Plain-language summaries of my peer-reviewed work on crops, pests and farm mechanisation in Nepal, and practical guides to the methods behind it: Sentinel-2 vegetation indices, Google Earth Engine, R for field trials and DSSAT crop modelling. Written for agriculture students, researchers and supervisors.
In-press TURJAF study by Bishal Neupane: an RCBD okra trial at Katahari, Morang found GA3 at 100 ppm most effective for growth and yield.
Read articleNAA at 150 ppm raised okra pod yield to 9.55 t/ha vs 3.39 t/ha in the control, while GA3 + NAA gave the tallest plants. RCBD trial, Sunsari, Nepal.
Read articleIR-19-A-5000 gave 6.38 t/ha, the earliest maturity and lowest sterility among nine spring rice genotypes tested against Hardinath-1 in Sunsari, Nepal.
Read articleSurvey of 60 Chitwan maize farmers: fall armyworm ranked a top pest, yet 35% used no control and none used cultural or biological methods.
Read articleSilver plastic mulch cut aphids, cutworms and Helicoverpa on lettuce; rice straw drew ladybirds and gave 13.07 t/ha. Field trial, Lalitpur, Nepal.
Read articleGA3 at 35 ppm gave the best mango fruit retention, BAP 15 ppm the top yield and NAA 35-50 ppm the sweetest fruit in a Bombay Green trial, Sarlahi, Nepal.
Read articleChandani vs Raja cucumber in Morang, Nepal: cost, yield, profit and BCR (2.40 vs 2.19) from a 60-farmer survey, plus top constraints.
Read articleSurvey of 100 maize households in Gulmi, Nepal: 69% use power tillers, 13% post-harvest machines; lack of advice (66%) outranks cost (17%).
Read articleSurvey of 91 spring rice growers in Rautahat, Nepal: irrigation and seed access shaped variety choice; sowing time changed cost and yield.
Read articleReview of 2019-2025 evidence on rice mechanization in Nepal: stage-wise rates, adoption drivers, barriers, AMPP 2014, PMAMP and spring rice.
Read articleHow a crop disease detection app works: MobileNetV2 transfer learning, offline TFLite inference, Flutter and FastAPI, and GPS-tagged data for Nepal.
Read articleA beginner's guide to DSSAT v4.8.5: the Cropping System Model, CERES vs CROPGRO, required inputs, GENCALC and GLUE calibration, and RMSE and d-index.
Read articleRemote sensing in agriculture works best with GIS and machine learning together. What each adds, a combined workflow, and examples from Nepal.
Read articleGoogle Earth Engine land cover classification with K-Means and Sentinel-2: code, cluster labelling and accuracy assessment, from a Kaski, Nepal project.
Read articleNDWI water body detection with Sentinel-2 in Google Earth Engine: McFeeters vs Gao NDWI, reading negative values, and seasonal composites for Pokhara.
Read articleStep-by-step RCBD ANOVA in R: aov() with blocks, Shapiro-Wilk and Levene checks, agricolae LSD and Duncan tests, and a ggplot2 bar chart with letters.
Read articleNDVI formula for Sentinel-2 (B8, B4) plus NDWI, SAVI, GCI and PSRI: correct bands, value ranges, when to use each, and working Earth Engine code.
Read articleHow an agriculture student in Nepal can build a research portfolio without grants: internship field trials, co-authored papers, open GEE and R work.
Read articleFor supervisors seeking a graduate research assistant in precision agriculture: Bishal Neupane's research aims, nine 2026 papers, field and GIS skills.
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