Paddy Crop Research Articles

Integration of rice-duck on growth and yield of paddy crops (Oryza sativa L.)

This study aims to examine the effect of the number of ducks on the growth and yield of paddy. This research was conducted in Paloh Village, Samalanga District, Bireuen Regency. This research started from July to November 2021. This study used a non-factorial randomized block design with three replications. The treatments of this experiments were the number of ducks per hectare, namely control (without ducks), 1,200 ducks.ha−1(3 ducks/Plot), 1,600 ducks.ha−1 (4 ducks/Plot), 2,000 ducks.ha−1 (5 ducks/ha Plot), 2,400 ducks.ha−1 (6 ducks/Plot), and 2,800 ducks.ha−1 (7 ducks/Plot). The experimental plots size were 5.0 m x 5.0 m and each plot was fenced with plastics. The observation parameters are plant heights, number of tillers, weight of ducks, weed population, number of snails, panicles numbers, panicles length, filled grain weight, empty grain weight, 1000 grains weight, yield potential, and rice yield. The results of this study showed the number of duck on paddy crops had a very significant effect on the parameters of plant height and the number of tillers at 30, 45, and 60 days after planting, filled grain, yield potential, rice yield, duck weight, number of snails, but had no significant effect on the plant biomass (dry weight) parameters, panicles number, panicles length, empty grain weight, and 1000 grain weight and was able to suppress weed populations accurately.

Assessment of Future Climate and Kharif Paddy Yields using Ceres-Rice in the State of Andhra Pradesh

Climate change considerably impacts water needs for agricultural production, particularly in paddy crops (Oryza Sativa). The paddy crop response is uncertain and also heterogeneous due to climate change. Climate variables rainfall and temperature directly impact crop productivity. A precise understanding of crop yields is required for agricultural production management to plan sustainable food demand in the future at the state level. The climate change scenario's impact on rice yield at 0.25° × 0.25° spatial resolution was assessed in Andhra Pradesh and presented in this paper. The use of representative concentration Pathway 8.5 scenario in projections made by the Global Climate Model (GCM) were downscaled for mid-century (2048-2078) using statistical tools. In this study, the Cropping System Model (CSM) and Crop Estimation through Resource and Environment Synthesis (CERES) modules for rice, as part of the Decision Support System for Agro-technology Transfer (DSSAT) package, were utilized. The use of the Regional Crop Yield Estimation System (RCYES) for the Cropping System Model (CSM) within the Decision Support System for Agro-technology Transfer (DSSAT) was facilitated through Python in this study. It is observed that rainfall will decrease during winter and pre-monsoon seasons related to the baseline period (1988–2018) for RCP 8.5. From July to October, there was a significant increase in rainfall. The most considerable change in the rain was 50.7 mm in September. A notable variation between the maximum and minimum temperatures of 2.3 and 2.5 degrees Celsius in June and April respectively. Rainfall is expected to increase in Anantapur, Kurnool and Nellore districts during the mid-century 2040's. The correlation between the baseline and DES mean yield was 0.87, with a maximum yield of 0.86 and a minimum yield of 0.82. Decrease paddy yields by up to 10.7% in West Godavari, Krishna, Guntur, Nellore and Prakasam districts. At the same time, an increase in paddy yields up to 9.8% is anticipated in Srikakulam, Visakhapatnam, Vizianagaram, East Godavari, Anantapur, Chittoor, Kadapa, and Kurnool. In contrast, a maximum decrease of 189.9 mm of rainfall is expected in the Vizianagaram district. These results could assist in devising adaptation measures to reduce the negative effect of climate change on rice crops in Andhra Pradesh.

Impediments and Plausible Suggestions to Farmers in Cyclone Affected Region of Odisha: Kendall's Coefficient of Concordance Approach

Taking into account the farmer's perception of impediments, this study examined the impediments encountered in cyclone ravaged regions as well as their plausible suggestions. Odisha is one of the top 10 ranked climatic vulnerable state of India. 480 km of coastal boundary is exposed to Bay of Bengal and 06 coastal districts are highly vulnerable towards climatic events. As Odisha has an agrarian economy, farmers are severely affected by cyclones. So, the state was purposively selected for the study. Total of 160 respondent farmers were chosen randomly from 8 villages of 2 districts. 20 specific impediments (constraints) were further categorized into 4 broad dimensions of impediments viz., social, economic, environmental, and miscellaneous impediments. Impediments were ranked using Garrett's ranking method, while Kendall's coefficient of concordance approach was executed to rank 4 broad dimensions of impediments. Among 20 impediments, "rain and storms lead to flooding after cyclone" with Garrett's mean value 64.53 was perceived as the most important one. Kendall's coefficient of concordance was significant at 1% significance level (p=.000, <0.01) with the commendable agreement value of 0.588, as it ranges from 0 to 1. Where, Zero denotes nonexistent of agreement among judges, and one denotes perfect agreement with the ?2 value of 282.192 with 3 degrees of freedom. Kendall's coefficient of concordance values for 4 broad impediments were environmental impediment (3.53) was ranked first as constraint followed by economic impediment (2.85), social impediment (2.40) and miscellaneous impediment (1.22). The following suggestions were extracted from the grassroots level investigations viz., attending timely training and awareness programs regarding cyclones, constructions of pucca houses to protect from heavy wind and rain, cultivation of early verities of paddy crops and vegetables, constructing permanent drainage systems, reforestation and afforestation of salt-tolerant mangrove trees, chlorination of drinking water after the cyclone and use of battery operated gadgets to save life post cyclones.

Effect of Nano Nitrogen and Zinc Application on Dry Matter at Different Stages and Grain, Straw Yield of Paddy

A Pot culture experiment was carried out at Agriculture Research Institute, Rajendranagar, To study the impact of Nano Nitrogen in combination with zinc (soil application or foliar spray) on yield, in paddy crop. The soils employed in net house experiment were selected based on low, medium and high zinc availability classes obtained from the zinc analysis data of surveyed samples. They are low (0.4 mg kg-1), medium (0.71 mg kg-1) and high (1.30 mg kg-1). The results revealed that the highest dry matter at Panicle initiation, Grain and Straw yield were observed in the treatment applied with hundred percent recommended dose of nitrogen through NCU granules along with RDPK and soil application of 25 kg zinc sulphate ha-1 resulted in an increase in grain and straw yields by 23 & 24 % over basal application of 1/3rd of 100 % RDN through NCU granules along with RDPK coupled with Nano nitrogen sprays (each at MT & PI stages in rice) and soil application of 25 kg zinc sulphate ha-1

Harvesting and Threshing Methods for Paddy-II: A Review

Threshing of paddy crop is carried out using manual, animal or mechanized power sources depends on the farmland size. In a thresher, rasp bar, spike tooth, peg tooth and wire-loop type threshing elements can be fitted with the threshing cylinder irrespective of direction of crop feed and flow. Different elements are responsible to thresh the crop with different actions which include impact, rubbing, combing, squeezing and their combination. This review was carried out to explore the effect of different threshing elements and threshing methods on performance of paddy threshing. Unlike threshing of other cereal crops, hull removal is not required in paddy. Selection of threshing elements based on the crop to be threshed. The type of threshing element determines the threshing efficiency, energy requirement and grain loss. Among rasp bar, spike tooth, peg tooth and wire-loop type threshing elements, wire-loop type was found to be most suitable for paddy threshing. Factors like cylinder speed, cylinder type and diameter, concave clearance and throughput rate affect the threshing performance. A low speed of cylinder produces more un-threshed grains. It can be compensated using for axial flow thresher as it has high crop retention period. Contrarily, a high speed is responsible for better threshing efficiency along with the more grain breakage and energy consumption. Using tangential flow thresher crop retention period can be minimized. The work rate of pedal and power thresher was, respectively 2 and 10 times more than that of manual threshing. The average threshing efficiency of pedal thresher, power thresher and combine harvester was reported to be 97 to 99%, 96.30 to 99.75% and 98.5%, respectively.

Paddy Crop Disease Detection Using Deep Learning

Agriculture plays a crucial role in human life, with approximately 60% of the population directly or indirectly involved in agricultural activities. Paddy is one of the essential food crops globally and is particularly significant in the Asian subcontinent. As a result of excessive use of chemicals and unpredictable weather patterns, there has been a significant increase in crop diseases. Sometimes an expert may be unavailable to identify the disease. Due to mistaken conclusions of experts, there is an unnecessary use of pesticides which will affect the yield badly, hence, it is essential to know which disease has affected the Paddy crop. Early detection of these diseases is essential to minimize the losses . To address this issue, Deep Learning models, including Artificial Neural Network (ANN), Convolutional Neural Network (CNN), and ResNet101, were employed to detect three types of paddy crop diseases including Leaf Blast (LB), Brown Spot (BS), and Hispa along with the healthy category. The dataset consisted of 6,061 images of three types of disease affected and healthy paddy crops, collected from Paddy Doctor Website and IRRI. ANN Model achieved an accuracy of 66.1%, CNN Model 94.3% and ResNet101 Model 98.2%

CLASSIFICATION OF PADDY LEAF DISEASES WITH EXTENDED HUBER LOSS FUNCTION USING CONVOLUTIONAL NEURAL NETWORKS

Paddy is a major food crop serving more than half the population of people in the world. It is inevitable to improve the quantity and quality of food crop with the growing population. Different factors including soil fertility, water availability, erratic climate variations, diseases, and pests, have an impact on paddy crop yield. It is crucial to identify the root cause for the reduction in yield of paddy. Early disease diagnosis prevents the plants from getting worst through its consecutive stage. The concern with manually diagnosing plant leaf diseases with the naked eye is that the results can be less accurate and even unreliable. Automatic disease diagnosis eliminates the need for experts and provides accurate results. This paper will assist the farmers to identify the leaf diseases automatically with the aid of Convolutional Neural Networks. This research includes paddy leaf disease categories: bacterial blight, blast, tungro, brown spot and healthy leaves. The dataset contains 800 images, 160 images from each of the five categories. Images are resized to 256 * 256 pixels and normalized. The network architecture created with convolutional, maxpooling, flatten and dense layers. The Dataset is divided into training and validation set in 70:30 ratios and model is trained with 20 epochs of batch size 16. The novelty of the study is the implementation of extended Huber loss function for minimizing the loss. Furthermore, it is cross compared with existing loss functions. The Proposed model has achieved 96.63% training accuracy and 86.61% validation accuracy with 5 classes. Performance of model is evaluated with confusion matrix with precision, recall, F1-score and support as parameters.

Comparative Study of Mathematical Model Applications on the Amount of N-P-K Fertilizer Absorbed to Meet the Best Yield Data of Paddy (Rice) Cultivation

Soil-based test studying prevailing to so many crops in Vindhyan alluvial plains from 2001 to 2004 has shown result of production on special rice crop (IR-36) by testing leveraging on soil stoichiometric testing and recommended balanced fertilizers and organic matter amelioration by application for the niche area of impact to targeted yield of paddy crop. The results confirm that soil micro-flora and micro-organisms speed up aeration, drainage, and the best crumby structures, resulting in embryonic fertility and support for crop plants' profuse and vigorous growth through the best soil texture under various agro-climatological divisions in particular. Preliminary and secondary data are calculated after administration of research questionnaire, structure, queue, flow and research objectives, first hand data fulfilment through field tour and experimental block designs under study in paddy-based ecosystem of control and treatment blocks. Nutrients and fertilizers are required for specific accelerated productivity of paddy crop by using control and treatment with specific fertilisers, which is organized in the old mathematical model of [CF (%)] and [CS (%)] gradient. Data in relation to studies of nutrient percentage recommended model development through incursion into stoichiometric trends, analysis, models, algorithms, principles/procedures and quantisation. Regression formulae support the experimental design blocks. Studies by experimental design of blocks replication and finding of experimentations on different mathematical models led to outcome of best efficient recommended fertilizers dose to enrich/replenish the gap of inadequate fertilizers to the paddy (rice) crop to touch our targeted yield of rice crops. Analytical trends and comparison experimentation sheet led to the effort for how much quantity fertilizers are actually needed for paddy crop growth by applying mathematical quantization and qualitative. Under experimental controls, originality of this innovative findings, this research supports systems approach for simplicity, spirituality and sustainability. We have used different mathematical models and three methods and comparing it with traditional method to show the better result of yield data of paddy crop.

Effects of contrasting N-enriched biochar applications on paddy soil and rice leaf phosphorus fractions in subtropical China

Biochar has been proved to be an important soil amendment to alleviate soil phosphorus (P) in the paddy crops. However, the role of specially prepared biochar (N-enriched biochar) on the distribution and transformation of P soil in and rice leaves needs to be revealed. In this study, we studied in a field experiment the effects of two different levels of application of N-enriched biochar on the P fractions of soil and leaves. The results showed that: (1) in early rice, both rates of N-enriched biochar increased soil concentrations of labile inorganic P (Pi) (+51.5 % and +66.2 %, respectively) and labile organic P (Po) (+167 % and + 76.9 %, respectively) and moderately labile Pi (+37.8 % and +27.8 %, respectively) and decreased soil concentration of moderately labile Po (−17.0 % and −52.7 %, respectively) in the 0–15 cm layer. Soil total P concentration was positively correlated with soil labile P fractions and moderately labile Pi concentrations (p < 0.05); (2) in early and late rice, application of the biochar at 4 t ha−1 increased rice leaf concentration of inorganic (+13.3 % and +34.8 %, respectively), nucleic acid (+24.2 % and +13.0 %, respectively) (p < 0.05). The foliar inorganic and nucleic acid P concentrations were positively correlated with foliar total P concentrations; (3) redundancy analysis showed that with the application of N-enriched biochar, soil total carbon (C), nitrogen (N) and P concentration were important factors affecting the chemical forms of soil P, while soil organic matter, soil total P and leaf total P content were important factors affecting the chemical forms of leaf P; (4) allometric growth models showed that under the application of N-enriched biochar, 0–30 cm soil labile Po concentration was positively related to leaf concentration of nucleic acid P, 0–15 cm soil moderately labile Pi concentration was positively related to leaf concentration of inorganic P and nucleic acid P. Thus, this study provides evidence that N-enriched biochar increase the soil P-availability of labile and moderately labile P that in turn improved rice plants P use efficiency.

Development of utility assisting controllers for solarised irrigation system

Several initiatives were taken by the Government of India (GoI) to increase the solar energy generation and had set a target of installing 100 GW grid-connected, solar power projects by 2020. Due to the unreliability of the solarised system and limitations of energy storage systems, grid-connected PhotoVoltaic (PV) has its own advantage over the stand alone systems. Analysis of distribution voltage profile indicates its dependence on the loading of the house and can be slightly different for different utility companies. An attempt is made to develop the irrigation pump controller which will perform the switching while considering the PV generation availability, utility voltage conditions, water availability and other field conditions for irrigating paddy crop in clay loam soil. The low cost, microcontroller-less switching module being developed can perform the pump switching according to PV and water availability, utility voltage and soil moisture condition. In contrast, the microcontroller based system is more flexible and can operate the pump switching according to several sensing quantities like PV generation, trend of the utility voltage over a finite time, crop ripening input, water availability in the reservoir, soil moisture level and temperature and humidity condition in the field. This will ensure the automatic protection of the pump against under-voltage, overvoltage, frequent voltage fluctuations and dry running while assisting the utility grid throughout the day and thereby providing the basic requirements of demand response. Although the microcontroller-less switching system will be simpler and cheaper, the microcontroller based system will have greater versatility and reliability.

Monitoring of Paddy and Maize Fields Using Sentinel-1 SAR Data and NGB Images: A Case Study in Papua, Indonesia

This study addresses the question of how to evaluate the growth stage of food crops, for instance, paddy (Oryza sativa) and maize (Zea mays), from two different sensors in selected developed areas of Papua Province of Indonesia. Level-1 Ground Range Detected (L1 GRD) images from Sentinel-1 Synthetic Aperture Radar (SAR) data were used to investigate the growth of paddy and maize crops. An NGB camera was then used to obtain the Green Normalized Difference Vegetation Index (GNDVI), and the Enhanced Normalized Difference Vegetation Index (ENDVI) as in situ measurement. Afterwards, the results were analyzed based on the Radar Vegetation Index (RVI) and the Vertical-Vertical (VV) and Vertical Horizontal (VH) band backscatters at incidence angles of 30.55°–45.88°, and 30.59°–46.16° in 2021 and 2022, respectively. The findings showed that Sigma0_VV_db and sigma0_VH_db had a strong correlation (R2 above 0.900); however, polarization modification is required, specifically in the maize field. The RVI calculated and backscatter changes in this study were comparable to the in situ measurements, specifically those of paddy fields, in 2022. Even though the results of this study were not able to prove the RVI values from the two relative orbits (orbit31 and orbit155) due to the different angle incidences and the availability of the Sentinel-1 SAR data set over the study area, the division of SAR image data based on each relative orbit adequately represents the development of crops in our study areas. The significance of this study is expected to support food crop security and the implementation of development plans that contribute to the local government’s goals and settings.

Phytoextraction of nickel, lead, and chromium from contaminated soil using sunflower, marigold, and spinach: comparison of efficiency and fractionation study.

Heavy metals in soil pose a serious threat through their toxic effect on the human food chain. Phytoremediation is a clean and green potentially cost-effective technology in remediating the heavy metal-contaminated soil. However, the efficiency of phytoextraction is very often limited by low phytoavailability of heavy metals in soil, slow growth, and small biomass production of hyper-accumulator plants. To solve these issues, accumulator plant(s) with high biomass production and amendment(s) which can solubilize metals in soil is required for better phytoextraction. A pot experiment was conducted to assess the efficiency of phytoextraction of sunflower, marigold, and spinach as affected by the incorporation of Sesbania (solubilizer) and addition of gypsum (solubilizer) in nickel (Ni)-, lead (Pb)-, and chromium (Cr)-contaminated soil. A fractionation study was conducted to study the bioavailability of the heavy metals in contaminated soil after growing the accumulator plants and as affected by using soil amendments (Sesbania and gypsum). Results showed that marigold was the most efficient among the three accumulator plants in phytoextraction of the heavy metals in the contaminated soil. Both sunflower and marigold were able to reduce the bioavailability of the heavy metals in the post-harvest soil, which was reflected in their (heavy metals) lower concentration in subsequently grown paddy crop (straw). The fractionation study revealed that carbonate and organically bound fractions of the heavy metals control the bioavailability of the heavy metals in the experimental soil. Both Sesbania and gypsum were not effective in solubilizing the heavy metals in the experimental soil. Therefore, the possibility of using Sesbania and gypsum for solubilizing heavy metals in contaminated soil is ruled out.

A comparative analysis of cost structure and farm business income: A case study of western Uttar Pradesh

Sugarcane is an important agricultural crop in India, which plays an important role in the national economy, contributing 1.9 percent to the GDP. The crop is cultivated on 5.03 million hectares producing over 384 million tonnes with a productivity of about 75.5 tonnes per hectare. In India, Uttar Pradesh contributes about 47 percent of the area (2.22 million hectares) and production (179.71 million tons) with 47.36 percent of the total sugarcane production. In Western Uttar Pradesh, two cropping systems mainly rice-wheat and sugarcane-wheat cover a large area under different irrigation systems. This study attempts to examine the trends in the production, cost of cultivation, benefits and profitability from sugarcane, wheat and paddy crops to investigate which crop for the farmers of western Uttar Pradesh is more profitable and economical. On an average, the cost of cultivation for sugarcane crop was Rs. 190.42 per quintal and the net return per hectare after subtracting the total cost (Cost C3) from the gross income was Rs. 138278.80. While the cost of production and returns from wheat, paddy and wheat + paddy crops was Rs. 1268.73 per quintal, Rs. 35825.40 per hectare, Rs 1645.32 per quintal, Rs. 34876.60 per hectare and Rs. 1457.02 per quintal and Rs. 70702.00 per hectare respectively. The study indicated that the cost of production per quintal for sugarcane crop was lower than that of wheat and paddy crop, on the other hand net income per hectare was highest in sugarcane crop as compared to wheat and paddy crop. Percent profit and farm business income was also getting higher from sugarcane as compared to wheat and paddy crop. All major crops like paddy, wheat and sugarcane were beneficial to the farmers under the study area, but sugarcane was the more profitable crop as compared to the rest. As the cost per quintal of production as well as returns per hectare sugarcane crop was more economical than wheat and paddy crop.

Investigating the Accuracies in Short-Term Weather Forecasts and Its Impact on Irrigation Practices

The effectiveness of irrigation schedules and crop growth models is largely dependent on the accuracies associated with the most uncertain input parameter, viz. weather forecasts. This research is focused on quantifying the inaccuracies associated with the India Meteorological Department (IMD) issuing short-term weather forecasts (with 1–5 days lead time), and their propagation into irrigation models, with an objective to select the optimal parameters for use with simulation. While precipitation (P) forecasts were directly used, remaining meteorological forecasts were converted to reference evapotranspiration (ET0) forecasts. The effectiveness of the ‘P’ and ‘ET0’ forecasts was found to be low at all lead times. We applied two popular bias correction methods: linear scaling (LS) and empirical quantile mapping (EQM), and observed a marginal improvement in forecast skill. Bias-corrected, forecast-driven irrigation scenarios, along with conventional irrigation (that ignores weather forecast), and a hypothetical perfect 5-day forecast-based irrigation (as reference) system were tested on a water-intensive paddy crop for two growing seasons (S1: monsoon and S2: winter). Conventional irrigation resulted in the highest use of irrigation water (820 mm in S1, 880 mm in S2) and percolation loss (1,140 mm in S1, 680 mm in S2), while achieving a low relative yield (0.88 in S1, 0.87 in S2). LS-corrected forecasts outperformed other scenarios with 20.24%±4.21% and 1.25%±1.51% savings in irrigation costs for S1 and S2, respectively. While IMD forecasts greatly improved irrigation schedules in the monsoon season, their usage for winter crops was found to be trivial. Our findings conclude that LS-corrected IMD forecasts were moderately reliable over multiple lead times and can serve as a valuable addition to irrigation scheduling, provided the contribution of ‘P’ to the total water balance is significant.

Is Minimum Support Price Effective in India? Evidence from State-wise Paddy Procurement

Aims: The paper tries to examine the effectiveness of the minimum support price (MSP) policy based on empirical data on price deviations as well as the procurement of paddy crops by various agencies. The cost and gross margin of cultivation are also analysed to add further reliability to the overall assessment of MSP policy.&#x0D; Data and Methodology: The effectiveness of price policy is examined by studying farm harvest price (FHP) with respect to MSP of Paddy. We have calculated the deviations of FHP of paddy from MSP for the entire study period of 1996-2016, where the positive deviations are taken as an indicator of the effectiveness of price policy. Our study has analysed the procurement data published by the Food Corporation of India (FCI) and the Ministry of Agriculture and Farmers welfare. We also used the unit-level data from the ‘Situation Assessment Survey of Agricultural Households’, 2012-13 of NSSO.&#x0D; Results: The MSP policy is found to be effective in Kerala, Madhya Pradesh, and Punjab but ineffective in other major rice-producing states across the country. And in states like Himachal Pradesh, Uttar Pradesh, Bihar, Assam, West Bengal, Jharkhand, Odisha, Andhra Pradesh, Karnataka, and Tamil Nadu, a vast majority of the medium, semi-medium, and small farmers sell their paddy to private agencies, thus making MSP policy for paddy in those states a complete failure. In states such as Haryana and Maharashtra, large farmers are found selling a significant portion of their total marketed surplus to processors.&#x0D; Conclusion: Overall, at the national level, procurement by government agencies (which stands at 17.2 percent) is far from satisfactory. The policy implication calls for enhancing paddy procurement by government agencies across the farming groups rather than concentrating only on medium and large farmers.

Research Productivity in Ph. D. Thesis in Agronomy of Indira Gandhi Krishi Vishwavidyalaya, Raipur During 2001-2021: A Study

In the present research paper, the research productivity of the subject of Agronomy at Indira Gandhi Agricultural University, Raipur has been studied from 2001-2021. For the study, the data on the subject of Agronomy at Indira Gandhi Agricultural University, Raipur has been collected from Krishikosh of Indian Council of Agricultural Research. Research productivity, authorship productivity, crop distribution, etc. have been described in the study. A total of 54 research works were completed in the subject of Agronomy from 2001-2021, out of which 45 male researchers and 09 female researchers were involved. Highest number of research work was done in year 2016 09, second place in 2017 and 2019, Dr. Narendra Pandey, Dr. G.K. Shrivastava , Dr. M.C. Bhrambri has the maximum number of 06 research scholars and Dr. Rajendra Singh Lakpale, Dr. B.L. Chandrakar , 04 researchers has been directed by Dr. G.S. Tomar and Dr. S.S. Kolhe. Research has been done on the maximum crop paddy and the second number, research has been done on maize.

EVALUASI KEBUTUHAN DAN KETERSEDIAAN AIR IRIGASI DALAM RANGKA PENINGKATAN HASIL PERTANIAN

The availability of water in irrigation areas can affect agricultural productivity. Water balance must be maintained so that there is no shortage of water. Cikunten II has an area of 4.362 ha, mostly in the Tasikmalaya district. This study aims to analyze the water requirement and balance. Data analysis used the KP01 guidelines and the Cropwat program. The data analysis results obtained differences in reference plants' evapotranspiration results using the Modified Penman method in KP and Pennman–Monteith in the Cropwat program. The difference between the two methods is 133,83% due to the difference in albedo coefficients. The effective rainfall for paddy and secondary crops, the KP method analysis is lower than the Cropwat simulation of 110.10%. Availability of water using data from the Ciwulan weir with a reliability of 80% obtained a maximum discharge of 2,73 m3/sec. The water requirement was calculated during planting periods I, II, and II. The KP method is greater than the Cropwat method with a percentage of 277.42% in analyzing water requirements in the Paddy-Paddy-plants cropping pattern. The availability of water in the Cikunten area using Cropwat has fulfilled the needs marked by a more stable k factor than the KP01 method.

Energy conservation prospects in water intensive Paddy-Wheat cropping system for groundwater pumping in the semi-arid region of Haryana.

The study was aimed at identifying the potential energy saving for groundwater pumping through enhanced efficiency of the pump sets. A total of 65 electrically powered tube wells were selected in the Sonipat district of the north Indian State of Haryana to study the energy use efficiency for groundwater pumping. The existing efficiency as well as the minimum expected overall efficiency of the tubewells were determined based on field survey, measurements, and applicable standard code of the Bureau of India Standards. The overall efficiencies of selected tube wells, computed based on actual measured power consumption, varied from 10.1% to 56.6% in the Sonipat block and 15.3% to 52.8% in the Rai block. The average energy requirement, for the selected tube wells, at the current efficiency level was 4,364.0 and 13,100.4 kWh for wheat and paddy crops, respectively, in the Sonipat block, while it was 3,424.8 and 10,280.9 kWh for wheat and paddy crops, respectively, in the Rai block. Analysis revealed that improving overall efficiency from the current level to the minimum expected level can lead to energy savings of 48.3% and 35.9% for tube wells in the Sonipat and Rai block, respectively. In the Rai block, where the groundwater level has declined significantly, the replacement of inefficient pumps should be done in tandem with crop diversification, improving water application efficiency and groundwater status by employing improved irrigation management practices and adopting groundwater recharge techniques.

Bionic Design of Furrow Opener Based on Muskrat Claw-Toe Structure to Improve the Operating Performance of Deep Application of Liquid Fertilizer in Paddy Fields in Cold Region of China

The deep application of liquid fertilizer in paddy fields is a fertilization technique that applies liquid fertilizer deep near the root system of paddy field crops, which can effectively improve the absorption rate of the crops and reduce the amount of fertilizer applied. In the cold regions of China, the soil return rate of the furrowing operation of the deep application of liquid fertilizer in paddy fields is low, which can easily cause the excessive liquid leakage of fertilizer and affect crop growth. Therefore, it is difficult to popularize in large areas. According to the characteristics of paddy soil in the cold regions of China and the operating requirements of a high backfill rate and low disturbance rate of the soil of the deep application of liquid fertilizer, this paper designed a bionic liquid fertilizer deep application furrow opener based on the claw-toe structure of the muskrat. In this study, an indoor soil bin test was conducted by constructing a deep application environment for the liquid fertilizer in paddy fields. The results of the soil bin test showed the effects of the key operating parameters of the bionic design of the liquid fertilizer deep application furrow opener, spraying pressure of the liquid fertilizer and operating speed on the furrowing resistance, soil disturbance rate and the leakage amount of liquid fertilizer. The bionic design of the liquid fertilizer deep application furrow opener has a low soil disturbance rate and leakage amount of fertilizer when the operating speed is 0.8 m s−1, and the spraying pressure is 0.2 MPa. This furrow opener significantly improves the operating performance of the deep application of liquid fertilizer in the cold regions of China and is suitable for the deep application of liquid fertilizer in the paddy fields of this region.

Extensive assessment of climate change impacts on coastal zone paddy growth using multispectral analysis and hydrodynamic modeling

Global warming has led to sea levels raise (SLRs) and Malaysia is no exception to this problem. Especially for low-lying coastal areas including the Kuala Kedah area which is active in agricultural and fisheries activities. Farmers have had to bear up to 75 % of yield losses due to seawater breaches since 2016. Therefore, this study is designed to assess the impact of seawater encroachment on water quality through spatial technology approaches and hydrodynamic modeling related to the growth of paddy trees. The study was conducted during two different paddy cultivation seasons namely Season 1–2019 and Season 2–2019 which take place in the southwest and northeast monsoon in Kuala Kedah, Malaysia. The study involved three phases, which are the assessment of salinity and pH concentration levels, the assessment of the health of paddy crops through multispectral image analysis involving three plant indices (VI), namely Normalized Difference Vegetation Index (NDVI), Blue Normalized Difference Vegetation Index (BNDVI) and Normalized Difference Red Edge (NDRE), and finally, the assessment of the impact of SLR through the numerical method in MIKE 21 for hydrodynamic modeling considering two conditions that are without mitigation factor (K1) and with existing mitigating factor (K2). According to the findings, the salinity concentration trend is decreasing across the growth stage during Season 1–2019, whereas it is the contrary during Season 2–2019. It was discovered that during the study period for both tidal events, 73 % of the 44 sampling points in Season 1–2019, as opposed to just 3 % in Season 2–2019, were categorized as Class 4 and Class 5. Even though there were fluctuations throughout the observation, the pH reading is still within the allowed range of 6.5 to 9.0 for the estuary area. Following that, the ANOVA analysis proved that salinity concentration a statistically significant difference with tidal variations and pH levels. Moreover, the multispectral image analysis findings revealed that the VI value was correlated with both the yield and the health of the rice crop, with R-square values of 0.842 compared to 0.706 and 0.575 for NDVI and BNDVI values, respectively. It confirmed that NDRE granted a more accurate and reliable measurements. Additionally, the hydrodynamic simulation results demonstrated that, if the mitigation factors were considered in the modeling, overflow seawater to the mainland could be reduced by up to 20 %, reducing the impact of coastal flooding on the local area as well as the nearby rice cultivation area. Ultimately, these three elements—water quality, vegetation index, and hydrodynamic modeling—can assist in identifying the underlying cause of the problem and develop short and long-term solutions.