Agricultural Research Research Articles

Phenotypic Characterization of Citron Watermelon (Citrullus lanatus var. citroides) Genotypes for Bioenergy Production

Citron watermelon (Citrullus lanatus var. citroides) is an important climate smart crop, characterized by high oil content in the seeds and it is a popular fruit in southern Africa. To determine best performing genotypes eight phenotypic traits were assessed to identify cultivars with potential for biodiesel production. A field experiment was conducted at Sebele Agricultural Research Station, in Southern Botswana, during 2019 to 2020 cropping season. Four (4) melon genotypes were planted in a Randomized Complete Block Design replicated three times and eight (8) characters were assessed. Except seed oil content (26.6%) there was significant (P < 0.05) difference among all the traits, an indication of higher genetic diversity in the selected citron watermelon. SC1-Sesoswane, exhibited highest seed yield (1540 kg/ha) and oil yield (435.03 kg/ha) while MMB-280-Lerotse recorded lowest seed yield and oil yield of 548.1 kg/ha and 144 kg/ha respectively. There was a significant correlation of (0.9) between oil yield (kg/ha), number of fruits produced, and seed yield (kg/ha), an indication that increasing the seed yield will positively increase the amount of oil produced. This study revealed the potential bioenergy production of the four cultivars. However, SC1-Sesoswane appears a more promising alternative cultivar for feedstock for biodiesel production.

Crop Yield Prediction using CNN

Deep learning is a branch of Machine Learning which is completely based on artificial neural networks, as neural networks are going to mimic the human brain so deep learning is also a kind of mimic of the human brain. Farming is the main occupation of India. Crop yield has a direct impact on nation and international economies annually and the yield predicted plays a significant part in the food management and agriculture sector. The task is to build a prediction model for crop production . A prerequisite of intelligent systems has brought artificial neural networks to become a new technology which provides assorted solutions for complex problems in agriculture research. Performance of the agriculture sector mainly hinges on natural forces such as spatio-temporal distribution of rainfall, temperature, climate etc, with the result any deviation of monsoon from the normal pattern brings about numerous fluctuations in area and production. Crop yield has a direct impact on nation and international economies annually and the yield predicted plays a significant part in the food management and agriculture sector. The task is to build a prediction model for crop production. The basic principle of ANN architecture, Data Modeling for Prediction involves four stages namely historical data analysis (Descriptive), Data preprocessing, modeling of Data and Performance Estimation. First classify data based on different attributes. Regression analysis using CNN, it observes the relation between an independent (predictor) and dependent (target) variables. Based on relation training the model will predict crop yield production. application of ANN in predicting crop yield by using various crop performance features as input parameter

Linking farmers’ perceptions and management decision toward sustainable agroecological transition: evidence from rural Tunisia

Global food systems face sustainability challenges like undernourishment, inequity, resource degradation, and pollution. Food production and consumption drive environmental change with greenhouse gas emissions, biodiversity loss, and land-system shifts. The climate change crisis has intensified concerns about the ecological impact of these systems. Sustainable food networks, such as community-supported agriculture, are promoting sustainable production and consumption through short supply chains. International bodies like the Food and Agriculture Organization (FAO) and the Consultative Group for International Agricultural Research (CGIAR) are also spearheading initiatives for more equitable and sustainable food systems. In Tunisia, where dryland areas predominate, the ongoing implementation of the Agroecology Initiative provides the context for this study, which explores the drivers and barriers of agroecological transformation in this challenging environment. The research focuses on stakeholder engagement, with a gender perspective to explore farmer perceptions. The study, conducted in the northwest of Tunisia in 2022–2023, involved focus groups, workshops, surveys, and questionnaires with various stakeholders. Findings highlight farmer organizations’ potential in promoting sustainable farming, with clear goals, diversified systems, and collaborations. However, challenges such as input scarcity, water shortage, low income, and marketing must be addressed. Results also indicate that over 90% of farmers who received assistance with agroecological practices reported a change in their ideas and practices. Fifty seven percent of the workshops participants identified the olive oil value chain as having the greatest potential for agroecological transformation, but it faces constraints such as climate, lack of policy incentives, training, funding, and difficulty in adopting technical innovations. Women’s inclusion in agriculture, environmental, social, and economic challenges were also highlighted. Despite these obstacles, key drivers for agroecological transition were identified. These include the compatibility of many agroecological practices with existing farmer capabilities, their cultural and economic benefits, and the positive outcomes for environmental sustainability and health. The study advocates for a socio-technical systems analysis to address the root causes hindering Tunisia’s agroecological transformation. A participatory approach is crucial to understanding priorities and developing a sustainable and resilient food system. Furthermore, the research underscores the importance of considering diverse farmer perspectives and tailoring strategies to support this critical transition effectively.

Screening of mungbean germplasm for resistance against Cercospora leaf spot under natural field conditions

Mung bean is an excellent protein source pulse crop grown throughout the world. Punjab province accounts for 80% area and production of mung bean in Pakistan. Mung bean is cultivated on a large scale for its green manuring ability and grain consumption. Mungbean is prone to economically important fungal, bacterial, and viral diseases. Cercospora leaf spot (CLS) caused by Cercospora canescens is one of the most serious disease concerns in Pakistan. The pulses program at the National Agriculture Research Centre, Islamabad is trying hard to get the resistant germplasm against CLS. Sixty-eight advance lines/approved varieties were evaluated in the augmented design under natural field conditions. Forty-one advance lines/approved varieties were found resistant and twenty-five advance lines/approved varieties were found moderately resistant. Two advanced lines/approved varieties did not perform well and were susceptible to CLS infection. This data indicates that the germplasm at pulses program is excellent in resistance against CLS under natural field conditions in the Arid Zone and can serve as potential future varieties.

Impacts on Various Management Practices on Crops Yield and Soil Biology in Maize-Wheat Cropping System

Aims: Integrated approaches that consider the synergies and trade-offs among tillage, residue, and nitrogen management are essential for optimizing agricultural sustainability to highlight the complex interplay between agronomic, environmental, and biological factors. We intended to evaluate the impact of tillage, residue, and nitrogen management on crop growth and soil biological properties under a maize-wheat cropping system in an inceptisol. Study Design: Split-split plot design. Place and Duration of Study: ICAR-IARI research farm, New Delhi, since 2014. Methodology: We collected soil samples at the anthesis stage of wheat crop and silking stage of maize crop at 0-5, 5-15, and 15-30 cm soil depth. Soil properties, namely soil organic carbon, dehydrogenase, acid, and alkaline phosphatase, soil microbial biomass carbon, soil microbial biomass phosphorus, and glomalin content by using standard procedures. Results: We observed that the soil organic carbon, enzyme activities, microbial biomass carbon and phosphorus, and glomalin content were significantly (P<0.05) higher under no-tillage and residue treatment at 0-5 and 5-15 cm soil depth. Enzyme activity and microbial biomass carbon (MBC) were significantly higher by application of 100 and 150% RDN, respectively, at 0-5 and 5-15 cm soil depth. The effect of nitrogen treatment on biomass yield was significant (P<0.05) and found to be higher at 150% Recommended dose of Nitrogen (RDN). The biomass yield of maize was 15.3% and 44.5%, and wheat was 7.8% and 20.4%, significantly increased by applying 150% RDN over the 100% and 50% RDN respectively. Conclusion: Farmers can successfully adopt NT with 5 t ha-1 crop residue mulch with 150% RDN to attain better soil health and higher biomass yield under the maize-wheat cropping system.

Growth, Yield Attributes and Yield of Barley (Hordeum vulgare L.) under Different Levels of Fertilizer and Vermicompost Grown under Every Furrow and Alternate Furrow Irrigation Methods

A field experiment was conducted during the Rabi season of 2021-22 at the Agronomy Research Farm of CCS Haryana Agricultural University, Hisar in a split-plot design with two vermicompost levels i.e., vermicompost @ 1.5 t ha-1 and vermicompost @ 3.0 t ha-1, two irrigation methods i.e., every furrow irrigation and alternate furrow irrigation method as the main plot treatments and three fertilizer levels at N40P20, N60P30 and N80P40 kg ha-1 as subplot treatments and replicated three times. Among the vermicompost levels, vermicompost at 3.0 t ha-1 recorded significantly higher no. of tillers; yield attributes i.e., no. of effective tillers (12.88%), spike length (14.49%), no. of grains per spike (13.85%), 1000-grain weight (10.57%) and yield i.e., grain yield (11.00%), biological yield (10.75%) than vermicompost at 1.5 t ha-1. Among methods of irrigation, every furrow irrigation recorded significantly higher in no. of tillers, yield attributes i.e., no. of effective tillers (13.68%), spike length (14.49%), no. of grains per spike (11.51%), 1000-grain weight (9.37%); yield (grain yield (17.15%), biological yield (22.08%) and economics (gross and net returns (15.52 and 25.66%) than alternate furrow irrigation. Among fertilizer level, application of N80P40 recorded significantly higher no. of tillers, spike length, no. of grains per spike, 1000-grain weight; yield (grain yield (13.02%), biological yield (15.81%), and economics (gross and net returns (13.72 and 24.49%) over other levels of fertilizer. Based on the study, it was found that vermicompost level, method of irrigation and fertilizer level has significant effect on no. of tillers, available NPK content in soil, yield attributes, yield and economics of barley.

Effect of FYM and Different Levels of Panchgavya on Growth and Establishment of Papaya (Carica papaya L.) cv. Red Lady

Today, with the advancement of environment pollution and health that is obtained from the improper use of inorganic fertilizer, production and use of organic fertilizer is considered as an important approach in the field of soil science in the world’s interest to investors. Research was conducted during the period 2023 on central research farm of department of horticulture, (NAI) SHUATS, Prayagraj. Field trial was designed on Randomized Block Design with three replications and ten treatments. Seedling were raised in polybag and 45 days old seedling were transplanted to the main field. Manure and fertilizer were applied as per treatment in ten equal split doses at 30,60 and 90days intervals. The treatment T9 (RDF) FYM+ Panchgavya (90ml/l) registered significantly maximum vegetative growth, chlorophyll content and survivality %. On the basis of our experimental findings, it can be concluded that the best result was found in treatment T9 (RDF) FYM+ Panchgavya (90ml/l) in term of vegetative growth parameters viz., plant height (cm), Number of leaves per plant, stem diameter (mm), leaf area (cm2) and root to shoot ratio, leaf area index (LAI), chlorophyll content and survivality % of papaya (Carica papaya L.) cv. Red lady.

Genetic Variability and Correlation Studies in Chilli (Capsicum annuum L.) Under Agro-Climatic Condition of Prayagraj

The present study assesses the extent of genetic variability and correlation in 12 different genotypes of chillies for various compositional and yield properties for identifying predominant genotypes for involvement in coming breeding programs. One of India's most significant crops for both vegetables and spices is the chilli. In the world, India is the top producer of dried chili. Around the world, people utilize chilli as a spice and to make drinks and medications. Since the beginning of time, curry has been an essential component of Indian cuisine. The field trial was conducted from December 2022 to June 2023 at the Horticulture Research Farm, Department of Horticulture, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj (U.P.), India. There is a great need and opportunity to assess and create location-specific cultivars with increased production potential. Twelve distinct genotypes of chillies were gathered from various regions of India for this inquiry in order to examine how well they performed in the Prayagraj agroclimatic conditions. The genetic data on yield and attributes associated with yield would be useful in developing a productive breeding program to enhance the chilli crop and create genotypes and hybrids that show promise.

Water use and yield response of rainfed safflower (Carthamus tinctorius L.) in Vertisols with varying soil depths

AbstractSafflower (Carthamus tinctorius L.) is an edible oilseed crop mainly cultivated in marginal lands. This study evaluates safflower crop water requirements to understand its feasibility to cultivate under rainfed ecosystem through a field experiment undertaken at the International Crops Research Institute for the Semiarid Tropics research farm, India. Eight improved and stress‐tolerant safflower cultivars (five spiny and three non‐spiny) were evaluated in Vertisols at three soil depths, that is, shallow: <0.60 m, medium: 0.60–1.20 m, and deep:1.20–1.80 m, over 3 years (2009–2012). Wet, normal, and deficit rainfall years were experienced during 2009/2010, 2010/2011, and 2011/2012, respectively. Soil moisture, crop yield, and growth parameters were measured, and field‐scale hydrology was captured through a calibrated one‐dimensional water balance model. Safflower responded to available residual soil moisture which varied with soil depth and rainfall received in different years. Total crop water use was 300–320 mm during the postrainy season, of which about 70% was extracted in deep Vertisols and 55% in medium Vertisols through residual soil moisture. In addition, 30% of water requirement was met through postrainy season rainfall. Safflower grown in shallow Vertisols could only meet 40% of crop water requirement. Spiny cultivar NARI‐H‐15 grown in deep soil recorded a maximum yield of 1890 kg ha−1 in the wet year. Seed yield from spiny cultivars grown in deep and medium soils was nearly similar (1500–1600 kg ha−1) during wet and normal years; a significant reduction in yield (>50%) occurred in shallow soils and also during a rainfall deficit year. Spiny cultivars produced 10%–50% higher seed yield compared to non‐spiny cultivars. Growing safflower in medium and deep Vertisols provides opportunities for crop intensification.

New records of family Chalcididae (Hymenoptera: Chalcidoidea) on vegetables ecosystem from New Delhi, India

ABSTRACT Chalcidids are important primary parasitoids for controlling several economic insect pests, and some are secondary parasitoids. These specimens were collected by using different traps during the period extending from November 2021 to October 2022, from various vegetable crops grown in different localities at ICAR-Indian Agricultural Research Institute (ICAR-IARI), New Delhi. The larvae and pupa of the pests were brought to the lab and reared for the emergence of parasitoids at 25 ± 0.5°C and relative humidity of 65 ± 5%. Eleven species belonging to four genera in three subfamilies were identified: Brachymeria bengalensis (Cameron, 1897); B. hime (Habu, 1960); B. kassalensis (Kirby, 1886); B. lasus (Walker, 1841); B. minuta (Linnaeus, 1767); B. podagrica (Fabricius, 1787) (Brachymeriinae); Dirhinus anthracia (Walker, 1846); D. auratus Ashmead, 1905 (Dirhininae) and Antrocephalus sepyra (Walker, 1846); Kriechbaumerella kraussi (Narendran, 1989); K. rufimanus (Walker, 1860) (Haltichellinae). Among them six species are newly recorded from New Delhi. On the other hand, B. hime was recorded for the first time as a parasite on Leucinodes orbonalis Guenée (Lepidoptera, Crambidae).

Using spectral vegetation indices and machine learning models for predicting the yield of sugar beet (Beta vulgaris L.) under different irrigation treatments

Yield prediction is essential for production planning, resource management, and competitive advantages. The use of vegetation indices and machine learning for yield prediction is rapid, practical, and accurate and contributes to the development of digital agriculture. Although many studies have been carried out on yield estimation, the number of studies on sugar beet and irrigation applications is limited. To solve this problem, in this study yield prediction of sugar beet under different irrigation treatments was carried out using spectral reflection-based vegetation indices obtained by proximal measurements and developed machine learning models. The multilayer perceptron (MLP), random forest (RF), k-nearest (kNN), bagging (BAG), support vector regression (SVR), gaussian processes (GP), and CustomNet (CN) predictors were used in yield prediction. The irrigation treatments included I100 (application of irrigation to increase the available moisture to field capacity by around 45–50% of the water holding capacity at the root depth), I75 (75% of the water applied in the control group), I50 (50% of the water applied in the control group), and I125 (25% of the water applied in the control group). The combinations of vegetation indices were determined using Pearson correlation and principal component analysis. OSAVI, SAVI, and NDVI had the most significant influence on the yield prediction of sugar beet. Among the combinations used, the kNN1 model (including all attributes as input) showed high R2 values of 0.99 for training and 0.64 for testing. In addition, the kNN3 model (including Treatment, NDVI, NWI, and OSAVI as inputs) had R2 values of 0.97 for training and 0.65 for testing, indicating successful outcomes. However, the MLP1 and SVR1 models had lower results with test R2 values of 0.53 and 0.56, respectively. The results demonstrate the successful application of machine learning and vegetation indices for yield prediction. The proposed approaches could encourage agricultural experts and researchers in future work for yield mapping and identification.

National dairy research programs: what is their role in animal health and sustainability research?

The US dairy industry has made great strides in improving animal health over many decades, which has driven substantial improvements in economic, social, and environmental sustainability. As consumer and corporate focus on climate continues to grow, the continued need to research and improve animal health and understand its connection with the environment is integral to the success of the dairy industry. Research to address these areas can be supported by national research programs and collaboration between them. The USDA and Dairy Management Inc established a collaborative research agreement in 2007; to date, this collaboration has not explicitly focused on animal health or its intersection with the environment. It is integral to the success of animal agriculture in an ever-changing sustainability landscape that animal health is addressed as a key piece of socioeconomic and environmental sustainability. An academic-industry stakeholder committee reached a consensus that supported this idea and identified that it is equally important to communicate these research findings with consumers in a way that resonates. The purpose of this Viewpoint article is to highlight that national research programs at the USDA Agricultural Research Service's National Animal Disease Center and Dairy Management Inc can and should play an important role in supporting and facilitating research at the intersection of animal health and sustainability broadly.

Seed Production in Jalandhar

A key factor in agricultural resilience, crop diversity, and productivity is seed production—particularly in areas like Jalandhar that must meet changing market demands and climate change. This project explores the complexities of seed production in Jalandhar and how it affects agricultural development with the goal of educating researchers, policymakers, and agricultural stakeholders on how to support sustainable seed production systems. Located in the rich plains of Punjab, Jalandhar has become a major centre for the production of seeds, especially for pulses, wheat, and rice. The region's favorable soil and climate, together with cutting-edge farming techniques, are what propel the expansion of the seed business. With the growing use of hybrid and genetically modified seeds, government programs encouraging agricultural output, and growing farmer awareness of the advantages of high-quality seeds, Jalandhar has a huge market potential for seed production. Nevertheless, in order to fully realize the potential of this industry, stakeholders must work together and implement strategic interventions in response to issues including volatile market pricing, restricted financial availability for small-scale farmers, and environmental sustainability concerns. The sector's growth trajectory is further aided by the existence of well-established agricultural research institutions and government policies that are supportive of the industry, providing growing opportunities in both domestic and foreign markets High-quality seeds improve crop yields while also contributing to overall sustainability and profitability in farming operations. Agro-ecologically-suited certified seeds are essential for reducing the danger of pests, illnesses, and unfavorable weather. Encouraging and supporting sustainable seed production systems in Jalandhar benefits all related departments and financial institutions by promoting agricultural development, economic success, and food security. Keywords : Seed production ,Agricultural development ,Market potential ,Sustainable seed systems ,Government initiatives ,Economic prosperity.

Effect of Nutrient Management on Growth and Yield of Foxtail Millet

The field experiment was conducted during ZAID season 2023 at experimental field of Crop Research Farm, Sam Higginbottom University of Agriculture, Technology and Sciences, Prayagraj, Uttar Pradesh, India. In the present study, the treatments consisting three levels of recommended dose of fertilizer (RDF) viz., 100% RDF (60-30-30 Kg/ha), 75% RDF (45-22.5-22.5 Kg/ha) and 50% RDF (30-15-15 kg/ha) along with three different micro nutrients viz., Zinc - 0.5 kg/ha, Boron - 0.5 kg/ha and Iron - 0.5 kg/ha. The experiment was laid out in a randomized block design with 10 treatments each replicated thrice. The soil of experimental plot was sandy loam in texture, nearly neutral in soil reaction (pH 7.3), low available nitrogen (278.93 kg/ha), medium available phosphorus (15.4 kg/ha) and medium available potassium (173.7 kg/ha). Results revealed that higher plant height (84.20 cm), plant dry weight (10.61 g), number of tillers/ hill (4.53), length of ears (9.20 cm), number of ears/plant (4.47), test weight (3.47 g), grain yield (1.22 t/ha), straw yield (2.80 t/ha) were recorded in treatment 8 (NPK 100% RDF+ Boron 0.5 kg/ha). Maximum gross return (INR 48,408.33), net return (INR 30,913.33) and B:C ratio (1.77) were also recorded in treatment 8 (NPK 100% RDF + Boron 0.5 kg/ha). It can be concluded that the application of NPK 100% RDF +Boron 0.5kg/ha (Treatment 8) recorded higher yield and benefit cost ratio in Foxtail millet.

Comparative Efficacy of Insecticides and their Combinations against Okra Shoot and Fruit Borer, Earias vitella (Fabricius)

The research was conducted on okra crop to check the efficacy of some insecticides and their combinations against okra shoot and fruit borer, Earias vittella (Fab.). The study was carried out during kharif 2023 at Central Research Farm of Sam Higginbottom University of Agriculture Technology and Sciences, Prayagraj (U.P.) with eight treatments including untreated check which were replicated thrice. All the treatments were found to be superior over untreated control, neem oil 3%, spinosad 45 SC, cypermethrin 25 EC, profenophos 50 EC, spinosad 45SC + neem oil 3%, cypermethrin 25EC + neem oil 3%, profenofos 50 EC + cypermethrin 25 EC were tested to compare the efficacy against Earias vitella and their influences on yield of okra. Here the best and the most economic treatment was profenofos 50 EC + cypermethrin 25 EC followed by cypermethrin 25EC + neem oil 3%, spinosad 45SC + neem oil 3%, spinosad 45 SC, cypermethrin 25 EC, profenophos 50 EC and the least effective treatment was neem oil 3%. The highest yield among the treatments was noticed in profenofos 50 EC + cypermethrin 25 EC (140quintal/hac.) and the lowest in neem oil 3% (75quintal/hac.) with cost benefit ratio 1:4.7 and 1:2.0, respectively.

Effect of Zinc and Panchagavya on Growth and Yield of Pearl Millet (Pennisetum glaucum L.)

A field experiment was conducted during Kharif 2023 at Crop Research Farm, Department of Agronomy, SHUATS, Prayagraj (U.P) on the topic “Effect of Zinc and Panchagavya on Growth and Yield of Pearl millet (Pennisetum glaucum L.)”, to study treatments consisting of three levels of Zinc viz. 10, 15 and 20 kg/ha and three levels of Panchagavya viz. 3, 4 and 5%. The soil of experimental plot was sandy loam in texture, nearly neutral in soil reaction (pH 7.6), low in organic carbon (0.25 %), available N (183.8 kg/ha), available P (11.50 kg/ha) and available K (87 kg/ha). There were 10 treatments each being replicated thrice and laid out in Randomized Block Design. The results revealed that treatment 9 (ZnSO4 20 kg/ha + Panchagavya- 5%) recorded significantly higher plant height (158.97 cm), plant dry weight (65.16 g) and length of ear (32.18 cm), No. of grains/ear (1824.66), test weight (8.02 g), grain yield (2.12 t/ha), stover yield (7.33 t/ha), gross return (INR 66509.00), net return (INR 46709.90) and B:C ratio (2.36) compared to other treatments.

Effect of Organic Manures on Growth and Yield of Cowpea (Vigna unguiculata L.) Varieties

A Field experiment was conducted during Zaid 2023 at Crop Research Farm, Department of Agronomy, SHUATS, Prayagraj (Uttar Pradesh) on Cowpea (Vigna unguiculata L.). The soil of experimental plot was sandy loam in texture, low in organic carbon (0.452%), nearly neutral in soil pH (7.1), high nitrogen (178.48 kg/ha), medium phosphorous (23.6 kg/ha), medium potassium (231.4 kg/ha). The experiment laid out in a randomized block design consists of three replications along with three cowpea varieties (viz., Kashi Nidhi, Kashi Unnati, Kashi Kanchan) and three solid organic manures (i.e. Poultry manure 2 t/ha, Goat manure 10.5 t/ha, Pig manure 15 t/ha) which were replicated thrice. The results revealed that maximum plant height (52.73 cm), dry weight (15.03 g/plant), crop growth rate (12.57 g/m2/day), number of pods/plant (11.80), number of seeds/plant (11.50), test weight (81.00g), seed yield (2.40 t/ha), stover yield (4.10 t/ha). Maximum net returns (INR 79,515.00/ha) and benefit cost ratio (2.30) which was significantly superior over other treatment T3 (Kashi Kanchan + Poultry manure 2 t/ha). It can be concluded that Kashi Kanchan variety with application of poultry manure 2 t/ha brought about significant improvement in the production and also proven economically viable in cowpea crop.

Differential Expression of Restorer Gene on Different Nuclear Background with Maldandi cytoplasm in Sorghum (Sorghum bicolor (L.) Moench)

To investigate the expression of restorer gene on different nuclear background an experiment was carried out using six iso-plasmic male sterile lines with maldandi cytoplasm, and each having different nuclear background. These lines were hybridized with a strong and stable restorer to generate six iso-plasmic hybrids at Main Agricultural Research Station (MARS), UAS Dharwad during rabi -2020-21. These hybrids were then evaluated for pollen fertility and seed set percentage during rabi -2021-22. The results found that, pollen fertility percentage of six iso-plasmic hybrids ranged from 69.82 per cent for ICSA 88004 A4 (M) × DSMR 8 to 92.42 per cent for M31-2A (M) × DSMR 8. Similarly, for seed set percentage M31-2A (M) × DSMR 8 and ICSA 88004 A4 (M) × DSMR 8 exhibited highest (85.17 per cent) and lowest (61.19 per cent), respectively. All the six iso-plasmic hybrids had varied expression for pollen fertility and seed set percentage which suggests that the restorer gene expressed differentially in different nuclear genome of female parent. The probable reasons for variation in fertility restoration behaviour are, abundance of inhibitors in the female parent or variation in the expressivity of restorer gene or influence of minor or modifier genes in the restorer parent or interaction between nuclear genes of both the parents.

Evaluation of Bio-efficacy of Compatible Agrochemicals against Sucking Pests in Soybean

A study was conducted at Agricultural Research Station (UAS, Dharwad), Sankeshwar, Karnataka during Kharif 2022-23 to assess the effectiveness of various agrochemicals alone and in combinations against whiteflies and thrips in soybean. Fifteen treatments were tested with three replications each. Among the treatments, diafenthiuron 50 WP at a concentration of 1.25 g/l exhibited the lowest mean population of whiteflies and thrips, with 2.63 and 3.22 per three leaves, respectively. This performance was comparable with its combination treatments, includes diafenthiuron 50 WP @ 1.25 g/l combined with propiconazole 25 EC @ 1 ml/l and 19:19:19 @ 5 g/l (2.92 whiteflies and 3.50 thrips/3 leaves), as well as diafenthiuron 50 WP @ 1.25 g/l combined with tebuconazole 50 + trifloxystrobin 25 WG @ 0.5 g/l and 19:19:19 @ 5 g/l (3.19 whiteflies and 3.74 thrips/3 leaves). Combination treatments effectively reduced whiteflies and thrips population as alone treatments by without showing any phytotoxicity symptoms on soybean crop.

Effectiveness of Zygogramma bicolorata Pallister (Coleoptera: Chrysomelidae) on Parthenium weed (Parthenium hysterophorus) under greenhouse condition in Ethiopia

Background Parthenium is an invasive annual weed that affects crop production, rangelands, grasslands, animals, the environment, and human health. Since its introduction into Ethiopia, different management options such as uprooting, slashing, burning, plowing, and applying synthetic herbicides have been practiced. However, these options are not sustainable in weed management. However, Zygogramma bicolorata is known to be used in different countries. Although many countries use it under field conditions, its population-based efficacy has not been well studied in Ethiopia. This study aimed to determine the effectiveness of Z. bicolorata populations on parthenium plants under greenhouse conditions. Methods This experiment was conducted at the Ambo Agricultural Research Center. Different numbers of Z. bicolorata per plant were used as treatments and were laid out in a completely randomized design with three replications. The numbers of damaged leaves, eggs, and larvae were recorded daily until the leaves were completely defoliated. The collected data and the correlation between beetle population and leaf defoliation were analyzed using SAS. Results The result revealed that all beetle populations caused damage to weed plants. A higher population of beetles completely defoliated the leaves within 12 days. However, lower numbers required 21 days to completely defoliate the weed. In contrast, a higher number of eggs (328.67) and larvae (272.33) were obtained from plants that received 20 pairs of beetles. The beetle population and exposure time were positively correlated, and the effectiveness of the bioagent was greater following the emergence of larvae. Conclusions Z. bicolorata can manage parthenium weeds, even with a lower population. However, more than 15 pairs of beetles could be suggested to manage weeds in a shorter time, and further study is needed under field conditions by considering the different agroecologies of the country.