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Nurwulan Agustiani
Indonesian Center for Rice Research
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CRITICAL VARIABLES OF MORPHO-PHYSIOLOGICAL RICE PLANT UNDER STAGNANT FLOODING CONDITIONS Nurwulan Agustiani; Sujinah Sujinah; Indrastuti Apri Rumanti
Indonesian Journal of Agricultural Science Vol 22, No 1 (2021): JUNE 2021
Publisher : Indonesian Agency for Agricultural Research and Development

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21082/ijas.v22n1.2021.p1-7

Abstract

Stagnant flooding (SF) stress has contributed decreasing rice production in Indonesia. The study aimed to explore critical variables of rice growth that contribute to the decreasing grain yield under SF conditions and a common irrigation system (control). The experiment was arranged in a complete randomized block design with four replications to test 10 rice genotypes (Inpari 30 Ciherang Sub-1, Inpara 3, Inpara 4, Inpara 8, IRRI119, IRRI154, IR42, IR14D121, IR14D157, and Tapus). The water depth was managed according to the farmer’s practices for control, while for SF plots the standing water depth was gradually increased from 35 days after transplanting and was maintained at 50 cm until harvest. Results showed that plant height, tillering ability, leaf greenness, panicle number per hill and grain filling percentage were critical growth variables that affect grain yield at optimal conditions. The yield of the 10 genotypes decreased by 25–50% under SF conditions. Inpara 3 had the stable yield in those two watering conditions. Therefore, it could be used as a check variety for SF condition. Inpara 9 and IRRI119 experienced decreased yield of more than 50% under SF conditions. The key factors determining the decreased yield were tillering ability and green leaf level. Optimization of the two variables at SF conditions will largely determine rice yield associated with panicle number per hill and grain number per panicle. Results of the study are useful as preliminary recommendations for designing new variety and cultivation techniques to reduce the impact of SF stress on rice yield.
VALIDASI AWAL TEKNOLOGI PENENTUAN WAKTU TANAM LAHAN SAWAH TADAH HUJAN “WeRise” MENGGUNAKAN VARIETAS UNGGUL INPARI 41 Nurwulan Agustiani; Sujinah Sujinah; Z. M. Hikmah; L. Hadiawati; Samijan Samijan; Y. Kamal; M. I. Wahab; L. Lliorca; K. Hayashi
Agric Vol. 33 No. 2 (2021)
Publisher : Fakultas Pertanian dan Bisnis, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/agric.2021.v33.i2.p165-174

Abstract

WeRise is a rainfed specific technology (IRRI-JIRCAS-IAARD) that helps farmers to determine planting time according to rainfall distribution and specific variety. The research was conducted in West Nusa Tenggara (WNT) and Central Java at 2018, involving 15 farmers in each location. It compared planting time according to WeRise’s recommendation (1) and farmers’ practice (2), using the same variety, namely Inpari 41, which is a specific high yielding variety for rainfed. It was analyzed using the T test at the 5% level. The best WeRise’s recommendations in WNT was ± 1 December 2018, while farmers’ planting time was carried out on ± 15 November 2018. Meanwhile, in Central Java WeRise’s recommendations was same as the farmers, on ± 15 November 2018. However, testing was still carried out following the second / third alternative WeRise recommendation even though the yield prediction were lower (1 December 2018). The yield from WeRise treatment and farmer practices was not significantly different with an average yield of 5.01 t ha-1 for the WeRise treatment and 4.84 t ha-1 for farmer practice in Central Java and an average yield of 5.44 t ha-1 for the WeRise treatment and 5.65 t ha-1 for farmer practice in WNT. This means that in this initial validation WeRise had shown a fairly good performance with equivalent yield to farmers. However, it was suspected that Werise’s prediction in Central Java was still too low or 54% lower than the actual yield, while the prediction in NTB reaches 102%.
Co-Authors Indrastuti Apri Rumanti K. Hayashi L. Hadiawati L. Lliorca M. I. Wahab Samijan Samijan Sujinah Sujinah Sujinah Sujinah Y. Kamal Z. M. Hikmah