertilizer use. The purpose of this study was to investigate how site-specific information on soil characteristics can help farmers optimize their fertilizer application decisions by reducing uncertainty in yield response. Our unique approach uses simple binary information about the expected effectiveness of nitrogen fertilizer based on a single soil parameter.MethodologyThe simple binary information was generated for a focal rice plot of each 70 household. Based on the evaluation of oxalate-extractable phosphorus content in the soil composites collected from each of these plots, each plot was categorized into either high or low in terms of the expected effectiveness of nitrogen application. A randomized controlled trial was conducted to estimate the impact of providing this simple binary information primarily on nitrogen application rate and, consequently, on rice yield and income at plot-level and household-level.ResultsThe results showed that first, compared to those in the target plots of the control households, the nitrogen application rate was greater in the target plots of the treatment households who were informed of the high expected effectiveness. Second, information that the expected effectiveness was high increased the amount of nitrogen fertilizer in the target plot compared to that in other plots with no information about expected effectiveness within a household. Third, this change in fertilizer allocation led to higher rice yields and higher rice incomes at the household level.ConclusionsThese results highlight how the binary information about the expected effectiveness with a single soil parameter can improve fertilizer allocation among rice plots and its use efficiency to increase rice productivity and income.

Prospecting and Identification of Fungi Associated with the Rice Leaf Scald Disease in Togo

Leaf scald, caused by Rhynchosporium oryzae, is the third most damaging rice fungal disease worldwide after blast and helminthosporiosis. This study presents the first report of leaf scald on rice in Togo, based on a comprehensive survey of 93 rice plots across 28 out of 39 prefectures. The research aimed to identify, characterize, and test the pathogenicity of fungi associated with leaf scald symptoms, as well as determine the disease's distribution and severity in Togo. Samples were collected, processed in the laboratory, and cultured using blotting paper and potato dextrose agar media. Results revealed that 97,84% of surveyed plots exhibited symptoms related to leaf scald and severity of the disease record were most 5 except two plots which were recorded 9 on the scale of 1 to 9. Fungal isolates were confirmed as R. oryzae through macroscopic and microscopic analysis, adhering to criteria described in existing literature. Growth of mycelium where about 7,5 days in 90 mm petri dish from both paper blotting and PDA medium from initiative culture. Sporus where two or three septa and were obtained after 9 days. Koch's postulates were fulfilled by reproducing leaf scald symptoms using the isolated fungi on the variety IR 841 at 50 days stage. This study contributes valuable insights into the prevalence and characteristics of leaf scald in Togolese rice field.

Living Hedges and Household Food and Nutrition Security in Cote D'ivoire

Soil degradation is a major problem, particularly for Ivorian rice farmers who grow rainfed rice on slopes or flood plains. To remedy this situation, some households are adopting agroforestry practices, in particular living hedgerows. This study analyzes the economic impact of the adoption of living hedgerows on the food and nutritional security of rice-growing households in Côte d'Ivoire. Data were collected from 456 households in the regions of Tonkpi in the west, Poro and Tchologo in the north, using stratified random sampling, with each village considered as a stratum. Then, the two steps of the propensity score matching (PSM) method were used to identify the factors involved in the adoption of living hedges and to measure the effect of this adoption on household food and nutritional security. The results obtained from the propensity score matching (PSM) analysis indicate that the adoption of living hedges improves the food and nutritional security of adopters by an average of 67% and 266.67% respectively. The study therefore recommends improving human capital through training in rice plot selection, raising awareness of the benefits of agroforestry practices, and capacity-building for producers in the use of living hedgerows.

Modelling rice competition with Leptochloa fusca, Bidens frondosa and Ammannia coccinea in transplanted rice cultivation

AbstractA 2‐year field experiment was conducted in Daejeon, South Korea, to investigate changes in the growth parameters of rice plants during the growth and model the rice yield loss as affected by the competition with Leptochloa fusca, Bidens frondosa and Ammannia coccinea under transplanted rice cultivation. Compared with B. frondosa and A. coccinea, L. fusca significantly reduced the number of tillers at the early growth stage, resulting in more reduction in the number of panicles and other yield components such as the number of spikelets, ripened grain ratio and the ultimate rice yield at the later growth stage. Among the components, the panicle number was the most negatively and positively correlated with weed density and rice yield, respectively. Cousens' rectangular hyperbola model predicted that weed competitiveness value represented by parameter β was 0.0337 and 0.0572 for L. fusca, 0.0124 and 0.0165 for B. frondosa and 0.0059 to 0.0061 for A. coccinea in 20.8 and 15.2 hill m−2 rice densities, respectively, indicating the competition effect of L. fusca on rice yield was greater than that of B. frondosa and A. coccinea. Weed densities corresponding to a 50% reduction in the rice yield were 27 and 18 for L. fusca, 81 and 61 for B. frondosa and 169–164 for A. coccinea in 20.8 and 15.2 hill m−2 rice densities, respectively. Weeds are more competitive in low‐density rice plots, leading to greater yield loss. In addition, the economic thresholds (ET) are positively correlated with rice densities and negatively correlated with weed competitiveness. Although low‐density rice transplanting may offer economic benefits during cultivation, optimal rice density and weed control strategies are important for securing a high yield. Therefore, the model and findings could be applied to decision‐making systems in rice farming where weed interference is present.

Dissipation of pendimethalin in a water‐seeded rice field and implications for water management

AbstractWater‐seeded rice (Oryza sativa L.) in California is produced near growing urban centers and a variety of neighboring high‐value crops, which make water quality a paramount concern because of potential herbicide residue contamination in downstream surface waters. Pendimethalin is a potential herbicide for use in California water‐seeded rice. A study was conducted to characterize pendimethalin's dissipation in water of a water‐seeded rice field. A capsule suspension (CS), emulsifiable concentrate (EC), and granule (GR) pendimethalin were applied onto flooded rice plots at 1.1, 2.3, and 3.4 kg ai ha−1 rates. Water samples were collected periodically and analyzed with an high pressure liquid chromatography tandem mass spectrometry system for residues. Pendimethalin dissipation differed across formulations. The initial sampled concentrations recorded values from 3.0 to 125.6 parts per billion (ppb). First‐order dissipation resulted in half‐lives for the CS from 2.3 to 3.5 days, the EC from 0.6 to 0.7 days, and the GR from 3.5 to 6.9 days. Pendimethalin use in water‐seeded rice is at low risk of contaminating downstream surface waters; however, early sampled residue concentrations could be concerning. The results can assist in generating management tactics like water‐holding periods to avoid potential downstream off‐target effects and ensure herbicidal activity in the applied area after a pendimethalin application in a water‐seeded rice field.

Design of a Portable Analyzer to Determine the Net Exchange of CO2 in Rice Field Ecosystems.

Global warming is influenced by an increase in greenhouse gas (GHG) concentration in the atmosphere. Consequently, Net Ecosystem Exchange (NEE) is the main factor that influences the exchange of carbon (C) between the atmosphere and the soil. As a result, agricultural ecosystems are a potential carbon dioxide (CO2) sink, particularly rice paddies (Oryza sativa). Therefore, a static chamber with a portable CO2 analyzer was designed and implemented for three rice plots to monitor CO2 emissions. Furthermore, a weather station was installed to record meteorological variables. The vegetative, reproductive, and maturation phases of the crop lasted 95, 35, and 42 days post-sowing (DPS), respectively. In total, the crop lasted 172 DPS. Diurnal NEE had the highest CO2 absorption capacity at 10:00 a.m. for the tillering stage (82 and 89 DPS), floral primordium (102 DPS), panicle initiation (111 DPS), and flowering (126 DPS). On the other hand, the maximum CO2 emission at 82, 111, and 126 DPS occurred at 6:00 p.m. At 89 and 102 DPS, it occurred at 4:00 and 6:00 a.m., respectively. NEE in the vegetative stage was -25 μmolCO2 m2 s-1, and in the reproductive stage, it was -35 μmolCO2 m2 s-1, indicating the highest absorption capacity of the plots. The seasonal dynamics of NEE were mainly controlled by the air temperature inside the chamber (Tc) (R = -0.69), the relative humidity inside the chamber (RHc) (R = -0.66), and net radiation (Rn) (R = -0.75). These results are similar to previous studies obtained via chromatographic analysis and eddy covariance (EC), which suggests that the portable analyzer could be an alternative for CO2 monitoring.

Effect of Lambda-cyhalothrin + Carbofuran Application and Habitat Modification on Population Dynamics Of 0rseolia oryzivora (Diptera: Cecidomyiidae) in Relation to its Parasitoids On Rice

ABSTRACT This experiment was carried out between 2018 and 2019 at the experimental site of National Cereals Research Institute’s identified hot spot (Edozhigi) for Africa rice gall midge (0rseolia oryzivora) infestation in Nigeria. Edozhigi in Niger State is within the southern Guinea savanna agro-ecological zone at latitude 09°45' N, longitude 06°07' E, to test integrated inluence of habitat manipulation, lambda-cyhalothrin and carbofuran on population dynamics of 0. oryzivora in relation to its parasitoids on rice. The treatments were arranged in split-plot and laid out in a RCBD with three replicates. Data were collected on number of tiller / stand, plant height, days to 50 percent flowering, percent incidence, percent severity, percentage parasitism of 0. oryzivora, panicle per meter square, grains per panicle and yield of rice. Data collected were subjected to Analysis of Variance and significant means were separated using Student Newman Keuls Test, (SNK) at 5 % probability. The result showed that Rice plots treated with P. scrubiculatum + 0.38L/ha lambda-cyhalotrin +3.75kg/ha carbofuran had lower incidence (2.36) and severity (1.54) of 0. oryzivora compared with incidence (7.99) and severity (7.40) respectively found in untreated plots (control). It also had significantly higher yield (3263.95kg/ha) compared with the yield (2688.28kg/ha) in control plots. In conclusion, having P. scrobiculatum at boarder of net plots enhanced number of parasitoids and reduced attack of rice by 0. oryzivora. Integration of habitat modification with insecticide application offers better protection of rice against O. oryzivora. Key words: Habitat P. scrobiculatum, Infestation, Modification, Galls.

Diversity and Population of Weed Propagule in Two Rice Cropping Systems

Weeds can reduce rice yields by 20-89%, mainly due to competition for nutrients, water, sunlight, and growing space. Weeds that grow in rice fields come from propagules previously in the soil. Seedlings are formed from the previous season, so the cultivation system greatly affects them. This study aims to determine the diversity and population of weed propagules in upland rice and lowland rice. This research was conducted by survey method in Semanu District, Gunungkidul Regency, Special Region of Yogyakarta, by taking soil samples from three plots of upland rice and lowland rice paddy. Soil sampling was conducted four times before tillage, 3, 6, and 9 weeks after planting. The results showed that the diversity of weed propagules in upland rice was higher than in lowland rice fields with more weed propagule species. Annual terrestrial weed propagules dominate in upland rice, while in lowland rice fields, it is dominated by annual aquatic weed propagules. The diversity index of weed propagules in upland rice and rice paddy is included in the medium criteria. The number of species and individual propagule weeds in upland rice is more than in the upland rice fields. The results of this study can be used as a basis for proper weed management so that it does not disturb and harm rice plants.

Time-series Sentinel-1A SAR remote sensing of rice planting methods in Ebonyi State, Nigeria

Timely and reliable agricultural data are essential to monitoring the implementation of rice intervention programs and policies aimed at sustainably reducing hunger and poverty. The difficulties associated with traditional data-gathering methods have made using satellite imagery for data acquisition imperative due to its coverage of large agricultural areas, high repetitive coverage, and cost-effectiveness. However, the use of satellite images for rice research in Nigeria is hampered by the peculiarities associated with methods of rice crop establishment, where manual transplanting and direct seeding methods are practiced in single rice plots due to financial constraints. To examine the effect of different planting methods on sensor signals, we analysed the temporal variation of Sentinel-1 synthetic aperture radar (SAR) data. Also, the relationship between SAR backscatter coefficients and field-measured rice plant parameters (wet biomass and plant height) as a function of planting methods was determined in contrast to similar studies where only the temporal variations in the planting methods were investigated. Multi-temporal, dual-polarised C-band Sentinel-1A backscatter data at 20 m spatial resolution and field measurements were simultaneously acquired every 12 days over the study area during the rainy season, from August to December 2019, in Ebonyi state, Nigeria. Average backscatter values were derived per sampling rice plot, with the temporal profiles of rice SAR backscatter plotted to show variability due to planting methods. Simple regression analysis determined the relationships between measured rice parameters and VH (Vertical transmit, Horizontal receive) and VV (Vertical transmit, Vertical receive) polarisation backscatter coefficients. Results revealed variations in the temporal profile and responses of transplanted and direct-seeded rice fields at different crop growth stages. Regression analysis showed that VH and VV backscatter values for transplanted rice were significantly related to wet rice biomass (R2 = 0.6; 0.51) and rice plant height (R2 = 0.5; 0.59). Conversely, wet biomass (R2 = 0.24; 0.19) and plant height (R2 = 0.18; 0.2) were reported for broadcasted rice for VH and VV polarisations, respectively. These findings show that significant differences exist in the SAR backscatter responses of these crop establishment methods, affecting the retrieved data's accuracy and reliability. Therefore, a cautious approach is advocated in using SAR data from small rice plots with multiple planting methods.

"Farmer Field School", a participatory educational approach for improving the fight against malaria vectors in irrigated rice-growing areas in Benin

Malaria is a major health problem in Benin where it is the main cause of morbidity and mortality, particularly among children under 5 and pregnant women. Although the vast majority of malaria cases occurs in rural and agricultural areas and are often associated with development projects, very few interventions target the agro-ecosystem. In Benin, irrigated rice growing is expanding to meet the increasing demand of the population. However, continuous flooding and tillage systems induce the development and proliferation of malaria and other diseases vectors. Intermittent flooding of rice plots and minimal tillage can reduce significantly the proliferation of mosquitoes including Anopheles in rice fields. However, the dissemination and implementation of these agricultural practices require community-wide action for greater effectiveness. As part of strengthening the capacity of farming communities in the fight against malaria vectors, the "Farmer Field School" appears to be an innovative approach. This learning by doing method promotes interactions between groups of producers to disseminate proven technologies. This study aims to disseminate among rice producers the agricultural practices of intermittent flooding and minimal tillage, likely to reduce the proliferation of malaria vectors in the rice fields. This study was carried out in the rice-growing perimeter of Malanville, Benin (11° 52' 5" North, 3° 22' 59" East) which covers an area of 516 hectares. Farmer Field Schools were set up after a basic survey at producer level. This survey was carried out through in-depth interview, focus group discussions and direct field observation with producers. Focus groups discussions and interviews made it possible to understand the perception of rice farmers on the link between rice production and the transmission of malaria. In order to disseminate new agricultural practices such as intermittent flooding and minimal tillage among producers, twelve plots have been set up. Farmer Field Schools were monitored weekly with rice producers accompanied by a facilitator and a medical entomologist (learning facilitator or moderator) helping the farmers with the collection and identification of mosquito larvae. According to the different stages of rice development (transplanting, tillering, maturation), the mosquito larvae were collected in the test and control plots from 10 a.m. to 2 p.m. by the dipping method. Then the water in the test compartments (intermittent flooding) was emptied. A cycle of 7 days of flooding and 2 days of drying was carried out for intermittent flooding. Mosquito larvae were identified morphologically using the identification key and Anopheles genus larvae were isolated in plastic cups. The impacts of intermittent flooding and minimum tillage in reducing breeding sites and larval densities were established by determining and comparing the larval densities of mosquitoes and of Anopheles between the test and control plots. Direct observations in the field allowed to identify three tillage systems, which include the use of tiller (28%), plow (66%) and hoe (6%) on the rice field. Continuous flooding was the only irrigation system used by farmers. The water used for irrigation comes either from boreholes installed individually or from the Niger River. The volume of water used varies with the seasons, the size of the farms and the variety of rice grown. Farmers observe that the nuisance of mosquitoes increases during the rice production period with an outbreak of malaria cases, especially among children, which leads to crowds in health centers. The preventive measures against malaria among farmers are the use of impregnated mosquito nets distributed free of charge by the national program against malaria, and of insecticide bombs or spirals. Considering the development stages of the rice, the larval densities varied according to the treatments. Overall, minimal tillage applied to intermittent flooding significantly reduced the density of mosquito larvae of all species. The reduction rates were 10.5, 5.4 and 2.5 during transplanting, tillering and maturation, respectively. Considering only the Anopheles larvae, minimal tillage applied to intermittent flooding reduced their density by 16, 5.5 and 4 respectively during transplanting, tillering and maturation. The rice-growing area of Malanville has many favorable conditions for rice production, including the presence of water supply sources such as the Niger River located near the rice field and numerous boreholes. The availability of water pockets for mosquito breeding during irrigation appeared to contribute to the extension of malaria transmission. The present study showed that the intermittent flooding coupled with minimal tillage could reduce the proliferation of malaria vectors. The results suggested that with technical support to farmers through the "Farmer Field School", the malaria incidence could be reduced in the farming community.

Ecological engineering in low land rice for brown plant hopper, Nilaparvata lugens (Stål) management.

Rice field bunds and edges can act as near crop habitats, available for planting flowering plants to attract and conserve the natural enemies. We evaluated the effect of ecological engineering on the incidence of Brown Planthopper (BPH), Nilaparvata lugens (Stål)(Hemiptera; Delphacidae) and the abundance of its predators in the rice variety Pusa Basmati-1121. Plots included the oilseed crops viz. sesamum, sunflower and soybean, with plantings of flowering crops marigold, balsam and gaillardia as bund flora around the edges of rice plots. Ecologically engineered plots contained both crops+flowers and resulted in a significantly reduced BPH population per hill in rice plots for 2019 (6.3) and 2020 (9.4) compared to the control plots (9.8 and 14.4). Ecologically engineered plots also witnessed the delayed appearance of BPH during each growing season. Peak BPH populations are lower in the ecologically engineered plots than in the control grounds. Furthermore, the activity of natural enemies, viz., spiders, mirid bugs and rove beetles was the highest in rice fields planted with oilseed crops like sesamum, sunflower and soybean. Olfactory response studies showed that the attraction response of spiders toward sesamum and balsam leaves was more significant than in other crop plants. Rice yield was enhanced in plots planted with crops+flowers during both seasons compared to control plots. Planting of oilseed crops plants such as sesamum, sunflower and soybean with flowering crops such as marigold, balsam and gaillardia as bund flora on the bunds around the main rice field enhanced the natural enemy activity, suppressed the planthopper population, and increased yields. Based on the results, we recommend including ecological engineering techniques as one of the management components in the Integrated Pest Management programme for rice crops.

An ecological network approach for detecting and validating influential organisms for rice growth.

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

An ecological network approach for detecting and validating influential organisms for rice growth

How to achieve sustainable food production while reducing environmental impacts is a major concern in agricultural science, and advanced breeding techniques are promising for achieving such goals. However, rice is usually grown under field conditions and influenced by surrounding ecological community members. How ecological communities influence the rice performance in the field has been underexplored despite the potential of ecological communities to establish an environment-friendly agricultural system. In the present study, we demonstrate an ecological-network-based approach to detect potentially influential, previously overlooked organisms for rice (Oryza sativa). First, we established small experimental rice plots, and measured rice growth and monitored ecological community dynamics intensively and extensively using quantitative environmental DNA metabarcoding in 2017 in Japan. We detected more than 1000 species (including microbes and macrobes such as insects) in the rice plots, and nonlinear time series analysis detected 52 potentially influential organisms with lower-level taxonomic information. The results of the time series analysis were validated under field conditions in 2019 by field manipulation experiments. In 2019, we focused on two species, Globisporangium nunn and Chironomus kiiensis, whose abundance was manipulated in artificial rice plots. The responses of rice, namely, the growth rate and gene expression patterns, were measured before and after the manipulation. We confirmed that, especially in the G. nunn-added treatment, rice growth rate and gene expression pattern were changed. In the present study, we demonstrated that intensive monitoring of an agricultural system and the application of nonlinear time series analysis were helpful to identify influential organisms under field conditions. Although the effects of the manipulations were relatively small, the research framework presented here has future potential to harness the ecological complexity and utilize it in agriculture. Our proof-of-concept study would be an important basis for the further development of field-basis system management.

Do female labor‐migrated households have lower productivity? Empirical evidence from rural rice farms in Bangladesh

AbstractThe labor movement from rural areas and the remittance flow from migrants is a common household livelihood strategy in rural Bangladesh. While migration can offer economic benefits through remittances, it can be a source of hardship for migrants and their families due to societal culture. This study examines the differences in farm productivity and technical efficiency between female and male labor migrants by focusing on female and male laborers who have lived away from their homes for 6 months or more within the country and its reflection on farm production. Using data on 2271 rice plots from Bangladesh Integrated Households Survey in 2018, we estimate plot‐level stochastic meta‐frontier approach for households with female‐labor migrants and male‐labor migrants separately emphasizing technological difference and heteroskedastic technical efficiency. The empirical result shows that the female‐labor migrants' farms have 10.3% lower production frontier (maximum frontier yield) and 6.1% higher technical efficiency than male migrants' farms, indicating that they have 4.2% lower productivity. Lower production frontier reflects lower management ability and less attention to farm practice. Moreover, the study reveals that female‐labor migrants' farms are closer to the meta‐frontier, suggesting smaller technology gaps. However, some farmers failed to achieve the highest possible output in relation to the meta‐frontier, indicating that farmers can boost their production by adopting and disseminating new rice production technology.

A Best-Bet System of Rice Intensification for Sustainable Rice (Oryza sativa L.) Production in Northwestern Nigeria

System of Rice Intensification (SRI) practices are expected to be used in location-specific ways and thus will vary somewhat across countries and regions. This study undertook to identify a ‘best-bet’ version of SRI for conditions in northwestern Nigeria, considering what is feasible for farmer use. Two years of experimental data from 260 farmer-managed rice plots evaluating four of the SRI practices in Zamfara State were analyzed. The variables evaluated were seedling age at transplanting, plant density, irrigation schedule, and fertilizer application. Farm budget analysis showed that the best-bet SRI practices most productive given the natural environment and farming system were transplanting 11-day-old seedlings at 25 cm × 25 cm spacing, with alternate wetting-and-drying of fields, as well as providing full compost plus some inorganic fertilization. Net economic returns were found to be highest with best-bet SRI practices and ranged from USD 1450–2120 ha−1. While rice production was profitable under both SRI and more conventional management, the return on investment was at least 40% higher with SRI practices than with the other practices evaluated. Based on our data and analysis, we recommend that the Nigerian government and its development partners prioritize and expand the testing and promotion of SRI in the northwest and other regions of the country. This initiative can significantly enhance farmers’ incomes and, ultimately, bolster food security.

Characterization of Rice Yield Based on Biomass and SPAD-Based Leaf Nitrogen for Large Genotype Plots

The use of Unmanned Aerial Vehicle (UAV) images for biomass and nitrogen estimation offers multiple opportunities for improving rice yields. UAV images provide detailed, high-resolution visual information about vegetation properties, enabling the identification of phenotypic characteristics for selecting the best varieties, improving yield predictions, and supporting ecosystem monitoring and conservation efforts. In this study, an analysis of biomass and nitrogen is conducted on 59 rice plots selected at random from a more extensive trial comprising 400 rice genotypes. A UAV acquires multispectral reflectance channels across a rice field of subplots containing different genotypes. Based on the ground-truth data, yields are characterized for the 59 plots and correlated with the Vegetation Indices (VIs) calculated from the photogrammetric mapping. The VIs are weighted by the segmentation of the plants from the soil and used as a feature matrix to estimate, via machine learning models, the biomass and nitrogen of the selected rice genotypes. The genotype IR 93346 presented the highest yield with a biomass gain of 10,252.78 kg/ha and an average daily biomass gain above 49.92 g/day. The VIs with the highest correlations with the ground-truth variables were NDVI and SAVI for wet biomass, GNDVI and NDVI for dry biomass, GNDVI and SAVI for height, and NDVI and ARVI for nitrogen. The machine learning model that performed best in estimating the variables of the 59 plots was the Gaussian Process Regression (GPR) model with a correlation factor of 0.98 for wet biomass, 0.99 for dry biomass, and 1 for nitrogen. The results presented demonstrate that it is possible to characterize the yields of rice plots containing different genotypes through ground-truth data and VIs.

Effects of fentin acetate molluscicide on biological performance and haematological of the common carp, Cyprinus carpio cultivated at rice field water

Molluscicide of fentin acetate (C20H18O2Sn) is commonly used at the present due to effective in terms to control of molluscs in the rice field. The aims of this experiment is to determine toxicity effect of fentin acetate on growth, productivity, and blood glucose on the common carp, Cyprinus carpio cultured at rice field water. A 12 of rice field plots with size of 25m2 each were used. The stocking density of common carp was 25 fish/m2 for each rice plot. The culture period of the common carp was 21 days. The different fentin acetate concentration as treatments were as followed M0) without molluscicide; M1) 0.375 g/L of molluscicide; M2) 0.75 g/L of molluscicide); and M3) 1.5 g/L of molluscicide. Statistical analysis using one-way ANOVA with three replicates for each treatment was performed. The result showed that the treatment of molluscicide at 0.75 g/L was significantly different to the others on survival rate and productivity (p<0.05). Application of 0.75 g/L of molluscicide showed a positive correlation on blood glucose value.

Access and Control of Resources and Participation in Rice-Breeding Activities among Men and Women Farmers in Southern Ghana

This paper provides evidence of gender differences in the access and control of resources and their relation to participation in rice-breeding activities among men and women farmers in southern Ghana. We used a mixed methods design which involved the use of qualitative data collected through focus group discussions (FGDs) and key informant interviews (KIIs) and quantitative data collection through a survey. Using data collected from 315 smallholder rice farmers, perception analyses and probit and multivariate regression were employed in the analyses. Our findings indicate that higher levels of education, experience in rice farming, a favorable dependency ratio, larger farm size, more rice plots, access to extension services, and involvement with financial organizations positively influence participation in rice-breeding activities. On the other hand, distance to market is found to have a negative impact on participation. Moreover, years of education, experience in rice farming, farm size, number of rice plots, dependency ratio, and distance to market were found to negatively influence the control of production resources among both male and female participants in rice-breeding activities. From both the quantitative and qualitative results, men had more access to productive resources than women. Insights from this study will enhance gender equity in promoting the participation of both men and women in rice varietal development activities.