Looking forward to exploring the next steps in crop monitoring and prediction! #PhDLife #RemoteSensing #RiceResearch #PrecisionAgriculture #MachineLearning

Many thanks to my supervisors @jamesbrinkhoff , @AndrewR234972, @BrianDunn1287 , and support from @une_aarsc , @AgriFuturesAU Australia, @UniNewEngland , and @NSW_AgWater , Yanco. Grateful to @RemoteSens_MDPI Remote Sensing for publishing our work.

-We found that combining remote sensing + weather features gave better predictions than either alone. -TabPFN & LSTM models outperformed tree-based and linear models for rice phenology prediction

In this study, we used -4 years of field data across 300+ field points. -7 rice varieties. - predicting panicle initiation, flowering & maturity using a combination of remote sensing + weather data.

Excited to share my first research paper as a PhD student! Title: Integrating Remote Sensing & Weather Time Series for Australian Irrigated Rice Phenology Prediction 📎 https://t.co/uVS7XvcsWs

Passover lamb shanks with @une_aarsc PhD researchers @jhakumarsunil (rice remote sensing) and @EphraimAchin (sensors for olive irrigation)

Strange being back at the desk in Armidale after 10 days enjoying 39 deg in the sun, sampling Riverina #rice grain moisture for our @AgriFuturesAU projects. @BrianDunn1287, TinaDunn, @joshhart93, @alex__schultz (@nswdpi) and @jhakumarsunil (@une_aarsc), +catchups w @RiceExtension

Love getting back to the Riverina, this time with @une_aarsc PhD student @jhakumarsunil. This weekend featured dawn at Fivebough wetlands, BBQ with the Dunn's, Leeton Presy church, Whitton Malt House.

Our @AgriFuturesAU Real-Time-Rice project featured on @UniNewEngland Agriculture Facebook page: https://t.co/hudwJ1OSl2 Delivering decision-making tools for Aus rice growers

In a recent field trip to Leeton, PhD student @jhakumarsunil visited our rice project collaborators from @nswdpi. Sunil had the chance to learn rice panicle initiation and nitrogen sampling techniques, contributing valuable insights for optimising fertilizer input and irrigation.

Happy group of rice samplers knocked over 105 quad samples today, did PI dates and fertilised 36 plots. Should sleep well. @jhakumarsunil @Alex__Schultz @JoshHart93 @jamesbrinkhoff

Congratulations to @une_aarsc PhD student, @jhakumarsunil who just presented his confirmation of candidature, with some great feedback. Looking forward to some excellent #rice #remotesensing research over the coming years with @BrianDunn1287 @AndrewR23497213 @AgriFuturesAU

Check out sugarcane crop classification using a 2D convolutional neural network (CNN) and pre-trained CNN models. https://t.co/Du2GKVhTup