Journal of Scientific Research and Reports

Studies on Heterosis for Pest and Disease Resistance in Spiny Brinjal

2026-07-16T10:48:08+00:00

Aims: The present investigation was undertaken to estimate standard heterosis for resistance to major insect pests and diseases in spiny brinjal (Solanum melongena L.) and to identify promising hybrid combinations that could serve as parental materials for future resistance breeding programmes.

Study Design: A five-parent full diallel mating design excluding selfing was evaluated in a randomised block design (RBD) with three replications.

Place and Duration of Study: The experiment was conducted at the Horticultural Farm, Department of Horticulture, Pandit Jawaharlal Nehru College of Agriculture and Research Institute (PAJANCOA & RI), Karaikal, Union Territory of Puducherry, India, during 2024–2026.

Methodology: Five genetically diverse parents, namely Illavambadi local (P₁), VRM–1 (P₂), Blue spiny brinjal (P₃), Small spiny brinjal (P₄), and Thar Rachit (P₅), were crossed in a full diallel mating design excluding selfing to produce twenty F₁ hybrids, including reciprocal crosses. The parents and hybrids were evaluated under natural field conditions in a randomised block design with three replications. Shoot and fruit borer infestation, bacterial wilt incidence, and phomopsis blight incidence were recorded following the standard procedures described by Mishra et al. (1988), Hussain et al. (2005), and Meah (2007), respectively. Standard heterosis was estimated over the commercial hybrid Sarpan Hybrid-65. Percentage data were analysed by ANOVA following appropriate transformation.

Results: Considerable variation was observed among the parents and F₁ hybrids in resistance to shoot and fruit borer, bacterial wilt, and phomopsis blight. Among the hybrids, shoot and fruit borer infestation ranged from 4.30 to 6.30%, bacterial wilt incidence from 0.40 to 1.60 PDI, and phomopsis blight incidence from 4.80 to 6.70 PDI. Small spiny brinjal × Thar Rachit (P₄ × P₅) recorded the lowest shoot and fruit borer infestation (4.30%) and phomopsis blight incidence (4.80 PDI), whereas Illavambadi local × VRM–1 (P₁ × P₂) recorded the lowest bacterial wilt incidence (0.40 PDI) and matched the commercial check for bacterial wilt and phomopsis blight. The commercial check recorded the lowest shoot and fruit borer infestation and was not surpassed for any resistance trait. Therefore, none of the hybrids expressed desirable standard heterosis over the commercial check. Nevertheless, several hybrids recorded lower pest and disease incidence than the remaining experimental hybrids, indicating their potential value as breeding materials.

Conclusion: Small spiny brinjal × Thar Rachit, Illavambadi local × VRM–1, Blue spiny brinjal × Thar Rachit, Thar Rachit × Small spiny brinjal, and Blue spiny brinjal × VRM–1 were identified as promising hybrid combinations among the experimental crosses because of their comparatively lower pest or disease incidence. Although these hybrids did not surpass the commercial check, they may serve as valuable parental materials for developing resistant cultivars after validation across seasons and locations.

Modelling Nonlinearity and Volatility in Castor Prices: A Comparative Study of ARIMA, ARCH, GARCH and Neural Network Models in Patan Market, Gujarat, India

2026-07-16T10:54:26+00:00

Castor (Ricinus communis L.) is a commercially important non-edible oilseed crop in North Gujarat, and price volatility in its principal markets remains a major source of income risk for growers and traders. This study fitted and compared linear, volatility-based and machine-learning models for the weekly castor price series from the Patan market over the period from January 2004 to December 2024 (1,092 weekly observations constructed as period-average aggregates of daily Agmarknet quotations). The Augmented Dickey-Fuller test confirmed that the series was non-stationary in levels but stationary after first differencing; the Brock-Dechert-Scheinkman test established significant nonlinearity; and the ARCH-LM test confirmed the presence of volatility clustering. Accordingly, an ARIMA(3,1,5) model, an AR(1)-ARCH(3) model, an ARMA(0,1)-GARCH(1,2) model and a feed-forward artificial neural network (14-32-1 architecture) were fitted, and their in-sample and out-of-sample performance was evaluated using RMSE, MSE, MAE and MAPE. Among the econometric models, ARIMA(3,1,5) provided the best level-based fit (RMSE = 663.38; MAPE = 9.79%), whereas ARMA-GARCH outperformed AR-ARCH in modelling conditional variance. The ANN model recorded the lowest error for every metric evaluated (RMSE = 115.31; MAPE = 1.37%), consistent with the nonlinear dependence detected by the BDS test. However, because the ANN was fitted to price levels using engineered lagged and rolling features, whereas the ARCH-family models were fitted to returns, the comparison was not fully equivalent and the performance gap should be interpreted with this caveat. The findings underline the value of combining diagnostic testing with a multi-model framework when characterising agricultural commodity price behaviour.

Assessment of Genetic Diversity of Maize (Zea mays L.) Inbreds for Starch Content, Yield and Yield Contributing Traits

2026-07-16T11:00:02+00:00

Genetic diversity among parental inbred lines is essential for developing productive maize hybrids with improved grain quality. This study assessed genetic diversity among 30 maize (Zea mays L.) inbred lines for starch content, grain yield and ten yield-contributing traits. The experiment was conducted during Rabi 2025–26 at the Maize Research Unit, Agricultural Research Institute, Rajendranagar, Hyderabad, using a randomised block design with three replications. Starch content was quantified by the anthrone method, and the data were analysed through analysis of variance, Mahalanobis D² statistics, Wilks’ criterion and Tocher’s clustering. Significant differences were detected among the inbred lines for all 12 traits, indicating substantial genetic variability. The genotypes were distributed across 11 clusters, and inter-cluster distances ranged from 19.50 to 179.01. The greatest divergence occurred between Clusters VI and IX. Ear height contributed most to total genetic divergence, followed by ear length and ear girth. Starch content ranged from 50.82% to 63.51%, while yield per plant ranged from 81.53 to 127.57 g. BML 51 and BML 7 combined high starch content with superior grain yield and were therefore identified as promising parental lines for simultaneous improvement of both traits. Crosses involving genetically distant clusters may broaden variability, although their heterotic performance requires confirmation through hybrid evaluation and combining-ability studies.

Isolation, Identification, and Molecular Characterisation of Shiga Toxin-producing Escherichia coli from Raw Beef

2026-07-16T12:47:18+00:00

Shiga toxin-producing Escherichia coli (STEC) is a foodborne pathogen associated with contaminated animal-derived foods. This study investigated the occurrence of E. coli and the presence of Shiga toxin-associated genes in raw beef collected in the Chittoor district of Andhra Pradesh. Seventy-two raw beef samples were obtained from slaughterhouses and retail meat shops and examined using conventional microbiological and molecular methods. Samples were enriched in MacConkey broth and cultured on Eosin Methylene Blue agar. Presumptive E. coli colonies were purified and confirmed by biochemical testing. Genomic DNA was extracted from the confirmed isolates, and polymerase chain reaction assays were used to detect the stx1 and stx2 genes. Of the 72 samples examined, 35 yielded presumptive E. coli, corresponding to a prevalence of 48.61%. Among the 35 isolates, four carried stx1 and three carried stx2, representing 11.42% and 8.57% of the isolates, respectively. These findings confirm the presence of Shiga toxin-associated genes among E. coli isolates recovered from raw beef in the study area. The results indicate the need for consistent hygienic practices during slaughter, meat handling, processing, and distribution. Continued microbiological surveillance across the meat supply chain may support the early detection of STEC contamination and inform locally appropriate food-safety measures.

Epidemiology, Occurrence and Severity of Early Blight of Potato Caused by Alternaria solani (Sorauer)

2026-07-16T12:53:27+00:00

Early blight of potato caused by Alternaria solani (Sorauer) remains a significant foliar problem in Uttar Pradesh; however, much of the research on its weather-driven epidemiology in the state is based on earlier studies and often considers more than one site at a time. A field survey was conducted during the 2022 Rabi season at five locations across the state—Kanpur, Kannauj, Agra, Meerut and Varanasi—which were selected to capture meaningful variation in winter temperature, humidity and soil conditions. Six commercial fields were monitored at each site. All fields were planted within a narrow window between 15 and 25 October 2022 and received no fungicide application, thereby allowing natural disease progression to be recorded. Disease severity was assessed weekly using the 0–5 scale of Horsfall and Barratt (1945) and expressed as the percent disease index (PDI). The pathogen was isolated from ten symptomatic leaves per location, purified, characterised morphologically and confirmed as pathogenic on Kufri Bahar through glasshouse inoculation. Local weather records were obtained from the observatory nearest to each field, and PDI was related to nine weather variables using Pearson correlation and full-model multiple linear regression. Disease appeared earliest at Agra (9 November 2022) and latest at Kanpur (22 November 2022). Final PDI ranged from 27.68 % at Kanpur to 38.46 % at Agra; the apparent infection rate ranged from 0.0859 units day−¹ at Varanasi to 0.1266 units day−¹ at Kanpur, and AUDPC ranged from 548.6 %-days at Kanpur to 1024.8 %-days at Agra. Maximum and minimum air temperatures showed consistent negative associations with PDI at every site.