Rice Crop Growth Research Articles

Impact of seed rate and time of sowing on rice fallow crops and their sustainable production system in machine-harvested rice fields

A field experiment was conducted at the Department of Agronomy, Agricultural College and Research Institute, Tamil Nadu Agricultural University, Madurai to study the performance of rice fallow crops in machine-harvested rice fields. The primary objective of this study was to determine the optimal seed rate and the time of sowing rice fallow crops in machine-harvested rice fields. Rice fallow crop cultivation is the most significant low-cost production system in the delta region. However, the sustainability of the system is uncertain in the context of mechanical harvesting of rice using heavy machinery. The crops selected for the experimental trial were black gram (Vigna mungo (L.) Hepper.), sesame (Sesamum indicum), and proso millet (Panicum miliaceum). The field experiment was conducted using a strip plot design. Rice fallow crops were arranged in vertical plots, while various seed rates and sowing timings were arranged in horizontal plots. The results indicated that the sowing time and seed rate significantly influenced the growth and development of rice fallow crops in machine-harvested rice fields. On the day of rice harvest, a 20% increase in seed rate (36 kg ha−1) resulted in greater grain and straw yield among the black gram treatments. The increased seed rate compensated for the damage caused by mechanical harvesting on the day of the harvest when a combine harvester was utilized, increasing the yield and sustainability of the rice fallow crops.

Inhibition of the Germination of Root Parasitic Plants by Zeolitic Imidazolate Framework-8.

Crystalline ZIF-8 (C-ZIF-8) and amorphous ZIF-8 (Am-ZIF-8) were prepared and investigated to control the germination of Striga hermonthica, a root parasitic plant, which threatens cereal crops production particularly in sub-Saharan Africa. We have demonstrated that Am-ZIF-8 shows a better performance than C-ZIF-8 in inhibiting Striga seeds germination. This efficient performance of Am-ZIF-8 materials can be attributed to the incomplete deprotonation of 2 methylimidazole (2MIM) during amorphization, leading to the presence of unsaturated Zn-N coordination with the uncoordinated -NH groups available to undergo hydrogen bonding with the strigolactone analog GR24 forming a more stable Am-ZIF-8⋅⋅⋅GR24 hydrogen bonded network. We further established that application of ZIF-8 materials generally has no adverse effects on the growth and quality of rice crops.

Impact of crop bio-intensification and nutrient management on growth, yield and yield attributes of rice crop under North West Himalayan region of Jammu-Kashmir

The experiment was performed in rabi, zaid and kharif seasons of 2018-19 and 2019-20 to study the bio-intensification possibilities in different cropping systems at Research Farm, Main Campus, Chatha, SKUAST-Jammu, Jammu & Kashmir, India .The experiment was laid out in randomized block design (factorial)/ DMRT with 15 treatments and three replications. Among the crop bio-intensification, rice crop sown under wheat (FIRB)+lentil (B)-summer moongbean -BM+rice (F)+moongbean (B) practice produced significantly higher panicle per meter row length, tillers per meter row length than the crop sown under wheat - rice during both the years of experimentations. Whereas, rice crop sown under wheat-rice practice produced significantly higher grain yield (35.42 q/ha and 36.65 q/ha), than the other existing crop bio-intensification practice during both the years of experimentation. Among the nutrient management, application of 100% in- organic showed significantly higher panicle per meter row length, tillers per meter row length and yield than 100% organic (FYM) and statistically at par with INM (50:50) during both the years of experimentations.

Effect of Integrated Weed Management Practices in Rice (Oryza sativa) Under SRI

An experimental study was conducted at the Annamalai University Experimental Farm in Cuddalore District, Tamil Nadu, between February and May 2023. The objective of this work is to chemically manage the developing weeds in rice during vegetative development using the System of Rice Intensification (SRI) technology. Additionally, the study aims to identify the weed flora in the experimental field. In this study, a Randomised Block Design with three replications was employed. The experimental treatments comprised optimal combinations of chemical and mechanical techniques for weed management. The experiment was structured in a randomised block design, consisting of seven treatments, and subsequently reproduced three times. Among the several treatments, the application of Penoxsulam + Butachlor @ 2L/ha (PE) on 3 days after transplantation (DAT) for rice, and the use of Conoweeder twice on 25 and 35 DAT (rice), effectively decreased weed density and thus reduced weed biomass. This led to an improvement in crop development and production. The greater plant height, drying matter potential (DMP), and grain yield seen with the application of Penoxsulam + Butachlor @ 2L/ha (PE) on 3 days after transplantation (DAT), and Conoweeder twice on 25 and 35 DAT, may be attributed to the effective management of a weed-free environment, especially during critical growth phases of the crop. Suppression of agricultural weed competition facilitated increased growth and development of rice crop, resulting in elevated grain and straw yield.

Statistical Analyses of Weather Conditions Impacts on Consumptive Use for Rice Production in Sulaimani Province

In this study, we show the impact of climate on the rate of consumption of water for production of rice as an agricultural product in Sulaymaniyah governorate, Various data was obtained from multiple weather stations including (Dukan, Chwarta, Penjween, Bazian, Sulaymaniyah and Darbandikhan) from the year 2003until 2016, and also determing those climate factors that have positive and negative influences on the consumption use of water .Thorinthweet equation was used to estimate the amount of potential evapotranspiration using rice plant coefficient.In this investigation, we depend on Description method to describe the relationship between climate elements and consumption of water, with Comparing method to compare consumption of water between the metrological stations, and Depending on this mathematical formula, the amount of water consumption in the study area was also found. Furthermore, effects of geographical distribution at both seasonal and periodic levels of rice crop growth were identified. Our aim in this investigation is the ability to irrigate our crops in a scientific way. Detailed statistical analysis revealed that climatic factors exert great influences of almost 99%, The temperature may come in the first degree for the positive reasons, and for the moisture component in the first degree for the negative reasons.

Utilization of Rhodopseudomonas palustris in Crop Rotation Practice Boosts Rice Productivity and Soil Nutrient Dynamics

Using beneficial microorganisms, such as purple non-sulfur bacteria (PNSB), has shown enormous potential for improving plant growth and agricultural production. However, the full extent of their benefits and interactions with agricultural practices is yet to be fully understood. The present study aimed to investigate the use of PNSB in crop rotation practice, focusing on its impact on rice growth and yield. The experiment was conducted over two rice cropping seasons, with djulis grown between the rice as a rotation crop. The study shows that PNSB treatment increased the concentration of 5-aminolevulinic acid (5-ALA) in plants, indicating enhanced photosynthesis. Moreover, when combined with crop rotation, PNSB remarkably improved soil fertility. These combined benefits resulted in substantial increases in tiller numbers (163%), leaf chlorophyll content (13%), and lodging resistance (66%), compared to the untreated plants. The combined treatment also resulted in higher productive tillers per hill (112%), average grain per hill (65%), and grain fertility (26%). This led to increased grain yield (65%), shoot dry weight (15%), and harvest index (37%). The findings clearly suggest that the incorporation of PNSB in crop rotation strategies can significantly augment the growth and yield of rice crops. These insights, pivotal for sustainable rice cultivation, hold the potential to simultaneously tackle the pressing issues of global food security and climate change.

Physiological and Biochemical Basis of Variation in Yield of Rice (Oryza sativa L.) under CA-based Crop Establishment Methods and Nutrient Management in R-W Cropping System

Background: Crop establishment methods and nutrient management practices treatments were continuously practiced in the same plots since 2011-12 as a part of long-term experiment. A field study was conducted during 2019-2020 and 2020-2021 i.e. during 9th and 10th year of study to investigate the effects of CE methods and nutrient management on growth, physiological, biochemical, yield attributes and yield of rice crop. Methods: Field experiments were carried out at the Agricultural Research Farm, Banaras Hindu University, Varanasi, laid out in split plot design replicated thrice with four crop establishment (CE) methods viz., CT (puddled transplanted) rice-CT wheat (CE1),CTDSR rice-CT wheat (CE2), CTDSR- ZT wheat (rice residue retention) (CE3), ZT rice-ZT wheat (residue retention in rice and wheat) (CE4) in main plots and three nutrient management (NM) practices viz., FP (164 kg N, 50 kg P2O5, 32 kg K2O and 4 kg Zn ha-1) (N1), RFD (150 kg N, 60 kg P2O5, 60 kg K2O and 5 kg Zn ha-1) (N2) and SSNM- RWCM recommendation (N3). The rice variety used was ‘Sarju-52’ in the present study. Result: The recorded data revealed that ZT rice–ZT wheat (CE4) recorded significantly higher plant height, tillers hill-1, leaf area, RWC, total chlorophyll content and protein content as compared to other CE methods. Among NM practices, SSNM-RWCM (N3) recorded significantly higher plant height, tillers hill-1, leaf area and protein content, whereas, RWC and total chlorophyll content did not differ significantly over farmer’s practice and recommended fertilizer dose. Improved growth and physio-chemical attributes in ZT rice-ZT wheat (CE4) and SSNM-RWCM (N3) resulted in significantly higher panicles hill-1, fertility percentage and number of filled grains panicle-1 over other CE methods and NM practices. Panicle length, spikelets panicle-1 and test weight showed non-significant differences. Grain yield, straw yield and biological yield were significantly higher in ZT rice-ZT wheat (CE4) among CE methods and SSNM-RWCM (N3) among NM practices. The harvest index showed non-significant differences for CE methods and NM practices both.

Mapping Leaf Area Index at Various Rice Growth Stages in Southern India Using Airborne Hyperspectral Remote Sensing

Globally, rice is one of the most important staple food crops. The most significant metric for evaluating the rice growth and productivity is the Leaf Area Index (LAI), which can be effectively monitored using remote sensing data. Hyperspectral remote sensing provides contiguous bands at narrow wavelengths for mapping LAI at various rice phenological stages, and it is functionally related to canopy spectral reflectance. Hyperspectral signatures for different phases of rice crop growth was recorded using Airborne Visible Near-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) along with corresponding ground based observations. Ground-based hyperspectral canopy spectral reflectance measurements were recorded with FieldSpec 3 Hi-Res spectroradiometer (ASD Inc., Forsyth County, GA, USA; spectral range: 350–2500 nm) and LAI data from 132 farmer’s fields in Southern India. Among 29 hyperspectral vegetation indices tested, 8 were found promising for mapping rice LAI at various phenological stages. Among all the growth stages, the elongation stage was the most accurately estimated using vegetation indices that exhibited a significant correlation with the airborne hyperspectral reflectance. The validation of hyperspectral vegetation indices revealed that the best fit model for estimating rice LAI was mND705 (red-edge, blue, and NIR bands) at seedling and elongation, SAVI (red and NIR bands) at tillering and WDRVI (red and NIR bands) at booting stage.

Spatial Variability of Selected Soil Chemical Parameters in Low-yielding Paddy Production Block in Mahaweli System H, Sri Lanka

Although water availability for paddy production in Mahaweli System H is abundant, paddy yield is lower in Nochchiyagama (278 km2), chosen for soil assessment. Paddy yield data were used to identify the low-yielding division using the area-weighted average. Twenty-five random locations were generated, and soil samples were collected for pH, soil conductivity (EC), salinity, and total dissolved solids (TDS) analysis. ArcGIS software was used to create spatial distribution maps and related geostatistical analyses for each parameter. Vector files were created with their associated properties, and thematic maps were generated using spatial interpolation techniques, such as universal kriging (UK), ordinary kriging (OK), and inverse distance weighted (IDW) methods of interpolation techniques to identify the best interpolation method for soil chemical parameters mapping. The entire Nochchiyagama land was observed to have a slightly acidic pH (5.6-5.9) range that may have affected rice crop growth due to nutrient mobility and uptake issues. The spatial interpolation evaluation suggests that at least two-thirds of the area observed for lower TDS levels (591-654 mg/L) is potentially unsafe paddy production. Elevated levels of EC (3.1-7.24 dS/m) along with TDS may lead to physiological drought due to interferences in ion uptake. In overall, spatial interpolation evaluation indicators suggest that the UK method was observed with a lower mean relative error (MRE) than the other two interpolations. However, EC distribution showed low MRE in both IDW and OK interpolation techniques. The IDW method was observed to have a lower RMSE (Root mean square error). The UK spatial interpolation performed better for TDS and salinity predictions than other methods. This study found consistent regional differences in low paddy yields in Mahaweli system H using the UK method for analyzing soil chemical parameters. 
 Keywords: Electrical conductivity, Interpolation errors, Salinity, Spatial interpolation

Effects of agro based organic amendments on growth and cadmium uptake in wheat and rice crops irrigated with raw city effluents: Three years field study

Cadmium (Cd) accumulates in the vegetative tissues of rice and wheat crops, posing a serious threat in the food chain. A long-term field experiment was conducted to investigate the effects of rice husk biochar (RHB), farm manure (FM), press mud (PrM), and poultry manure (PM) on the growth, yield, and economics of wheat and rice crops grown with sewage water. The results showed that RHB increased wheat plant height (27%, 66%, 70%), spike-length (33%, 99%, 56%), straw yield (21%, 51%, 49%), and grain yield (42%, 63%, 65%) in year-1, year-2, and year-3, than respective controls. For rice crop, RHB showed the maximum increase in plant height (64%, 92%, 96%), spike length (55%, 95%, 90%), straw yield (34%, 53%, 55%), and grain yield (46%, 66%, 69%) each year (2019–2021), compared to their respective controls. The Cd immobilization was increased by the application of RHB while other treatments followed FM > PrM > PM > control in each year of wheat and rice crops. For year-1, benefit-cost ratio remained maximum with the application of FM while for the 2nd and 3rd years in sequence, RHB proved more economical than other treatments and consistently produced wheat and rice with lower Cd concentration than FM, PrM, and PM in grains. This long-term experiment suggested that the application of organic amendments consistently increased biomass of rice and wheat and decreased the Cd concentration in tissues. The RHB remained more effective compared with FM, PrM, and PM in terms of yield, low Cd accumulation and economics of rice and wheat crops.

Response of integrated use of humic acid and chemical fertilizer on growth and yield of rice crop (Oryza sativa L.) in calcareous soil

Response of integrated use of humic acid and chemical fertilizer on growth and yield of rice crop (Oryza sativa L.) in calcareous soil

Soil moisture simulation of rice using optimized Support Vector Machine for sustainable agricultural applications

The growth and development of rice crops primarily depend on appropriate soil water balance for which soil moisture is the key determinant. Soil moisture is a crucial parameter in the hydrological cycle, which has a vital role in optimal water management for sustainable agricultural growth as it has a significant impact on hydrological, ecological, and climatic processes. Thus, accurate estimation of soil moisture is important otherwise it will drastically reduce crop yields, intensifying the global food crisis. A novel soil moisture prediction model (SVM-COLGWO) that incorporates the Grey Wolf Optimizer (GWO) into Chebyshev chaotic maps and opposition-based learning to optimize the Support Vector Machine (SVM) model is proposed. The suggested model simultaneously increases the simulated model’s accuracy while speeding up global convergence. To evaluate the proposed model, the prediction performance is compared with other hybrid and standalone models where the feasibility of the proposed model is validated through superior simulation results (MAE = 0.167, MSE = 0.179, RMSE = 0.423, MAPE = 0.162, and R2= 0.949) including Shannon’s Entropy. Thus, based on accurate soil moisture simulation through the proposed model, irrigation can be effectively scheduled for sustainable rice growth.

Evaluation of Physiological and Biochemical Traits in Relation to Sodicity Tolerance in Selected Rice Genotypes under Different Sodicity Levels

Background: Soil sodicity is becoming a serious problem which is increasing every year has a negative impact the physical and nutritional qualities of the soil and plant which has an immense adverse effect on crop growth. Sodicity tolerance includes the manifestation of biochemical and physiological variations. Understanding these physiological and biochemical mechanism in rice is one of the biological solution for increasing the yield of crops through increased tolerance mechanism. Methods: A field experiment was conducted at Anbil Dharmalingam Agricultural College and Research Institute, Tiruchirappalli, Tamil Nadu to evaluate the performance of different rice varieties i.e., TRY 1, CO 43, TRY 2, CSR 27, TRY 3, white ponni (WP) with particular reference to Exchangeable Sodium Percentage (ESP) at various levels viz., ESP 8, 16, 24, 32, 40 and 48 and its impact on physiological and biochemical components. Plant samples were collected at flowering stage was analyzed for chlorophyll, sugars and proline content. Grain and straw yield of the crop was recorded. Result: The Chlorophyll and non-reducing sugars showed decreasing trend with increasing ESP levels but proline, reducing sugar and total sugar showed an increasing trend with increasing sodicity levels. The variation in biochemical and physiological components had significantly affected the growth and yield of rice crop. Among different rice varieties TRY 3 was found to be superior at increasing sodicity levels..

Rainy season and crop calendars comparison between past (1950–2018) and future (2030–2100) in Madagascar

AbstractThis paper analyzes rainfall data to characterize the rainy season and define rice and maize crop calendars for current and future conditions in Madagascar. The daily rainfall data are taken from observational climate records and climate model simulations from the CMIP6 under the SSP245 and SSP585 scenarios. Rainy season characteristics are calibrated to fit rice and maize crop growth stages. The comparison between the past (1950–2018) and the future (2030–2100) highlights changes in the onset and cessation dates, which happen later and earlier, respectively. This causes the reduction of the rainy season duration, which affects the rice and maize crop calendars, especially its sowing or seeding periods. The worst (best) case is mainly observed in the southeast (southwest). On the one hand, the southwestern region may need to adapt to grow rice and maize crops with short or medium crop cycles in the future. In the Highland or Central land, the length of the sowing or seeding period increases. On the other hand, the North and East face a significant reduction in the length of the sowing or seeding period. Rice endures more than maize. Growing rice crops twice a year may not be possible in the future. But rather, we observe minor changes in the West. Our analysis suggests the imperative necessity to advise smallholder farmers to rely on short crop cycle varieties of rice and maize crops. Predominantly, the harvesting period is postponed. It is recommended to carefully consider our results for the definition of food policies.

Production potential of short duration rice (Oryza sativa) in relation to age of seedlings, date of transplanting and crop geometry

An experiment was conducted at the research farm of Punjab Agricultural University, Ludhiana, Punjab during 2018 and 2019 to determine the production potential of rice (Oryza sativa L.) in relation to age of seedlings, date of transplanting and crop geometry. The results revealed that growth and productivity of short duration rice crop were improved by transplanting younger seedlings of 3 and 4 weeks age (nursery sown on June 12 and June 19) as compared to the older ones 5 and 6 week old seedlings (nursery sown on May 29 and June 5). Transplanting of rice at 25th June and 10th July with 20 cm × 15 cm crop geometry recorded better growth, yield attributes and higher yield as compared to 15 cm × 15 cm crop geometry. Rice transplanted on 10th July required fewer irrigations (14 and 17) as compared to the crop transplanted on June 25 (16, 19) in 2018 and 2019, respectively. This led to a water saving of 12.5 and 10.5% during those respective years, without compromising the yield. It is worth noting that a single irrigation was applied at a depth of 7.5 cm. For higher saving in irrigation water, nursery of PR 126 can be sown up to June 20 and 25–30 days old seedlings can be transplanted up to July 10 at 20 cm ×15 cm spacing.

Identification of rice leaf diseases and deficiency disorders using a novel DeepBatch technique.

Rice is one of the most widely consumed foods all over the world. Various diseases and deficiency disorders impact the rice crop's growth, thereby hampering the rice yield. Therefore, proper crop monitoring is very important for the early diagnosis of diseases or deficiency disorders. Diagnosis of diseases and disorders requires specialized manpower, which is not scalable and accessible to all farmers. To address this issue, machine learning and deep learning (DL)-driven automated systems are designed, which may help the farmers in diagnosing disease/deficiency disorders in crops so that proper care can be taken on time. Various studies have used transfer learning (TL) models in the recent past. In recent studies, further improvement in rice disease and deficiency disorder diagnosis system performance is achieved by performing the ensemble of various TL models. However, in all these DL-based studies, the segmentation of the region of interest is not done beforehand and the infected-region extraction is left for the DL model to handle automatically. Therefore, this article proposes a novel framework for the diagnosis of rice-infected leaves based on DL-based segmentation with bitwise logical AND operation and DL-based classification. The rice diseases covered in this study are bacterial leaf blight, brown spot, and leaf smut. The rice nutrient deficiencies like nitrogen (N), phosphorous (P), and potassium (K) were also included. The results of the experiment conducted on these datasets showed that the performance of DeepBatch was significantly improved as compared to the conventional technique.

Pyramiding of transcription factor, PgHSF4, and stress-responsive genes of p68, Pg47, and PsAKR1 impart multiple abiotic stress tolerance in rice (Oryza sativa L.).

Abiotic stresses such as drought, salinity, and heat stress significantly affect rice crop growth and production. Under uncertain climatic conditions, the concurrent multiple abiotic stresses at different stages of rice production became a major challenge for agriculture. Hence, improving rice's multiple abiotic stress tolerance is essential to overcome unprecedented challenges under adverse environmental conditions. A significant challenge for rice breeding programs in improving abiotic stress tolerance involves multiple traits and their complexity. Multiple traits must be targeted to improve multiple stress tolerance in rice and uncover the mechanisms. With this hypothesis, in the present study gene stacking approach is used to integrate multiple traits involved in stress tolerance. The multigene transgenics co-expressing Pennisetum glaucum 47 (Pg47), Pea 68 (p68), Pennisetum glaucum Heat Shock Factor 4(PgHSF4), and Pseudomonas Aldo Keto Reductase 1 (PsAKR1) genes in the rice genotype (AC39020) were developed using the in-planta transformation method. The promising transgenic lines maintained higher yields under semi-irrigated aerobic cultivation (moisture stress). These 15 promising transgenic rice seedlings showed improved shoot and root growth traits under salinity, accelerating aging, temperature, and oxidative stress. They showed better physiological characteristics, such as chlorophyll content, membrane stability, and lower accumulation of reactive oxygen species, under multiple abiotic stresses than wild-type. Enhanced expression of transgenes and other stress-responsive downstream genes such as HSP70, SOD, APX, SOS, PP2C, and P5CS in transgenic lines suggest the possible molecular mechanism for imparting the abiotic stress tolerance. This study proved that multiple genes stacking as a novel strategy induce several mechanisms and responsible traits to overcome multiple abiotic stresses. This multigene combination can potentially improve tolerance to multiple abiotic stress conditions and pave the way for developing climate-resilient crops.

Effects of Root Growth of Deep and Shallow Rooting Rice Cultivars in Compacted Paddy Soils on Subsequent Rice Growth

Rice is often grown as multiple seasons in one year, alternating between flooded and upland systems. A major constraint, introduced from the flooded system, is a plough pan that may decrease rooting depth and productivity of follow-on upland rice. Roots penetrating the plough pan under flooded rice system can leave a legacy of weaker root growth pathways. Deeper rooting rice cultivars could have a bigger impact, but no direct evidence is available. To explore whether a deep rather than a shallow rooting rice cultivar grown in a flooded cropping cycle benefited deeper root growth of follow-on rice in an upland, reduced tillage cropping cycle, a simulated flooded paddy in greenhouse was planted with deep (Black Gora) and shallow (IR64) rooting cultivars and a plant-free control. Artificial plough pans were made in between the topsoil and subsoil to form different treatments with no plough pan (0.35 MPa), soft plough pan (1.03 MPa) and hard plough pan (1.70 MPa). After harvest of this ‘first season’ rice, the soil was drained and undisturbed to simulate zero-tillage upland and planted rice cultivar BRRI Dhan 28. The overall root length density (RLD), root surface area, the numbers of root tips and branching of BRRI Dhan 28 did not vary between plough pan and no plough pan treatments. Compared with the shallow rooting rice genotype, the deep rooting rice genotype as ‘first season’ crop produced 19% greater RLD, 34% greater surface area and 29% more branching of BRRI Dhan 28 in the subsoil. In the topsoil, however, BRRI Dhan 28 had 28% greater RLD, 35% greater surface area and 43% more branching for the shallow rather than deep rooting genotype planted in the ‘first season’. The results suggested that rice cultivar selection for a paddy cycle affects root growth of a follow-on rice crop grown under no-till, with benefits to subsoil access from deep rooting cultivars and topsoil proliferation for shallow rooting cultivars.

Rice crop growth monitoring with sentinel 1 SAR data using machine learning models in google earth engine cloud

The rainfed rice crop monitoring and yield prediction have been Herculean task with optical remote sensing systems operation under cloud cover. The free-of-cost sentinel 1 based SAR data along with machine learning models in GEE cloud was used for rainfed rice crop monitoring for 214 farm plots on a micro-scale in Hooghly, West Bengal, India. The individual plot rice parcel showed a low median backscattering signature for the SAR data during the land preparation/crop transplanting stages with VH and VV at −17.63 dB and −9.63 dB, respectively; whereas, higher median backscattering was experienced at the peak vegetation stage of VH and VV Polarization with −15.20 dB and −6.34 dB, respectively. The random forest model was found best suited with R2 of 0.87 for total crop biomass estimation. The backscatter values have a sound correlation with Heading NDVI, which validated the suitability of SAR images for crop monitoring under rainfed conditions. Further, crop yield prediction using SAR data and total biomass data through machine learning models showed positive correlation for Random forest, Extreme gradient boosting, and Decision tree models with an Area under receiver operating characteristics curve (AUROC) test accuracy of 0.99. These low-cost, high temporal SAR data based models can be used for near real-time crop monitoring even under overcast conditions in near future.

Effect of Different Planting Geometry and Nitrogen Levels on Growth and Yield of Rice Crop (Oryza sativa L.)

Effect of Different Planting Geometry and Nitrogen Levels on Growth and Yield of Rice Crop (Oryza sativa L.)