Grain discoloration and its management: an emerging threat to paddy cultivation

Chhabra, Rohit; Vij, Lavanya

doi:10.1007/s41348-019-00272-2

Cited by 9 publications

(4 citation statements)

References 21 publications

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“…These results are consistent with those mentioned by Gutiérrez et al (2009b) In the present study, we found substantial links between meteorological variables and RGD during the susceptible critical period (Scp) between the flowering and hard dough stages. These findings are in accordance with those mentioned by Ou (1985), Pinciroli et al (2015), and Chhabra and Vij (2020), who stated that RGD starts at flowering and continues until maturity, and agree partially with those of Nunes (2013) and Malavolta and Takada (1997), who also considered the booting stage (7-10 days prior to flowering) as part of the Scp. Duraiswamy and Mariappan (1983) demonstrated that pathogenicity tests with spore suspensions of B. oryzae, A. padwickii and C. lunata caused maximum RGD when inoculation was performed at the flowering stage rather than at the milk or soft dough stage.…”

Section: Discussionsupporting

confidence: 92%

“…In contrast, other authors, e.g. Chhabra and Vij (2020) and Baite et al (2020), consider that the pathogens are able to infect rice plants under higher temperatures (28–33°C and 25–37°C, respectively).…”

Section: Discussionmentioning

confidence: 89%

“…More complex weather variables such as DPrecTRH and DWet1, which need relative humidity daily records (that are not always available in historical weather data) for their calculations, decreased slightly their correlations with RGDI. Several authors agree that high relative humidity subserve RGDI and disease severity (Baite et al, 2020;Chhabra & Vij, 2020;da Silva-Lobo et al, 2011), while others have found no correlation between relative humidity and RGDI (Rawte, 2007). Concerning precipitation, although it is widely mentioned as an influential factor, information regarding the amounts required to incentivize infection is scarce (Baite et al, 2020;dos Santos et al, 2009;Huang et al, 2011a).…”

Section: Discussionmentioning

confidence: 99%

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Modelling of the effects of environmental factors on rice grain discoloration incidence in Corrientes province, Argentina

Dirchwolf

Moschini

Gutiérrez

et al. 2022

Journal of Phytopathology

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Rice grain discoloration (RGD) is a disease of complex aetiology for which there are no resistant varieties. Due to the need to better define the environmental conditions that favour the disease, the aims of this work were to (i) identify the predominant fungi associated, (ii) determine the meteorological variables most closely related, and (iii) develop preliminary weather‐based models to predict binary levels of RGD incidence. After analysing 123 rice grain samples under natural infection conditions from rice‐cropping regions throughout Corrientes province, Argentina, we found that RGD was mainly associated with Alternaria padwickii (14.2%) and Microdochium albescens (13.7%). The strongest associations between weather variables and RGD incidence were observed in a susceptible critical period (Scp) that extended from the rice flowering stage until 870 accumulated degree days (Scp lasting 32 days, ±7 days). The binary response logistic model including the weather variables DPrecT (which combined the effect of the simultaneous daily occurrence of precipitation lower than 12 mm and air temperature between 13 and 28°C), and DDMnT (sum of the exceeding amounts of daily min temperature from 23°C), was the most appropriate, showing prediction accuracy (PA) values of 84.6%. The univariate model that included DPrecT presented a PA of 82.1%. The logistic regression techniques here used to develop weather‐based models to estimate the probabilities of occurrence of binary levels of RGD can not only help to clarify and quantify the environmental effect on the development of RGD but also be useful tools to be included in future management strategies.

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Section: Discussionsupporting

confidence: 92%

Section: Discussionmentioning

confidence: 89%

Section: Discussionmentioning

confidence: 99%

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Modelling of the effects of environmental factors on rice grain discoloration incidence in Corrientes province, Argentina

Dirchwolf

Moschini

Gutiérrez

et al. 2022

Journal of Phytopathology

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“…In the case of unpredictable climatic conditions across different ecological zones, severity of the disease also ranges from minor to major. The shape and size of the grain are affected by grain discoloration which further leads to a significant lower yield of the crop (Chhabra & Vij, 2019) The Terai region of Nepal is considered the granary of the country and it accounted for about 70 percent of the country's rice output, while the hills produces 26 percent and the mountain about 4 percent (CDD, 2015). Cereals are the main staple food of Nepal however; their production is dropped by 9% since last census (NPC, 2012).…”

Section: Introduction 11 Background Informationmentioning

confidence: 99%

An Economic Analysis of Rice Production in Rautahat District of Nepal

Sapkota¹,

Yadav²,

Sapkota³

2021

Food.agr.eco.rev.

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Study was conducted to analyze the production economics, socioeconomic status, potential and problems of rice in Rautahat district. Total 80 farmers were selected by simple random sampling method. Respondents were categorized into small and large scale based on the average land holding under rice cultivation. Result of socio demographic characters showed that the average household size and area under rice cultivation was 7.3 and 35.44 Katha respectively. Human labor was the major input used along with others viz. seed, tillage, FYM and chemical fertilizer and pesticides, irrigation in both large and small farms. The production per household (kg) and productivity (t/ha) were 4458.965 kg, 3.64t/ha respectively and there was significant difference in production (kg) per household between small scale farms (1811 kg) and large scale farms (7863.4 kg). The total average cost, gross revenue and gross margin per hectare were estimated as NPR.108214.79, NPR.120227.04 and NPR.12012.25 respectively. The average benefit cost ratio was 1.11. Cobb Douglas production function presented the inputs; human labor, tillage, FYM chemical and pesticides and irrigation were found to have positive relationship with income while other cost (mainly transportation cost) was found to have negative relation with the total income. The return to scale value was computed to be 0.96 indicating decreasing return to scale in rice production in Rautahat district. Therefore, the findings suggest that, the production and income can be maximized by efficiently solving problems of quality inputs and others mentioned.

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