Indian Conditions Research Articles

Impact of regenerative farming practices on soil quality and yield of cotton-sorghum system in semi arid Indian conditions.

Regenerative agricultural practices, i.e. organic and natural farming, are rooted in India since ancient times. However, the high cost of production, lack of organic pest control measures and premium price of organic produces in chemical agriculture encourage natural farming. In the present study, the quality improvement of calcareous soils under organic (OGF) and natural (NTF) management was compared with integrated conventional (ICF) and non-invasive (NIF) farming practices with cotton-sorghum crops over three consecutive years. A total of 23 soil attributes were analyzed at the end of the third cropping cycle and subjected to principal component analysis (PCA) to select a minimum data set (MDS) and obtain a soil quality index (SQI). The attributes soil organic carbon (SOC), available Fe, pH, bulk density (BD) and alkaline phosphatase (APA) were selected as indicators based on correlations and expert opinions on the lime content of the experimental soil. The SQI was improved in the order of OGF (0.89) > NTF(0.69) > ICF(0.48) > NIF(0.05). The contribution of the indicators to SQI was in the order of available Fe (17-44%) > SOC (21-28%), APA (11-36%) > pH (0-22%), and BD (0-20%) regardless of the farming practices. These indicators contribute equally to soil quality under natural (17-22%) and organic (18-22%) farming. The benefit:cost ratio was calculated to show the advantage of natural farming and was in the order of NTF(1.95-2.29), ICF (1.34-1.47), OGF (1.13-1.20) and NIF (0.84-1.47). In overall, the natural farming significantly sustained the soil quality and cost benefit compared to integrated conventional farming practices.

Advancements in Deep Learning for Autonomous Driving in Indian Road Conditions

Recent advancements in deep learning techniques tailored for autonomous driving in Indian road conditions are crucial for revolutionizing transportation systems. Indian roads present unique challenges, including unpredictable traffic patterns, diverse road infrastructures, and challenging weather conditions. Deep learning is pivotal in addressing these challenges, focusing on perception, decision-making, and control. Various architectures, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Deep Reinforcement Learning (DRL), are analyzed for their efficacy in autonomous driving. Sensor fusion techniques enhance perception capabilities, such as lidar, radar, and camera data integration. Additionally, advancements in semantic segmentation and object detection algorithms improve scene understanding and obstacle recognition. Collaborative efforts between academia, industry, and government agencies are essential for accelerating the deployment of autonomous driving technology in Indian road conditions. In conclusion, leveraging cutting-edge deep learning methodologies enables safe and efficient navigation of autonomous vehicles, ushering in a transformative future in transportation systems.

Effect of Organics on Yield and Yield Components of Chia (Salvia hispanica L.)

Chia (Salvia hispanica L.) is a new emerging crop as functional food. Its seeds are richest source of omega-3, antioxidant, calcium and are known to prevent heart disease, diabetes and cancer. Owing to its nutraceutical and therapeutical values, the studies on its organic production are very essential under Indian condition. Therefore, an experiment to determine the influence of organic fertilization on growth and yield of chia was done at Jabalpur, Madhya Pradesh during 2018-19 and 2019-20. The recommended fertilizers dose (RDF) 57.5:40:24 NPK kg ha-1 with FYM 10 t ha-1 was compared with fourteen treatment combinations of organic manures viz., vermicompost (V), bio gas spent slurry (BSS) and Neem cake (Nc) at 25% or 50%N equivalent dose of RDF and organic supplements namely, microbial consortia (M), Jeevamrita (J) and humic acid (H).
 The maximum plant height, number of branches per plant, number and weight of spikes per plant, spike weight, dry matter, seed yield per plant and seed yield per hectare were higher under RDF which was at par with FYM50V25BSS25MJH, RDFM, RDFJ. During first year, RDF recorded the higher yield (835.67 kg ha-1) followed by RDFMJH (680.93 kg ha-1), RDFJ (665.84 kg ha-1), FYM50V25BSS25H (616.19 kg ha-1) and FYM50V25BSS25 (603.57 kg ha-1). During first year, chia resulted in lower yield in comparison to second year in all the treatments. The reproductive phase, blooming to seed filling was found sensitive to frost. During second year RDFMJH gave higher yield (1201.65 kg ha-1) and was at par to FYM50V25BSS25M (1186.28 kg ha-1), FYM50V25BSS25J (1165.71 kg ha-1) and RDF (1165.43 kg ha-1). Therefore, the RDF can be substituted by organic manures combination viz. FYM 10.7 t + vermicompost 1.07 t + biogas spent slurry 1.68 t ha-1 along with microbial consortia or with Jeevamrita.

Driver behavior modeling at uncontrolled intersections under Indian traffic conditions

Driver behavior modeling at uncontrolled intersections under Indian traffic conditions

Young tree performance of grapefruit varieties (Citrus paradisi Macf.) under central Indian conditions

Young tree performance of grapefruit varieties (Citrus paradisi Macf.) under central Indian conditions

Plant bioregulators induced manipulation in the yield attributes of mango cv. Langra

The present study was carried out in two successive years to evaluate the comparative efficacy of CPPU and NAA combination in improving the yield attributes of Langra mango. Higher fruit drop and low fruit retention are the most critical constraints for mango production under north Indian conditions. Fruit drop starts occurring just after fruit set and continues till harvest, leading to substantial economic loss to the growers. The foliar application of CPPU 10 ppm + NAA 20 ppm and CPPU 20 ppm + NAA 30 ppm immediately after the fruit set resulted in a significant reduction in fruit drop in comparison to the control (water spray). Various physical attributes like endocarp size (5.16 cm), pedicel length (1.20 cm), pedicel thickness (4.02 mm), fruit weight (248.12 g), fruit size (7.46 cm width and 9.83 cm length), fruit volume (243.52 cc), and specific gravity (1.02) got improved with CPPU 10 ppm + NAA 20 ppm followed by CPPU 20 ppm + NAA 30 ppm than the control. In conclusion, the spray of CPPU 10 ppm + NAA 20 ppm proved to be an effective treatment for managing fruit drop and improving yield attributes in Langra mango.

Reliable and consistent genotype selection for leaf biomass and natural sennosides yield across multi-environments in Senna (Senna alexandrina Mill)

The relationship between genotype and season significantly hinders the development of stable genotype selection and improved genotypes for senna breeding programs. This study aimed to assess stable, high-yielding senna genotypes under South Indian conditions. Twenty-five different senna genotypes were tested for yield stability using a randomized, completely-block design. The additive main effects and multiplicative interaction (AMMI) model was used to investigate the relationships between genotype (G), environment (E), and genotype × environment. Based on the findings, the three genotypes—GEN 1, GEN 9, and GEN 18—might be recommended for large-scale production. Stable and high-yielding genotypes should be the main genetic resources used in senna-based cropping season breeding programs.

Geospatial modeling and mapping of soil erosion in India

Soil erosion generally removes the topmost fertile layer of soil, affecting agricultural productivity on a larger scale. As a significant portion of the Indian economy depends on agricultural productivity, granular assessment of the impact of soil erosion becomes critical. However, a national-scale assessment of soil erosion and an impact classification system currently doesn’t exist over India. Given the resource-intensive and time-consuming nature of field experiments required for the measurement of soil loss across a vast country, the Revised Universal Soil Loss Equation (RUSLE) was extensively utilized for soil erosion calculations due to its simplicity, streamlined data requirements, and accuracy. This study estimates the yearly potential soil loss throughout India at a spatial resolution of 250 m and quantifies its variability considering districts, soil texture, soil type, land use and land cover, and basins. The relative importance of individual and combined impact of multiple parameters on quantified soil loss has been assessed using a random forest model. Rainfall erosivity (R-factor) emerges as the most crucial feature in estimating soil erosion in Indian conditions while rainfall intensity, combined with the topographic factor, demonstrated the highest influence on soil erosion in Indian conditions when the combined impact was assessed. Further, we mapped the Sediment Delivery Ratio (SDR) and Specific Sediment Yield (SSY) to assess the actual soil loss reaching downstream of basins across the national boundary. The national mean values for Sediment Delivery Ratio (SDR) and Sediment Yield (SSY) stand at 0.11 and 2.61 tons per hectare per year, respectively. The yearly potential soil loss for India is calculated at 21 tons per hectare per year, and nine out of the twenty districts with the highest susceptibility to soil erosion are in the state of Assam. Finally, a novel impact-based erosion-severity classification system has been introduced which finds that 29.46% of the landmass is prone to minor erosion while 3.17% experiences catastrophic erosion. This is the first comprehensive national-scale assessment of both soil erosion and sediment yield mapping over India, and the consequent classification system will enable the planning and implementation of soil conservation strategies locally as well as nationally.

GODI India: a kickstart to innovative batteries for electric vehicle

Research methodology The case is based on the data collected from various secondary sources only. Case overview/synopsis Godi India, a lithium-ion cell manufacturing company in India, was working to design e-cell for electric vehicles (EV) which would be compatible with Indian conditions and reduce the cost of battery to the extent possible because e-cell contributes half of the electric vehicle’s price. Godi India was set up in January 2020 by Mahesh Godi. Looking for opportunities in India after having worked in the USA for 17 years, Mahesh found that even with the rise in EV the lithium-ion cell manufacturing in India was almost zero. Using innovation as its main strategy, the start-up started its operation with a team of 30 scientists. The start-up already registered 25 patents under its name with few awaiting. Most of the EV companies relied on Chinese lithium-ion cell. Local lithium-ion cell manufacturing was believed to be the key for EV industry growth in a country. Central government production linked schemes worth INR 18,100 crore were signed by major players like Ola electric, Reliance new energy and Rajesh exports to develop locally manufactured advance cells. The push from the government for locally manufacturing the cells was a major trigger for the rise in the EV industry. The case provides the analysis of the strategies applied by the company to grow in the lithium-ion cell manufacturing industry. Complexity academic level This case can be used in strategic management, entrepreneurship and general management courses/modules at the Undergraduate and Postgraduate level.

Development of high-amylose maize (Zea mays L.) genotypes adapted to Indian conditions through molecular breeding

Context Amylose is a type of resistant starch with numerous health benefits and industrial applications. Starch from maize (Zea mays L.) usually has an amylose content of ~25%. Aims The aim was to develop high-amylose maize genotypes suitable for human consumption and adapted to Indian conditions. Methods Marker-assisted backcross breeding was used to transfer the mutant ae1 allele from a high-amylose donor from the USA into the three parents (HKI 1344, HKI 1378, HKI 1348-6-2) of two high-yielding white maize hybrids (HM5 and HM12) grown in India. Key results In converted lines, amylose content was 40.40–58.10% of total kernel starch, compared with 22.25–26.39% in parents. The percentage increase in amylose content was 63.70–153.03%. There was a significant amount of background recovery in each backcross generation: 66.80–79% in BC1F1, 72.85–88.60% in BC2F1, and 84.45–93.70% in BC2F2. Overall, the total kernel starch content was reduced (by ~22%) in the ae1-introgressed families. Conclusions The converted lines developed in the study are enriched with kernel amylose while showing significant background recovery. Implications The high-amylose lines developed may be highly beneficial for diabetic patients and in the bioplastics industry, and should be suitable for growing under Indian conditions.

Field calibration protocol for optical-based air quality sensors in Indian conditions

The calibration process of the sensor/instrument governs sensor accuracy and needs to be dynamic. Optical air quality sensors (PM2.5) were collocated with reference monitoring stations for two weeks. The sensors were installed at different distances from the reference instrument and rotated twice. The performance parameters, such as inter-node variability and correlation between concentration data, were evaluated using statistical descriptors. Finally, the data was calibrated by the reverse regression method. The results are in close agreement with the reference values. Initial uncalibrated measurements ranged from 52.43 to 59.58 μg/m3. After calibration, LR models achieved MAE improvements from 22.63 to 71.36 μg/m3, NMSE from 0.16 to 2.69 μg/m3, and bias from 1.74 % to 30.42 %. MLR models showed MAE enhancements from 31.10 to 67.39 μg/m3, NMSE from 0.25 to 2.58 μg/m3, and bias from 18.22 % to 42.08 %. However, the correlation (R2) with the reference monitor is poor and sensitive to slight deviations indicating independence of sensor performance of correlation values.

Transportation stress: Impact on behaviour and welfare in meat-type chickens under indian scenario

In order to find standard transport time and its effect on the welfare, 480 marketable commercial broiler chickens (CARIBRO VISHAL; avg. 2.0 kg body weight) were transported for 2, 4, 8h and without transport in crates in three replicates in a completely randomized design. Transport affected welfare as well as behaviour of broiler chickens. Transport stretch impacted the gait score and tonic immobility with maximum aggravation with extended duration. Runaway results shown that 8h group exhibited more run-away time (279.20sec). Number of birds affected by physical injuries increases with the duration. Bodyweight change was significant among transported groups, especially 8h travelled group exhibited more (−8.21%) body weight loss. It is concluded that a transport period of more than 4h in Indian conditions is not recommended as its causing a significant level of stress in the birds leading to stress, production loss and hampering welfare of broilers.

Investigation of Degradation in 20-Year-Field-Exposed PV Modules From India by Cross-Characterization Using Electroluminescence Imaging and Thermography

The reliability of photovoltaic (PV) modules is essential for ensuring a smooth operation over the anticipated timespan while operating outside. Examining the degradation in field-exposed photovoltaic (FEPV) modules will help to identify the possible degradation modes that can affect PV module performance and functioning. In this paper, to identify the major modes of degradation in Indian subtropical climate conditions, 20-year-old FEPV modules have been investigated by cross-characterization using dark lock-in thermography (DLIT) and electroluminescence (EL) imaging. Cross-characterization using EL and DLIT images has been helpful in investigation of various modes of degradations in FEPV modules in the presence of multiple degradations. Encapsulant and busbar ribbon interface degradations have been identified as the two main modes of degradation observed in Indian sub-tropical climate conditions. Minor degradations include finger interruptions and cell cracks. A major effect of degradation has been observed on the fill factor and short circuit current, which have decreased by up to 30% and 40%, respectively. The results presented in this paper can be used to understand degradation occurring in a sub-tropical climate and for the non-destructive analysis of degradations in the FEPV modules.

Unraveling the dynamics of wheat leaf blight complex: isolation, characterization, and insights into pathogen population under Indian conditions.

Wheat, a staple food crop for 35% of the global population, faces a threat from Helminthosporium leaf blight (HLB), a complex of spot blotch (Bipolaris sorokiniana) and tan spot (Pyrenophora-tritici-repentis) diseases under warm and humid conditions. However, in Indian conditions, the knowledge of existing pathogen populations associated with the HLB complex is limited and largely dominated by only B. sorokiniana (spot blotch). To address this, diseased samples were collected from all six wheat growing zones during 2020-2022. The pathogenic species were identified through in-depth morphological characterization, supplemented with ITS-rDNA and GAPDH sequence analysis, a diagnostic SCAR marker, and pathogenicity studies on two wheat varieties: Sonalika and HD2733. The 32 isolates collected from 10 different states consist of B. spicifera (12.5% of all isolates), Exserohilum rostratum (9.3%), Bipolaris oryzae (3.1%), and B. sorokiniana (75%). B. sorokiniana exhibited the highest disease severity on both varieties. Other lesser-known pathogenic species also produced comparable disease severity as B. sorokiniana isolates and, therefore are economically important. Unraveling pathogen composition and biology aids in disease control and resistance breeding. Our study highlights economically impactful and lesser-known pathogenic species causing wheat leaf blight/spot blotch in India, guiding both current management and future resistance breeding strategies in plant pathology.

Designing and Evaluating the Performance of Full-scale Bioretention Cells in Indian Conditions

Designing and Evaluating the Performance of Full-scale Bioretention Cells in Indian Conditions

Object Detection for Self-Driving Car in Complex Traffic Scenarios

The application of convolutional neural networks (CNNs) in particular has greatly enhanced the object detection capabilities of self-driving cars, because of recent advancements in artificial intelligence (AI). However, striking a balance in vehicular settings between high precision and fast processing continues to be a persistent challenge. Developing nations such as India, possessing the second-largest global population, introduce unique intricacies to road scenarios. Numerous challenges arise on Indian roads, such as unique vehicle kinds and a variety of traffic patterns, such as auto-rickshaws, which are only seen in India. This study presents the outcomes of evaluating the YOLOv8 models, which have demonstrated superior performance in Indian traffic conditions when compared to other existing YOLO models. The examination utilized the dataset, compiled from data collected in the cities of Bangalore and Hyderabad, as well as their surrounding areas. The investigation's findings demonstrate how well the YOLOv8 models work to address the unique problems that Indian road conditions present. This study advances the development of autonomous vehicles designed for intricate traffic situations such as those found on Indian Roads.

An embedded system and IoT-based approach to determine milk quality at milk collection centre - pertaining to Indian conditions

An embedded system and IoT-based approach to determine milk quality at milk collection centre - pertaining to Indian conditions

Optimizing durability of the thin white topping applying Taguchi method using desirability function

White topping is a relatively new rehabilitation technology for giving strength to Asphalt pavement. Time to time resurfacing is necessary for bituminous pavement in hot climate region of India where heavy vehicles, operating under frequent start/stop conditions. So, we can apply white topping where recurring problem arises due to rutting of bituminous pavement. In India, endeavors to develop both traditional and ultra-thin white toppings as well as thin white toppings were built on an experimental basis, but their outcomes have not been specifically tracked. The performance and existence of pavement is affected by a range of things such as the load imposed by means of the site visitors plying on it, the weather, indigenous materials used and renovation standards. To examine their overall performance below Indian site visitors and climatic conditions road roughness test, compressive power by way of taking concrete cores and visible inspection survey has been executed.Moreover, the necessity for the new sorts of concrete with higher durability and higher overall performance for precise purposes, as compared to the available sorts, is sensed greater than ever. The concrete durability, laid low with one kind of variables consisting of compressive strength, resistance and permeability, has already attracted the attention of many researchers. In this research the effects of adding white topping concrete, changes in the humidity and temperature of the rehabilitated surrounding atmosphere are investigated to observe whether they will cause any growth in compressive strength and resistance of concrete and/or any decay in its permeability. For this, the Taguchi method is carried out as a method of design of experiment to get the most excellent level for every variable, accompanied by applying the regression approach to model the variables. finally, the final most desirable degrees for the sturdiness are offered primarily based on the desirability function.

Development of New Hibiscus rosa-sinensis L. Cultivar Acharya Jagadish Chandra Bose D. Chakraborty, J. Swamy & D. Singh in West Bengal, India

Hibiscus has a unique and wide range of colors ranging from brown, purple, white, pink, red, orange, yellow, etc. Many cultivars introduced from various countries were adapted to Indian conditions, of which suitable elegant cultivars Hibiscus rosa- sinensis L. ‘Valentine's Day’ (female pod parent) and Hibiscus rosa- sinensis L. ‘Moorea Memory of July’ (male pollen parent) were selected and hybridized. Hybrid seeds from the female parent were collected, germinated, and grown to the flowering stage. The developed cultivar was named after a great Indian scientist Acharya Jagadish Chandra Bose (H. rosa-sinensis cv. Acharya Jagadish Chandra Bose). A detailed development of the new cultivar with photographs is discussed.

Performance of Strawberry Cultivars under different Growing Environments in Nilgiris

Strawberry, an important berry fruit crop with high value and nutritional properties is picking up in the South Indian conditions, especially in Tamil Nadu under temperate region of Nilgiris district. Since the fruit is directly consumed by the children and all group of categories, the choice of varieties and its performance in terms of fruit yield and quality particularly sugar and acidity level will decide the marketability and preference. The field evaluation of strawberry varieties collected from different places and suitability will help the farmers to cultivate and get benefit and profitability out of the crop. A collection of nine strawberry varieties was done and assessed for the performance under greenhouse growing environment, in Nilgiris condition with randomized block design having three replications during the year 2018 to 2020 in Horticultural Research Station, TNAU, Ooty, Nilgiris.The variety Rania recorded better performance for plant height (33.81 cm), plant spread(E-W) [45.38 cm], (N-S) [43.96 cm] during 120 days after planting. Flavia recorded more number of leaves (24.80). Rania recorded a fruit length (4.05 cm), fruit width (11.29 cm), fruit weight (27.62 g). The variety Capri recorded more number of fruits per plant (68.86) which is on par with Flavia (68.80). The fruit quality parameters Total Soluble Solids (TSS) is high with 12.43o brix in Nabila and acidity (0.98 %) in Flaminia. The highest yield per plant (1190.20 g) was recorded in Flavia and with lowest yield in Capri (563.46 g). The variety Flavia recorded maximum in fruit parameters like fruit length, fruit width, fruit weight and highest yield whereas fruit quality parameters of TSS and acidity is highest in Nabila and Flaminia respectively.