Key Techniques of an Ecological Pattern“Planting Rice in One Season and Breeding Red Swamp Crawfish in Three Seasons” for Green Production in Lixiahe Region of Jiangsu Province

Three big field projects, independent irrigation and drainage facilities, and a blocking net, which are auxiliary projects of a green planting and breeding pattern composed of rice and red swamp crawfish （Procambarus clarkii）, spatial and temporal coupling technology of ＂planting rice in one season and breeding red swamp crawfish in three seasons＂, green fertilization technology, green prevention and control technology, control technology of water level, and throwing technology of bait in Lixiahe region of Jiangsu Province were introduced successively, which can provide technical support for the development of ecological planting and breeding patterns and realization of green production in paddy fields.

Distribution and Transport of Heavy Metals in Rice Plants in the Jiujiang River Basin

Inductively coupled plasma mass spectrometry(ICP-MS)was used to analyze the distribution and migration of heavy metals in rice plants in the Jiujiang River Basin,to evaluate the distribution of heavy metals in rice plants and to analyze their migration.The results showed that the distribution of different heavy metal elements in various tissues of rice plants varied greatly.The heavy metal migration factor of rice plant stems and leaves was significantly higher than that of rice husk and brown rice.The distribution of heavy metal content in rice in the Jiujiang River can provide a certain theoretical basis and reference value for the safety and quality of rice in the Jiujiang River Basin.

Spatio-Temporal Changes in the Rice Planting Area and Their Relationship to Climate Change in Northeast China: A Model-Based Analysis

Rice is one of the most important grain crops in Northeast China （NEC） and its cultivation is sensitive to climate change. This study aimed to explore the spatio-temporal changes in the NEC rice planting area over the period of 1980-2010 and to analyze their relationship to climate change. To do so, the CLUE-S （conversion of land use and its effects at small region extent） model was ifrst updated and used to simulate dynamic changes in the rice planting area in NEC to understand spatio-temporal change trends during three periods： 1980-1990, 1990-2000 and 2000-2010. The changing results in individual periods were then linked to climatic variables to investigate the climatic drivers of these changes. Results showed that the NEC rice planting area expanded quickly and increased by nearly 4.5 times during 1980-2010. The concentration of newly planted rice areas in NEC constantly moved northward and the changes were strongly dependent on latitude. This conifrmed that climate change, increases in temperature in particular, greatly inlfuenced the shift in the rice planting area. The shift in the north limit of the NEC rice planting area generally followed a 1＆#176;C isoline migration pattern, but with an obvious time-lag effect. These ifndings can help policy makers and crop producers take proper adaptation measures even when exposed to the global warming situation in NEC.

Temperature and solar radiation utilization of rice for yield formation with different mechanized planting methods in the lower reaches of the Yangtze River,China

Several studies have demonstrated the effect of planting methods on rice yield, but information on the climate resources is limited. This study aims to reveal the effects of planting methods on climate resources associated with rice yield in a rice-wheat rotation system in the lower reaches of the Yangtze River, China. Field experiments were conducted in 2014 and 2015 with two japonica, two indica hybrid, and two japonica-indica hybrid varieties grown under three mechanized planting methods： carpet seedling of mechanical transplanting（CT）, mechanical direct seeding（DS）, and pot-hole seedling of mechanical transplanting（PT）. The rice yield and total dry matter under PT were greater than those under CT and DS methods. Besides, the entire growth duration and daily production showed significant positive relations with rice yield. Compared with CT and DS, the effective accumulated temperature and cumulative solar radiation of rice under PT were higher in phenological phases. In addition, the dry matter/effective accumulated temperature and solar energy utilization of rice under CT and DS were higher during vegetative phase and lower during reproductive and grain filling phases in contrast to PT. The mean daily temperature and mean daily solar radiation in the entire growth duration showed significant positive correlation with rice yield, total dry matter, and harvest index. This study demonstrated that when the mean daily temperature is 〈25.1°C in vegetative phase and 〉20.1°C in grain filling phase, rice yield could be increased by selecting mechanized planting methods. Most varieties under PT method exhibited high yield and climate resources use efficiency compared with CT and DS. In conclusion, the PT method could be a better cultivation measure for high rice yield, accompanied with high temperature and solar radiation use efficiency in a rice-wheat rotation system in the lower reaches of the Yangtze River, China.

Towards Intelligent Detection and Classification of Rice Plant Diseases Based on Leaf Image Dataset

The detection of rice leaf disease is significant because,as an agricultural and rice exporter country,Pakistan needs to advance in production and lower the risk of diseases.In this rapid globalization era,information technology has increased.A sensing system is mandatory to detect rice diseases using Artificial Intelligence(AI).It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases.Deep Neural Network(DNN)is a novel technique that will help detect disease present on a rice leave because DNN is also considered a state-of-the-art solution in image detection using sensing nodes.Further in this paper,the adoption of the mixed-method approach Deep Convolutional Neural Network(Deep CNN)has assisted the research in increasing the effectiveness of the proposed method.Deep CNN is used for image recognition and is a class of deep-learning neural networks.CNN is popular and mostly used in the field of image recognition.A dataset of images with three main leaf diseases is selected for training and testing the proposed model.After the image acquisition and preprocessing process,the Deep CNN model was trained to detect and classify three rice diseases(Brown spot,bacterial blight,and blast disease).The proposed model achieved 98.3%accuracy in comparison with similar state-of-the-art techniques.

Preliminary Study on Optimized Conditions for Dry-cultivated Rice Seedling Planting

The effects of soil moisture content, pot seedling buried depth, and pot seedling height on the survival rate and growth of dry planted seedlings were researched by field experiment. The results showed that the seedling survival rate and growth were enhanced with the increase of soil moisture content after pot seedling transplanting, but there was no significant difference in the survival rate and growth of seedlings with 85% and 100% of soil moisture content. Pot seedling buried depth was one of the important factors affecting the survival rate, and when the pot seedlings were buried 2 cm deep, the seedlings showed high survival rate and excellent growth. Under the same condition of soil moisture content and buried depth, seedlings with pot seedling height of 15 cm had the best survival rate and growth. Therefore, the optimized conditions for dry-cultivated rice seedling planting were soil moisture content of 85%, pot seedling buried depth of 2 cm, and pot seedling height of 15 cm.

Photosynthetic Characteristics of Transgenic Rice Plants Overexpressing Maize Phosphoenopyruvate Carboxylase

用转PEPC、PPDK、NADP_ME、PEPC +PPDK 双基因水稻 (OryzasativaL .)及原种为材料 ,以光合酶活性、饱和光合速率及PSⅡ光化学效率 (Fv/Fm)为指标 ,研究了转PEPC基因水稻的光合生理特征。结果如下 :转PEPC基因水稻PEPC活性比原种提高 2 0倍 ;饱和光合速率比原种高 5 5 % ;用高光强或人工光氧化剂甲基紫精 (MV)处理后 ,与原种相比 ,转PEPC基因水稻光化学效率下降较少 ,证明其耐光抑制、耐光氧化能力增强 ,测定其光合日变化看出 :在 1d中不同时间 ,转PEPC基因水稻的光合速率均高于原种 ,且与PEPC活性的日变化有相似的趋势。上述结果为转PEPC基因水稻的生理机制和育种研究提供了依据和途径。

Rice planting acceleration of the activation and loss of soil iron in the red soil region of southern China

Rice planting decreased total iron but increased active iron.Iron activation varied greatly among different paddy soils but not in woodland soils.Paddy soil iron was mainly affected by pH,SOC and particle composition.The decrease of soil Fe was mainly in the form of Fec and was closely related to SOC.

Developmental characteristics and response to iron toxicity of root border cells in rice seedlings

To investigate the Fe^2＋ effects on root tips in rice plant, experiments were carried out using border cells in vitro. The border cells were pre-planted in aeroponic culture and detached from root tips. Most border cells have a long elliptical shape. The number and the viability of border cells in situ reached the maxima of 1600 and 97.5%, respectively, at 20---25 mm root length. This mortality was more pronounced at the first 1-12 h exposure to 250 mg/L Fe^2＋ than at the last 12-36 h. After 36 h, the cell viability exposed to 250 mg/L Fe^2＋ decreased to nought, whereas it was 46.5% at 0 mg/L Fe^2＋. Increased Fe^2＋ dosage stimulated the death of detached border cells from rice cultivars. After 4 h Fe^2＋ treatment, the cell viabilities were _〉80% at 0 and 50 mg/L Fe^2＋ treatment and were 〈62% at 150, 250 and 350 mg/L Fe^2＋ treatment; The viability of border cells decreased by 10% when the Fe^2＋ concentration increased by 100 mg/L. After 24 h Fe^2＋ treatment, the viabilities of border cells at all the Fe^2＋ levels were 〈65%; The viability of border cells decreased by 20% when the Fee＋ concentration increased by 100 mg/L. The decreased viabilities of border cells indicated that Fe^2＋ dosage and treatment time would cause deadly effect on the border cells. The increased cell death could protect the root tips from toxic harm. Therefore, it may protect root from the damage caused by harmful iron toxicity.

Nutritive Equilibrium in Rice Plant Populations for High Yield

The effects of nitrogen, phosphorus and potassium application level, seed rate and transplanting density on the growth and development of rice plants were studied to find out nutrient status in high-yielding rice plants and to increase grain yield by adequate fertilization. There was an equilibrium relationship among nutrient elements for high-yielding rice plant populations. The equilibrium index of nutrient amount, content and distribution in high-yielding rice plants should be generally greater than-2 but less than 2. The optimum nutritive proportion of nitrogen: phosphorus: potassium assimilated by the plants was about 10: 2: 9 at the ripening stage. But the content and the proportion varied with the growth stages. Therefore, the nutrient in rice plant populations should be in a dynamic equilibrium, so as to achieve high yield.

Effect of Cultural Measures on Nutrient Contellts in Rice Plants with Erect Panicles

Field experiments were carried out with rice variety of Shennong 91 of short culms and erect panicles to study nutrient contents in high-yielding rice plants and to increase rice yield by appropriate fertilization.Nitrogen, phosphorus, potassium, magnesium, zinc, manganese, iron and copper contents in rice plants varied with different treatment factors. The relationship between the nutrient contents and treatment factors could be simulated using a multiple quadratic equation. The nutrient contents in plants should be appropriate for high-yielding rice. If the mean nutrient content in rice plants producing 11 t ha-1 or more of grain (μj) was set as the standard value and the standard deviation (σj) was set as the range of variation, the nutrient content in high-yielding rice plants should be μj±1.99σj. Rice leaves were sensitive to the nutrient elements. Heavy nitrogen dressing increased the content of nitrogen in rice plants. Sparse transplanting also increased nitrogen content. Improper application of nitrogen, phosphorus and potassium could affect the nutrient contents and decrease the grain yield.

Characteristics of photosynthesis in rice plants transformed with an antisense Rubisco activase gene

Transgenic rice plants with an antisense gene inserted via Agrobacterium tumefaciens were used to explore the impact of the reduction of Rubisco activase (RCA) on Rubisco and photosynthesis. In this study, transformants containing 15% to 35% wild type Rubisco activase were selected, which could survive in ambient CO2 concentration but grew slowly compared with wild type controls. Gas exchange measurements indicated that the rate of photosynthesis decreased sig- nificantly, while stomatal conductance and transpiration rate did not change; and that the intercellular CO2 concentration even increased. Rubisco determination showed that these plants had approximately twice as much Rubisco as the wild types, although they showed 70% lower rate of photosynthesis, which was likely an acclimation response to the reduction in Rubsico activase and/or the reduction in carbamylation.

An Optimal Classification Model for Rice Plant Disease Detection

Internet of Things(IoT)paves a new direction in the domain of smart farming and precision agriculture.Smart farming is an upgraded version of agriculture which is aimed at improving the cultivation practices and yield to a certain extent.In smart farming,IoT devices are linked among one another with new technologies to improve the agricultural practices.Smart farming makes use of IoT devices and contributes in effective decision making.Rice is the major food source in most of the countries.So,it becomes inevitable to detect rice plant diseases during early stages with the help of automated tools and IoT devices.The development and application of Deep Learning(DL)models in agriculture offers a way for early detection of rice diseases and increase the yield and profit.This study presents a new Convolutional Neural Network-based inception with ResNset v2 model and Optimal Weighted Extreme Learning Machine(CNNIR-OWELM)-based rice plant disease diagnosis and classification model in smart farming environment.The proposed CNNIR-OWELM method involves a set of IoT devices which capture the images of rice plants and transmit it to cloud server via internet.The CNNIROWELM method uses histogram segmentation technique to determine the affected regions in rice plant image.In addition,a DL-based inception with ResNet v2 model is engaged to extract the features.Besides,in OWELM,the Weighted Extreme Learning Machine(WELM),optimized by Flower Pollination Algorithm(FPA),is employed for classification purpose.The FPA is incorporated into WELM to determine the optimal parameters such as regularization coefficient C and kernelγ.The outcome of the presented model was validated against a benchmark image dataset and the results were compared with one another.The simulation results inferred that the presented model effectively diagnosed the disease with high sensitivity of 0.905,specificity of 0.961,and accuracy of 0.942.

Effects of Film-Degraded Rice Controlled Release Fertilizer on the Nitrogen Uptake and Yield of the Hybrid Rice

Field experiment was carried out to nitrogen release characteristics of rice controlled release fertilizer (RCRF) coated with natural and half natural high molecular materials, and to thereof effects on the nitrogen uptake and yield of early and late hybrid rice from 1999 to 2000, with urea as control.In experimental fields regardless of early and late seasons, the amount of N in the plants increased exponentially at the early growth stage (y=abx) and nonlinearly at the middle and late growth stages (y=a+bx+cx2).Rice controlled release fertilizer lengthened the exponential phase and increased the parameter -b/c during the nonlinear phase. Although the N amount of plants was less in rice controlled release fertilizer plots man in urea plots within 20 days after transplanting, at the heading and maturity stages, the N amount of plants in rice controlled release fertilizer plots was above two times greater than in the urea plots due to the higher N recovery, and the high absorption density of N in the nonlinear phase.Tillers pattern and achievement of the maximum tillering stage varied with fertilizer types. The maximum tillering stage in the urea plots occurred a week earlier than in the rice controlled release fertilizer plots. Yield sink size and potential sink size of the plants reflected the N absorption pattern and the amount of N in the plants. The yields of early and late rice with 90 kg N ha-1 of rice controlled release fertilizer were respectively increased by 832.7 kg ha-1 and 412.8 kg ha-1 than those with 90 kg N ha-1 of urea, almost equivalent to the yield of early and late hybrid rice with 180 kg N ha-1 of urea.

RDA- CNN: Enhanced Super Resolution Method for Rice Plant Disease Classification

In thefield of agriculture,the development of an early warning diagnostic system is essential for timely detection and accurate diagnosis of diseases in rice plants.This research focuses on identifying the plant diseases and detecting them promptly through the advancements in thefield of computer vision.The images obtained from in-field farms are typically with less visual information.However,there is a significant impact on the classification accuracy in the disease diagnosis due to the lack of high-resolution crop images.We propose a novel Reconstructed Disease Aware–Convolutional Neural Network(RDA-CNN),inspired by recent CNN architectures,that integrates image super resolution and classification into a single model for rice plant disease classification.This network takes low-resolution images of rice crops as input and employs the super resolution layers to transform low-resolution images to super-resolution images to recover appearance such as spots,rot,and lesion on different parts of the rice plants.Extensive experimental results indicated that the proposed RDA-CNN method performs well under diverse aspects generating visually pleasing images and outperforms better than other con-ventional Super Resolution(SR)methods.Furthermore,these super-resolution images are subsequently passed through deep classification layers for disease classi-fication.The results demonstrate that the RDA-CNN significantly boosts the clas-sification performance by nearly 4–6%compared with the baseline architectures.

Dissipation of pencycuron in rice plant

Pencycuron is a non-systemic protective fungicide for controlling sheath blight of rice. However, information on the fate of pencycuron in rice plant is lacking. The degradation of pencycuron in waterlogged tropic rice field was investigated.Pencycuron was applied at recommended field dose (187.5 g a.i./ha) and double recommended dose to cropped plots for three consecutive years. Pencycuron was rapidly degraded in rice plant at all doses of pencycuron application with first order half-lives of 1.57～2.77 d. The study revealed that pencycuron is safe from the human and environmental contamination point of view.

Effect of Percolation Pattern on Yields and Accumulation of Copper and Cadmium in the Rice Plants with Soil Dressing Models

A greenhouse experiment was conducted using stratified paddy field models, which were prepared by polluted soil with 12.5 cm soil dressing. The paddy models were assembled with open and closed percolation system to focus the effect of percolation pattern on accumulation of cupper （Cu） and cadmium （Cd） in rice plants in contaminated paddy filed with soil dressing models. Percolation pattern has significant effect on soil environment, especially redox potential that may influence mobilization of Cd, Cu and other elements. In open system percolation models, the plowsole and subsoil were in oxidative condition （600 mV）, whereas reduction condition （-200 mV） was measured in closed system percolation models. Accumulations of Cu and Cd in all parts of rice plants （roots, grains, stems and leaves） were found higher in an open system percolation with the paddy field model comparatively than in a closed system percolation. The soil redox （Eh） condition influenced by the percolation pattern might be one of the main factors for uptake and accumulation of Cu and Cd in rice plants. The plant height and stem number were found lower in open system percolation comparatively to closed system percolation. In the yields section, the average panicle length, number of panicle and rice grain/hill and weight of grain/hill were lower in open system percolation than the closed system percolation.

Realistic Simulation of Rice Plant

The existing research results of virtual modeling of rice plant, however, is far from perfect compared to that of other crops due to its complex structure and growth process. Techniques to visually simulate the architecture of rice plant and its growth process are presented based on the analysis of the morphological characteristics at different stages. Firstly, the simulations of geometrical shape, the bending status and the structural distortion of rice leaves are conducted. Then, by using an improved model for bending deformation, the curved patterns of panicle axis and various types of panicle branches are generated, and the spatial shape of rice panicle is therefore created. Parametric L-system is employed to generate its topological structures, and finite-state automaton is adopted to describe the development of geometrical structures. Finally, the computer visualization of three-dimensional morphologies of rice plant at both organ and individual levels is achieved. The experimental results showed that the proposed methods of modeling the three-dimensional shapes of organs and simulating the growth of rice plant are feasible and effective, and the generated three-dimensional images are realistic.

Rice plant growth and yield: foliar application of plasma activated water

Plasma activated water(PAW)was prepared for 10 min to be applied one tofive times as a foliar spray to rice plants,to investigate plant growth,yield and the concentrations of total soluble protein and sugar in the rice grains produced.The results reveal that(1)the plant height,stem diameter,dry weight,chlorophyll and total carotene concentrations were improved by∼15%,∼25%,∼24%,∼47%and∼45%,respectively,with respect to control,(2)defense mechanisms of the plants treated with PAW were improved,(3)concentrations of total soluble protein and sugar were enhanced in the rice grains of PAW treated plants and(4)yield was increased by∼14%.

Relationship Between Plant Type and Grain Quality of Japonica Hybrid Rice in Northern China

Plant type and grain quality are two major aspects in rice breeding. Using canonical correlation analysis and canonical redundancy analysis, the relationship between plant type traits and rice grain quality traits was studied with 100 crosses derived from 10 sterile lines × 10 restorer lines. There was a complex relationship between parts of the traits of the two aspects. The angle of the 2nd leaf from the top and single panicle weight played important roles in plant type system and amylose content and grain length in grain quality system. The angle of the 2nd leaf from the top, plant height and single panicle weight had a great effect on grain quality traits, and amylose content, brown rice rate and translucency were easily influenced by plant type traits. Selection index model indicated that japonica hybrid rice in Northern China with good quality was characterized by broad flag leaf and 2nd leaf from the top, narrow and short 3rd leaf from the top, low plant height, short culm, long and more panicles and low single panicle weight.