Adoption level of integrated crop management practices among rice farmers: Does the adoption of production technology predict postharvest technology adoption

SAMARICA is the second district of Occidental Mindoro province in the Philippines having a vast land area for rice production. It supports the rice milling sector of the province with promising facilities for postharvest of rice. This study investigates the rice farmers’ adoption level of integrated crop management practices (ICMPs). The adoption ICMPs aims to promotes farm productivity and efficiency. A total of 404 rice farmers participated in this study selected through a multi-stage sampling technique. Quantitative data were generated from the survey questionnaire and were analyzed using Descriptive Statistics. Partial Least Square Structural Equation Modeling (PLS-SEM) was used to analyze the relationship between production and postharvest practices. The results revealed that rice farmers have “very high” adoption of rice production technologies except for water technologies and intermittent irrigation with “high” adoption level. In terms of postharvest, there is “very high” adoption of mechanized harvesting and recommended moisture content for rice but “moderate” adoption for rice parboiler, dying machines, and threshing of rice right after harvest. On the other hand, a statistically significant evidence was found for production technologies as predictor of postharvest technologies, specific for the care and management of rice (β =0.55; P<0.01).

Rice crop response to site variability in a multi-locational trial: A call for site specific management

Yield is a net expression of genotype (G) x environment (E) interactions including management. However, the segregation of 'E' into respective causes is seldom done while 'G' is a constant. Soil is a component of 'E' with imminent variability in attributes among multiple locations. Data on yield response of varieties to a set of treatments in different soils from multi-locational yield maximisation trial under All India Coordinated Rice Improvement Project were regularly gathered. A dataset pertaining to a trial conducted in Karaikal district of Puducherry Union Territory was analysed to ascertain the site-specific crop responses with inherent variability in soils. Rice varieties, ADT 46, BPT 5204 and CR 1009 were tested for responses at 17 sites with farmer fertiliser practices (FFP), regional recommended fertiliser dose (RDF) and software, 'Nutrient Expert®' (2016) (NE) derived fertiliser quantities. Analysis of variance showed that test sites explained 59.3% variability in yield. A multivariate technique, Factor Analysis extracted two factors, which are linear combinations of soil attributes those explained 76% of variance in soils. Factor scores classified soils into four groups, owing to variability in soil properties. Soil texture influenced yield significantly (across varieties and treatments) (R2 = 11.1%). Sites varied in excess duration in nursery ranging from 2 - 26 days. However, this excess duration reduced number of panicles m-2 only in CR 1009 (r = -0.328**). General linear model with sites and treatments as fixed factors, their interactions and panicles m-2 as covariate predicted better (R2 = 90.3%) with their significant contribution to the model. The order of R2 (%) was Sites (59.3) > Varieties (27.4) > Treatments (13.6%) in explaining variability in yield highlighting site-specific responses. Mean differences between ADT 46 and BPT 5204; BPT 5204 and CR 1009 were significant. Yield significantly changed across sites and treatments when fertiliser management shifted from non-specific (FFP) to site-specific NE based calculations through RDF (region specific). Results of this trial placed emphasis on soil test-based crop management to realise the uniform best, which clearly is site specific crop management.