An experiment was conducted at the research farm of Assam Agricultural University, Jorhat, Assam during 2020–22 to assess the genetic variability among 50 rice (Oryza sativa L.) genotypes with respect to ratooning ability and perennation. Out of 50 genotypes, only 30 genotypes showed different degree of ratoon production and ratoon yield. All the genotypes showing better ratooning ability mainly belonged to photo-insensitive group and only few were slightly photosensitive. True perenniation as expressed by formation of rhizome (O. longistaminata) was not observed in any of the genotypes. However, stolen formation as in O. rufipogon was observed only in 1 genotype Terabali. ANOVA result suggested the presence of statistically significant variability among all the genotypes in both main and ratoon crop. Genotypes, viz. Binadhan-11, Sayjihari and IR-64 were found to be best performing for all the desirable ratoon crop traits. High heritability coupled with high genetic advance was estimated for all the ratoon crop traits except for days to ratoon maturity indicating the involvement of additive gene action in the expression of the traits.
The research was conducted at Instructional cum Research (ICR) farm in Assam Agricultural University, Jorhat, Assam for the year 2019–21 with the objective to determine the crossability of wild rice species O. longistaminata and O. rufipogon with O. sativa and observe the inheritance of rhizome. In first year of experiment, varieties having good ratooning ability were identified. Out of them, five varieties namely Ranjit, Ranjit sub-1, IR-64, Binadhan-11 and Bahadur were crossed with both of the wild species. Crossablity of O. longistaminata with O. sativa ranged from 11.1% (Ranjit sub-1 × O. longistaminata) to 22.2% (Binadhan11 × O. longistaminata) while O. rufipogon with O. sativa ranged from 13.3% (Ranjit sub-1 × O. rufipogon) to 30% (Ranjit × O. rufipogon). All the hybrids except for IR64 × O. longistaminata were photoinsensitive as that of their female parent. Hybrids from O. sativa/O. longistaminata exhibited various distinguishing characters which can be used as morphological marker in order to identify true interspecific hybrids in further breeding programme. The pollen viability of these interspecific hybrids were found lower than both the parents. However, rhizome formation could not be observed in any hybrid.
Black pepper (Piper nigrum L.), is a high-value historic spice crop that is mainly cultivated in Vietnam, Indonesia, India, Malaysia, Brazil, and Sri Lanka. It is valued for its characteristic aroma, pungent and biting taste and is mainly used for flavoring and seasoning. Black pepper is grown commercially in the southern part of India, but in some states in North-East India predominantly Assam is also engaged in the production. Black pepper cultivation in Assam covers 3428 ha area, producing 1833 tons of peppercorn (Kandiannan, 2018).Black pepper production is challenged by about 17 diseases, one of them being foot rot or nursery wilt (Thomas and Naik, 2017). Nursery wilt is caused by Phytophthora capsici, an oomycete soil-borne phytopathogen that causes 30%-40% yield loss in Indonesia (Nam, 2012), more than 95% loss in Malaysia, and up to 30% yield decline in India (Anandaraj, 2002). For disease establishment, there should be proper optimization of all variable factors (host, pathogen, and environment) at correct and for sufficient time. All factors and elements should be in favor of pathogen for epiphytotic (Graham and Vance, 2003). A study on the role of weather parameters on the epidemiology of foot rot in Karnataka was carried out by Shamarao and Siddaramiah (2002). However, information regarding the relationship between nursery wilt incidence and weather variables is still lacking. Therefore, the present study was piloted up intending to investigate the role of different weather parameters on the natural occurrence of nursery wilt in Assam and develop a forecasting model to prewarn the farmers about the disease risk as well as to develop a comprehensive approach for sustainable and eco-friendly management of nursery wilt. The mathematical model was constructed using Binary Logistic regression which was further validated. The accuracy of the model was scrutinized and fitness was examined to display the real facet of the black pepper and nursery wilt pathosystem.
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