Determination of Paddy Rice Yield in the Context of Farmers’ Adoption of Multiple Technologies in Colombia

Ly, Nguyen Thi; Nanseki, Teruaki; Ogawa, Satoshi; Chomei, Yosuke

doi:10.1007/s42106-021-00173-1

Cited by 4 publications

(4 citation statements)

References 12 publications

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“…Fruit yield of different varieties of potatoes has been studied and the yield of single potatoes has been determined [17][18][19].…”

Section: Potato Yield Determinationmentioning

confidence: 99%

Study on early maturity and high yield cultivation technology of potato considering quality input parameters

Xia,

Gao,

Xie

2023

Applied Mathematics and Nonlinear Sciences

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[Objects] In order to determine the best parameter of potato early-maturing and high-yield cultivation technology, the early-maturing and high-yield cultivation technology considering quality input parameters was studied. [Methods] Four varieties of early-maturing potato, Zaodabai, Zihuabai, Kexin 6 and Dongnong 303, were selected as experimental materials. Sowing time, fertilizer formula and pest control were selected as quality input parameters, the plant height, weight, stem diameter, leaf area index, potato yield and vitamin C were selected as potato quality evaluation parameters, and the effects of different quality input parameters on early maturity and high yield of potato were determined. [Results] The sowing time of potato cultivation was about March 1, and the formula of fertilization was 160 km2 of N, 150 km2 of P2O5, and 105 km2 of K2O. When comprehensive pest control measures were adopted, the potato had the best quality and the highest yield. [Conclusion] The yield and quality of potatoes can be improved by adjusting sowing time, fertilization formula and formulating effective pest control measures.

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“…Fruit yield of different varieties of potatoes has been studied and the yield of single potatoes has been determined [17][18][19].…”

Section: Potato Yield Determinationmentioning

confidence: 99%

Study on early maturity and high yield cultivation technology of potato considering quality input parameters

Xia,

Gao,

Xie

2023

Applied Mathematics and Nonlinear Sciences

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“…However, yields in rain-fed systems can also be high under favorable environmental and management conditions [3]. Various initiatives are in place to improve rice productivity and sustainability, including promoting high-yielding varieties and providing technical assistance and training to farmers [4][5][6]. One topic of interest is plant breeding, where, through the selection of favorable genes and higher-level omics characterization [7], optimal rice varieties are obtained for cultivation.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Rice Yield Based on Biomass and SPAD-Based Leaf Nitrogen for Large Genotype Plots

Duque

Patino

Colorado

et al. 2023

Sensors

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The use of Unmanned Aerial Vehicle (UAV) images for biomass and nitrogen estimation offers multiple opportunities for improving rice yields. UAV images provide detailed, high-resolution visual information about vegetation properties, enabling the identification of phenotypic characteristics for selecting the best varieties, improving yield predictions, and supporting ecosystem monitoring and conservation efforts. In this study, an analysis of biomass and nitrogen is conducted on 59 rice plots selected at random from a more extensive trial comprising 400 rice genotypes. A UAV acquires multispectral reflectance channels across a rice field of subplots containing different genotypes. Based on the ground-truth data, yields are characterized for the 59 plots and correlated with the Vegetation Indices (VIs) calculated from the photogrammetric mapping. The VIs are weighted by the segmentation of the plants from the soil and used as a feature matrix to estimate, via machine learning models, the biomass and nitrogen of the selected rice genotypes. The genotype IR 93346 presented the highest yield with a biomass gain of 10,252.78 kg/ha and an average daily biomass gain above 49.92 g/day. The VIs with the highest correlations with the ground-truth variables were NDVI and SAVI for wet biomass, GNDVI and NDVI for dry biomass, GNDVI and SAVI for height, and NDVI and ARVI for nitrogen. The machine learning model that performed best in estimating the variables of the 59 plots was the Gaussian Process Regression (GPR) model with a correlation factor of 0.98 for wet biomass, 0.99 for dry biomass, and 1 for nitrogen. The results presented demonstrate that it is possible to characterize the yields of rice plots containing different genotypes through ground-truth data and VIs.

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“…[2]. To increase productivity, reduce production costs, be environmentally friendly, and adapt to climate change, the adoption of various agricultural technologies has become the best option worldwide [3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Adoption Rate of Lowland Rice Technology in Bolaang Mongondow Regency, North Sulawesi Province

Sondakh,

Da Silva,

Rembang

et al. 2023

E3S Web of Conf.

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Farming technology will be successful if farmers adopt it correctly. The research aims to determine the level of farmers’ adoption of lowland rice farming technology. The research location was in Bolaang Mongondow Regency in October 2022, using a survey technique of 30 lowland rice farmers. Adoption data were analyzed descriptively and Spearman’s correlation statistic test. The results of the correlation test showed that there was a negative relationship between the adoption of technology components and age and education, but was positive for farming experience, land area, innovation characteristics. The information channel correlation is not significantly related at the level of α = 0.05 with the technology component adopted, this means that there are many information channels that can be utilized but farmers do not directly apply the technology obtained. Meanwhile, the adoption of lowland rice technology components, namely harvest handling - post-harvest, was 96.67%, the use of NSV and intermittent irrigation was 90% each, and other technological components were below 80%. The government has an important role in introducing technological innovations by adjusting the level of needs and whereabouts of farmers to technological components so that they can be adopted for the expected increase in productivity.

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Determination of Paddy Rice Yield in the Context of Farmers’ Adoption of Multiple Technologies in Colombia

Cited by 4 publications

References 12 publications

Study on early maturity and high yield cultivation technology of potato considering quality input parameters

Study on early maturity and high yield cultivation technology of potato considering quality input parameters

Characterization of Rice Yield Based on Biomass and SPAD-Based Leaf Nitrogen for Large Genotype Plots

Analysis of the Adoption Rate of Lowland Rice Technology in Bolaang Mongondow Regency, North Sulawesi Province

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