Indian Institute of Oil Palm Research

This study presents a comprehensive characterization of nine cold-pressed vegetable oils derived from fruits, nuts, and seeds commonly retailed in India, focusing on their nutritional quality, oxidative stability, and potential health benefits. Our study uniquely combines detailed profiling of fatty acid composition with the assessment of key bioactive components such as carotenoids, phenolics, and flavonoids an approach not often addressed collectively in previous literature. Coconut, almond, and safflower oils contained the highest proportions of saturated (87%), monounsaturated (66%), and polyunsaturated (74%) fatty acids, respectively. Minimal quantities of coconut and safflower oils were sufficient to meet daily intake recommendations for saturated (8 g) and unsaturated (10.4 g) fatty acids, respectively. Due to its high saturated fat, coconut oil exhibited the highest atherogenicity (10.7) and thrombogenicity (5.2) indices. Palm and niger oils demonstrated higher oxidation values, correlating with their oxidative state. Palm oil showed exceptional carotene content (812 mg/kg), while sesame and palm oils exhibited the highest phenolic (30 and 23 mg/100 g) and flavonoid (1.27 and 1.57 mg/g) contents. Using robust techniques GC-FID, spectrophotometric assays, and principal component analysis, we provide integrative insights into the health implications and quality parameters of these oils. This multifactorial assessment bridges critical knowledge gaps and offers evidence-based recommendations aligned with global dietary standards, serving as a valuable resource for health-conscious consumers and the edible oil industry.

Abstract This study integrates XGBoost modeling with Partial Dependence Plots to optimize carbon sequestration. The experiment was conducted using a split-split plot design replicated thrice with the main plot compressing tillage practices viz. , minimum tillage (M 1 ) and conventional tillage (M 2 ), subplot consists of row ratios viz. pigeonpea + maize (1:2 ratio) (R 1 ), pigeonpea + maize (1:3 ratio) (R 2 ), and sole pigeonpea (R 3 ) and sole maize (R 4 ), sub-subplot consists residue management practices viz. on farm produced biochar application (S 1 ), on farm produced residue application (S 2 ), and control with no biochar or residue application (S 3 ). Machine learning models of XGBoost accurately predicted CSQ while Artificial Neural Network performed best for SP and CF, confirming nonlinear relationships. PDPs showed available nitrogen increased productivity from 3.0 to 3.4 Mg ha⁻¹ y⁻¹ (150–300 kg ha⁻¹), while SOC reduced it from 3.8 to 3.2 Mg ha⁻¹ y⁻¹ (0.425–0.525%). Sensitivity analysis identified SOC, moisture, and enzyme activities as key drivers, with SOC enhancing sequestration by ~ 1.5 Mg C ha⁻¹ and improving footprint by ~ 1.2 Mg CO₂-Ce ha⁻¹. These insights enable targeted, efficient soil management for productivity and climate benefits. Machine learning-based Partial Dependence Plot (PDP) and sensitivity analysis (SA) revealed SOC, BD, and microbial parameters as key drivers of these outcomes.

PurposeBasal stem rot (BSR), with Ganoderma spp. as the principal causative agent, is an important oil palm disease, leading to significant stand loss and reduced yield potential. The use of antagonistic fungi, particularly Trichoderma spp., offers a sustainable approach to disease suppression through hyperparasitism, antibiosis, and rhizosphere competence. However, strain-dependent variability in antagonistic potential necessitates the selection of the most efficacious isolates for integrated BSR management. Here we show that T. afroharzianum exhibits superior antagonism against Ganoderma spp., in dual culture, inverted plate assay as well as cellfiltrate assays.MethodsFrom 50 Trichoderma isolates screened, 12 highly mycoparasitic strains (>80% Ganoderma suppression) were selected. To enhance applicability under field conditions, the selected strains were further evaluated against co-occurring soil-borne pathogens commonly associated with oil palm decline.ResultsT. afroharzianum exhibited hydrolytic enzyme secretion (chitinase, cellulase, and pectinase), solubilized key macronutrients, and suppressed multiple soil-borne phytopathogens including Rhizoctonia solani, R. bataticola, Fusarium solani, Lasiodeplodia theobromae Colletotrichum gleosporoides and Curvularia lunata. A tailored Trichoderma consortium achieved 61.94% disease suppression, reduced foliar and bole severity by 48.59 and 20.22%, respectively, and increased plant height (47.59 ± 2.52 cm) and shoot fresh weight (15.83 ± 0.80 g).Implications/conclusionThese findings establish T. afroharzianum as a promising biocontrol agent for BSR suppression through multiple mechanisms, including competitive exclusion and pathogen inhibition. The results support its potential for field deployment as part of an integrated, climate-resilient disease management strategy in oil palm cultivation.

Bacterial blight (BB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is a major constraint to rice production in humid tropical regions. In the search for new genetic sources of resistance, we focused on OsRPM1 (LOC Os12g30070.1), a rice gene encoding a coiled-coil nucleotide-binding leucine-rich repeat (CC-NB-LRR) protein, structurally similar to well-characterized resistance (R) proteins in Arabidopsis and other plant species. Although its role in rice immunity was previously uncharacterized, transcriptomic profiling revealed that OsRPM1 is significantly upregulated in a type III secretion system (T3SS)-dependent manner during infection with the virulent Xoo race 4, suggesting a pathogen-responsive defence function. To evaluate this, we employed virus-induced gene silencing (VIGS) to transiently suppress its expression in rice. Silencing OsRPM1 increased susceptibility to Xoo, resulting in more severe disease symptoms, reduced reactive oxygen species (ROS) accumulation, and impaired callose deposition; key defence responses linked to effective resistance. These findings demonstrate that OsRPM1 acts as a positive regulator of rice defence and support its potential as a candidate for broad-spectrum, durable resistance breeding.

Okra [Abelmoschus esculentus (L.) Moench] is an often cross-pollinated crop with up to 19–42% of cross pollination assisted by insects and planned pollination may improve the economic fruit yield and biological parameters. The present study was carried out during rainy (kharif) seasons of 2021 and 2022 at Research Farm of ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan, Hawalbagh, Almora, Uttarakhand to assess the pollinator diversity and possible results (both biological and economical) of planned bee pollination. The study on floral visitors of okra recorded 28 insect spp. belonging to four insect orders, among which five spp., viz. Apis cerana indica (Fabricius) 1798, Apis mellifera (Linnaeus) 1758, Bombus haemorrhoidalis (Smith) 1852, Lithurgus atratus (Smith) 1853 and Xylocopa latipes (Drury) 1773 were predominant. The foraging activity and pollination behaviour showed that two non-Apis bee species (X. latipes and B. haemorrhoidalis) were swift flyers and visited more numbers of flowers per unit time. It was noticed that, peak period of pollinator’s visitation was between 9.00–11.00 h accounting to 113.76±7.65 insects/m2/10 min, during which stigma receptivity and pollen germination were at its peak. Assessment of yield related parameters of insect pollinated flowers showed superior quality fruits with better capsule length (17.4–20.9 cm), capsule girth (6.56–7.84 cm), seeds/capsule (51.4–60.6), test weight of 100-seeds (7.05–8.38 g) and even the seed yield (1.86–3.04 tonnes/hectare) than closed control and hand pollination (emasculated and cross pollinated). In conclusion, ecological engineering of okra fields enhances the pollination rate and ultimately the yield and seed quality.

This study presents a strategic planning model to optimize economic returns and minimize the environmental impact of Palm Oil Mill Effluent (POME) treatment systems. The model aims to maximize profits while reducing CO2e emissions by evaluating three treatment options: Anaerobic Digester Tank System (ADT), Covered Lagoon (CL) with biogas capture, and Open Pond System (OP). Constraints considered include fresh fruit bunch (FFB) production, POME generation, treatment system capacity, electricity generation from the existing boiler and additional biogas engine, electricity demand, capital costs, and operating costs. A mixed-integer linear programming model (MILP) is formulated and optimized using GAMS 40.1.0 software, focusing on selecting the treatment system that balances profitability with minimal CO2e emissions. Applied to a case study of two mills in Papua New Guinea, the model identified the ADT system as the optimal treatment system. In the Economic Mode, the model prioritizes profit maximization, achieving a total annual profit of USD 9,769,439, with electricity sales amounting to USD 12,399,439 per year. The developed model can assist governmental agencies and private sectors in developing strategic pome treatment systems that enhance profitability while minimizing environmental impact.

For genetic mapping research in a crop like oil palm, polymorphic SSR (simple sequence repeat) markers are crucial.Thirty four SSR loci were used for screening in the current work to test a total of 10 hybrids at molecular level.There were between two and four alleles in these, with 22 of them being polymorphic and 12 being monomorphic.The primer SMG00026 had the greatest Polymorphism Information Content (PIC) value (0.60), while mEgCIR0408 had the lowest (0.14), with a mean PIC value of 0.22.Genetic variation scores varied between 0.15 (mEgCIR0408) and 0.66 (SMG00026), with an average of 0.286.Seven highly polymorphic markers, SMG00026, mEgCIR0074, mEgCIR0353, mEgCIR3350, mEgCIR0555, mEgCIR3886, and mEgCIR0905, were identified based on PIC and other genetic criteria.The oil palm crop development programme can effectively utilise the found polymorphic SSR loci in genetic diversity investigations and mapping.The 10 hybrids were divided into two primary clusters by a total of 22 polymorphic SSRs, and the observed clustering was based on geographic origin.These polymorphic primers can be used effectively because they make it easier to choose promising varieties at nursery stage, which helps both researchers and farmers to modernise the plant breeding programme for oil palm.