Background: Acacia nilotica var. cupressiformis is an evergreen multipurpose leguminous tree species which is suitable to agroforestry purposes and mainly distributed in Western parts of Rajasthan in India particularly Pali and its adjoining areas. The species has many advantages, however the natural germination in wild is very limited due to its hard seed coat dormancy. Methods: The experiment was conducted to study the effect of presowing treatment on seed coat of A. nilotica var. cupressiformis seeds with ten treatments in Completely Randomized Block Design at ICAR-Central Arid Zone Research Institute, Regional Research Station, Pali Marwar. The treatments were replicated thrice. Result: Among the treatments, maximum germination and higher values was obtained in sand paper scarification with water soaking for 12hrs (T2) followed by mechanical scarification with sand paper (T1), acid scarification (50% for 20 min) (T7) and acid scarification (98% for 10 min) (T5). Further, the present study aims to initiate the research areas for conservation and utilization of A. nilotica var. cupressiformis in Western parts of Rajasthan and other parts of India.

The integration of trees into diverse land-use systems holds potential for India to meet nationally determined contribution (NDC) targets under the Paris Climate Agreement. With a target of sequestering 2.5–3 billion tons of CO2 equivalent by 2030, the study focused on the widespread and economically viable eucalyptus-based agroforestry, practiced widely in various planting geometries tailored to meet industrial end-use requirements. In this context, a detailed study was conducted to quantify the influence of five planting geometries [3 m × 3 m, 6 × 1.5 m, 17 × 1 × 1 m (paired row) and two boundary plantations (east–west and north–south directions) at 2 m away from tree to tree] of eucalyptus on intercrops [dhaincha (Sesbania aculeata)—barley (Hordeum vulgare L.) rotation] biomass, soil properties, and carbon stock of the system during 2009–2016. Results revealed that biomass accumulation of different tree components was 62.50%–74.09% in stem; 6.59%–9.14% in branch; 3.18%–5.73% in leaves; 12.20%–20.44% in stump roots; and 1.71%–3.48% in fine roots across the planting geometries. The mean carbon content of the stem, branch, leaves, and roots was 49.00, 47.00, 43.00, and 49.00%, respectively. Over the 8-year period, geometry of 3 × 3 m performed better in terms of total biomass production (344.60 Mg ha− 1 by tree biomass and 62.53 Mg ha−1 by intercrops). The independent parameter, DBH2H (DBH: diameter at breast height and H: tree height), was found to be a very good predictor of dry weight, followed by DBH alone. Among various functions (linear, allometric, logistic, Gompertz, Chapman, and exponential), the best-fit equation was allometric, i.e., B = 300.96 × DBH2H0.93 (adjusted R2 = 0.96) for eucalyptus based on universal model adequacy and validation criteria. The carbon sequestration rate was maximum (20.79 Mg C ha−1 year−1) in 3 × 3 m followed by 17 × 1 × 1 m. The total carbon stock of eucalyptus-based system (tree + crop + soil) varied significantly under different planting geometries and sole crop rotation (dhaincha–barley). The higher carbon stock (237.27 Mg ha−1) was obtained from 3 × 3 m spacing and further partitioning carbon stock in trees—166.29 Mg ha−1, crops—25.01 Mg ha−1 and soil—45.97 Mg ha−1. The paired row spacing (17 × 1 × 1 m) yielded higher crop yield and net returns (Rs. 600,475 ha−1), underscoring wide spacing’s role in system productivity and sustainability. Tree-based systems were valuable components of agriculture, advocating for their widespread adoption to reduce CO2 emissions and generate income through carbon credits. These findings will provide crucial insights into sustainable land-use practices and advance India’s commitment toward adaptation of climate change mitigation strategies.

The development of multimedia technology has increased the challenge in protecting the information. This paper proposes an effective method for data hiding in videos based on the Pixel Sequence (PS), weight interpolation to protect the secret data from intruders. Initially, the noise is removed from the video with the help of median filter and Moving Objects (MO) inside the frames having different backgrounds are accurately detected using Fast Region-based Convolution Neural Network (FR-CNN). Next, the MO and Non Moving Object (NMO) pixel from each frame are mapped with the adjacent frames to determine the weights applying PS. Then, the cover video is up-scaled with interpolated pixels based on weights of MO and NMO. Finally, the secret data are hidden inside the both interpolated and non-interpolated pixels elevate Embedding Capacity (EC). In interpolated pixels, both Most Significant Bit (MSB) and Least Significant Bit (LSB) of each frames based on their weight are utilized to hide data. Whereas, in non-interpolated pixels, Quorum Function (QF) is used to embed data. Two different data embedding techniques are adopted in each frame to enhance the security. The performance evaluation of the proposed method out-performs the existing methods in terms of precision and recall. Experimental results also show that the stego-video quality is uncompromised and is resistive to security attacks.

Global climate change conventions have increasingly highlighted the importance of quantifying carbon stored in trees outside of forested areas, as they play a crucial role in carbon sequestration. In India’s arid agroforestry landscapes, Prosopis cineraria (L.) Druce., Tecomella undulata (Sm.) Seem., and Hardwickia binata Roxb. are three key tree species. This study aims to quantify biomass and carbon partitioning across different tree components to estimate the total carbon sequestered within these systems. For H. binata, biomass and carbon were calculated using existing allometric equations for specific components such as bole, branches, leaves, and roots. However, for P. cineraria and T. undulata, where available allometric equations only provided total biomass, destructive sampling of one tree per diameter class was conducted to determine biomass partitioning (

The sandalwood (Santalum album) tree holds significant commercial and cultural value globally, particularly in India. Among the 17 species within the Santalum genus, Santalum album stands out due to its high oil content and the presence of favorable compounds such as α-and β-santalols. The wood of this species is highly prized for carving and its aromatic heartwood oil is widely used in attar, perfumes, cosmetics, soaps, toiletries, medicinal products, flavored tobacco, and areca nut products. Despite its historical significance, sandalwood is vulnerable and endangered due to legal policies, illegal harvesting, grazing, lopping, natural fires, exotic plantations, sandalwood spike disease, and climate change. The combination of increased demand and declining supply has led to a surge in sandalwood prices, attracting attention from farmers, policymakers, and the industry sector, prompting interest in commercial cultivation. This has sparked global involvement from various countries, government agencies, industries, research disciplines, industry representatives, and sandalwood growers. This article offers a thorough review of sandalwood utilization, legal issues, and management challenges. It draws on literature and expert insights to assess current practices and research findings. The study identifies critical factors such as the number of hosts, host type, and planting geometry that influence successful establishment and production in farmers' fields. It also highlights obstacles and opportunities for the future sustainability of sandalwood, aiming to guide effective management and policy strategies for this valuable resource. The government of India has initiated policy-level changes regarding the ownership, cultivation, and harvesting of sandalwood trees, encouraging many farmers to cultivate on private land even beyond its natural boundaries. However, the complexity of sandalwood cultivation requires further scientific introspection to ensure successful establishment and sustainable management in the future.

Litter decomposition is an important process that maintains soil fertility and enriches soil organic matter in agroforestry. They are highly influenced by tree density, age, timing, the quantity of litterfall, soil organisms, the chemical nature of the litter, and environmental conditions. An experiment was conducted in a multifunctional agroforestry model established in 2018 at Forest College Research Institute, Mettupalayam, India. Based on litter fall, among 25 tree species, seventeen species were chosen to study litter decomposition and the relationship between decay rates, initial litter chemistry, and soil properties. A total of 153 litter bags each of 20 g samples were placed in soil and retrieved at 60, 120, 180, and 360 days to observe litter mass remaining and further analysed in laboratory for its properties. The results of decay rates revealed that the litter of Neolamarckia cadamba (3.03), Tectona grandis (2.85), Annona muricata (2.81), Moringa oleifera twigs (1.10) decomposed fast whereas Calophyllum inophyllum (0.86), Pterocarpus santalinus (1.02) and Melia dubia twigs (1.10) exhibited the lowest rate of decomposition. Calophyllum inophyllum takes 3.50 years while Neolamarckia cadamba takes only 0.99 years for decomposition of 95

The mumps virus causes a very infectious sickness. The enlargement of the parotid salivary glands can be quite uncomfortable. Mumps treatment centers on symptom management. The illness must take its natural course. While most people experience very moderate symptoms, some develop severe consequences. The mumps virus can be avoided with the use of the MMR vaccination. In this research, we employ a convolutional neural network (CNN) technique to better automate mumps detection. In order to automate mumps detection, the authors of this research suggest a convolutional neural network (CNN) trained using XGBoost Classifier data. Incorporating machine learning (ML) technique comparisons. A mumps dataset consisting of 50×50 RGB picture patches served as the basis for all the models. Quantitative findings from each approach were put through validation testing based on their respective effectiveness metrics. To improve the efficiency of the model, the Mayfly Optimization Algorithm is implemented. Results show that the suggested method is effective, with 97% accuracy, suggesting that it might help decrease diagnostic errors caused by human error. And the suggested system we've developed is so precise that it outperforms the CNN model, which only gets around 92% of the time. Consequently, the suggested method is 5% more accurate than the CNN Model.

Henna (Lawsonia inermis L.) is a commercial and export-oriented important perennial shrub used in the ornamentation of palm, feet, dyeing of hair, etc. Developing high-yielding varieties and elite plant materials are the best method to increase the productivity and quality in henna. An experiment was conducted at research farm of ICAR-Central Arid Zone Research Institute, Regional Research Station, Pali-Marwar, Rajasthan during 2018–22 in Randomized block design to assess variability among morphometric traits and genetic parameters for dry leaf yield and attributing characters in Henna. The results indicated that among 19 germplasms maximum dry leaf yield and minimum number of inflorescence was recorded in CZ-RSPH-8 followed by CZ-RSPH-15. The accession CZ-RSPH-9 (2.33%) exhibited the highest lawsone content (%) followed by CZ-RSPH-8 and CZ-RSPH-15. The estimates of phenotypic co-efficient variation (PCV) were higher than the respective genotypic co-efficient variation (GCV). The number of inflorescences registered high heritability with high genetic advance. Path analysis exhibited the direct effect of the number of inflorescence with dry leaf yield. Cluster analysis revealed two major clusters classified into 6 and 13 germplasm which depicts the diverse degree of relatedness among different accessions.

A study was carried out to study the pollination system in henna at CAZRI, RRS, Pali marwar in hot semi-arid region of India.Two types of pollination systems viz., natural open pollination and pollination in controlled condition were studied.Total of 10 inflorescences borne on ten different 20-year old henna plants were selected and covered with muslin cloth bags and butter paper for controlled pollination.Simultaneously, 10 inflorescences of same plants were kept uncovered for open pollination.Out of three modes of pollination studied in henna, maximum fruit set (60.84%) was observed in natural open pollinated condition while minimum fruit set (11.78%) recorded in controlled pollination covered with butter paper followed by controlled pollination covered with muslin cloth (10.10%).The highest fruit flower ratio also registered in natural open pollinated condition (0.608) whereas lowest were recorded in controlled pollination covered with muslin cloth (0.117) followed by controlled pollination covered with butter paper (0.101).Besides, the common flower visitors also observed which may favour the cross pollination in henna flowers.This study confirms that henna is cross pollinated species.

A field experiment was conducted at the research farm of ICAR-CAZRI, Regional Research Station, Pali, Rajasthan during winter (rabi) season 2017–18 and 2018–19 to study the effect of organic culture on growth, yield attributes, yield and economics of wheat (Triticum aestivum L.) under low saline water irrigated condition. The experiment was laid out in randomized block design consisting of 8 treatments of organic culture with 3 replications. The results revealed that application of organic culture through seed treatments and foliar spray (10%) at different growth stages significantly influenced the growth and yield attributes of wheat in pooled data of 2 years. Application of organic culture (T4) exhibited significantly the highest grain yield (4391 kg/ha) followed by T3 (4074 kg/ha) and T5 treatment (3912 kg/ha) over the control (3044 kg/ha) in both the years (pooled basis). Significantly the higher net return and Benefit cost (B:C) ratio of `75446/ha and 2.24, respectively was recorded under the T4 treatment while the lowest net return of `46178/ha and benefit cost ratio 1.40 was obtained under T1 (control) treatment.Thus, application of organic culture through seed treatment and foliar spray (10%) at 30 and 60 days after sowing (DAS) of wheat was found best for realizing higher growth, yield and benefits.

Lawsonia inermis (henna) is a perennial shrub cultivated as a ratoon crop (annual pruning of hoots) in the hot semi-arid regions of India for its dye-containing leaves. Considering its perennial nature, we hypothesized that henna plantation may sequester carbon in the biomass as well as soil; further, severe shoot pruning may affect the distribution of carbon in the above and below-ground biomass and different soil layers. Therefore, we quantified biomass and soil carbon stock in an age-sequence of 2-, 13, 21- and 56-year old henna plantation to study dynamics and pattern of carbon accumulation. Biomass and soil carbon stock significantly increased with the age of the plantation. While, shoot pruning and plant populations significantly impacted the distribution of carbon in the aboveground and belowground biomass as well as in the soil. Within the plant system, belowground biomass stored more carbon as compared to aboveground biomass. While within the soil, carbon stock was higher in the lower soil layer (15-45cm) as compared to the surface soil layer (0-15 cm). The 2-, 13-, 21- and 56-year old plantation stored about 1.60±0.44, 10.13±1.28, 10.14±1.02 and 11.42±2.50 Mg biomass-C ha-1 respectively with a higher rate of sequestration during early stages of the plantation.

Agroforestry is identified as a potential carbon sequestration strategy, involved in carbon capture and storage in woody perennials. However, the use of default values of wood-specific gravity (WSG) and carbon content (CC) in biomass estimation may lead to over or underestimations. Therefore, the present study attempted to assess the difference in WSG and CC among 25 different species of multifunctional agroforestry (MFA) established at Forest College and Research Institute, Coimbatore, Tamil Nadu, India. Wood core samples were collected using the wood-cutter and incremental borer. Determination of WSG and CC was done by water displacement method and combusting in a muffle furnace. Analysis of variance revealed significant differences for both WSG and CC (P < 0.001). WSG ranges from 0.26 ± 0.01 (Jatropha curcas) to 0.81 ± 0.04 (Santalum album). Out of 25 trees, wood carbon fractions of > 40% were noticed in 21 tree species. Among 25 trees, ten species fall under light wood (WSG < 0.5), eight species in moderately heavy wood (0.5–0.7), and seven species fall under the category of heavy wood (> 0.7). Therefore, documenting WSG and CC will provide better insight in biomass estimations.

Poplar is popular among farmers and planted widely in the form of block and boundary systems. The preferences of farmers are shifting much more towards bund plantations due to their smaller yield reductions and can take up kharif and rabi crops till rotation. As for boundary plantations, farmers tend to grow trees in any direction without concern for yield reduction or profitability. Against this background, an experiment was designed by planting poplar at 2 m intervals in East–West (E–W) and North–South (N–S) directions during 2008 to determine the production potential and economic viability of boundary plantations and their effect on sorghum (Sorghum bicolor) and wheat (Triticum aestivum) crop rotations till harvesting of the trees. The experiment comprised three variables: stand age (years); four aspects (northern and southern E–W rows, eastern and western N–S rows; these four aspects are considered by dividing the tree lines); and six distances from tree the lines (0–3, 3–6, 6–9, 9–12, 12–15, 15–18 m and a control). A split-split plot design with three replicates was used. A significant reduction of fodder biomass of sorghum and wheat yield was observed up to 9 m distant from the tree line: the reduction was 10 to 60% for the kharif season and 7.2 to 29.5% for rabi crops from the second year to eight years after planting, respectively. Interestingly, the poplar boundary plantation had a favorable microclimatic effect from 9 to 15 m distance from the tree line, which increased crop yields compared with the control. The total dry wood production of poplar in the E–W direction (166.99 mg ha−1) was almost two times more than production for the N–S direction (82.62 mg ha−1) at 8 years of rotation. The economic analysis of this study concluded that an E–W boundary plantation of poplars exhibited the maximum net returns of INR 549,367 ha−1, a net present value of INR 222,951 ha−1, a BC ratio of 1:1.65, an IRR of 85% and an LEV of INR 1,220,337 ha−1. Therefore, it is concluded that the intercropping of a sorghum-wheat crop rotation in E–W boundary plantations was more beneficial for enhancing farm income over traditional agriculture in north India.

Agroforestry is widely recognized for its role in climate change mitigation and adaptation.However, carbon sequestration and a marketable carbon value of smallholder agroforestry systems in India are poorly documented.Therefore, the present study was carried out to quantify carbon stock in a circular-shaped multifunctional agroforestry (MFA) divided into four equal quadrats.It comprises 24 different tree species and 8 intercrops, mainly established to provide daily income to small and marginal farmers.A nondestructive method was used to assess biomass carbon stock.Soil core samples collected from 0 to 60 cm depth were analysed to quantify soil organic carbon (SOC) stock.Results revealed significantly higher biomass and carbon stock in the following order: Neolamarckia cadamba > Melia dubia > Lagerstroemia parviflora > Dalbergia latifolia > Tectona grandis.Duncan's multiple range test revealed significant differences in the multi-utility circles (P < 0.001).The total change in SOC stock was 11.55 Mg quadrat -1 , but the difference was insignificant in different soil depths.The results indicated that the total carbon sequestration and CO 2e from vegetation were 2.23 and 9.23 tonnes respectively.Similarly, CO 2e from the soil were 42.37 Mg quadrat -1 respectively; the highest contributions were from quadrat II and quadrat IV of MFA.By taking into account profitability and incentives to smallholder farmers, the total marketable carbon revenue of MFA was calculated as US$ 206.40.

This study deals with the oxygen production potential of India taking baseline data from ISFR 2019.The Indian forests have an oxygen production potential of 7896.14 million tonnes (mt) and the annual potential was 28.04 mt yr -1 for 2019.Considering oxygen production potential of the top 10 tree species from forests and those outside forests, Shorea robusta (Sal) and Mangifera indica (Mango) ranked first, i.e. 657.87 and 214.39 mt respectively.The fast-growing agroforestry tree species exhibit a net oxygen production rate in the range of 1.03-34.15tonnes ha -1 yr -1 .Bamboo being a fast-growing and higher biomass-producing species showed oxygen production of 27.38 mt yr -1 .Overall this provides huge scope for establishing oxyparks in India.