Добірка наукової літератури з теми "Water quality management (N.S.W.)"

ABSTRACTAvian and possum fecal droppings may negatively impact roof-harvested rainwater (RHRW) water quality due to the presence of zoonotic pathogens. This study was aimed at evaluating the performance characteristics of a possum feces-associated (PSM) marker by screening 210 fecal and wastewater samples from possums (n= 20) and a range of nonpossum hosts (n= 190) in Southeast Queensland, Australia. The host sensitivity and specificity of the PSM marker were 0.90 and 0.95 (maximum value, 1.00), respectively. The mean concentrations of the GFD marker in possum fecal DNA samples (8.8 × 107gene copies per g of feces) were two orders of magnitude higher than those in the nonpossum fecal DNA samples (5.0 × 105gene copies per g of feces). The host sensitivity, specificity, and concentrations of the avian feces-associated GFD marker were reported in our recent study (W. Ahmed, V. J. Harwood, K. Nguyen, S. Young, K. Hamilton, and S. Toze, Water Res 88:613–622, 2016,http://dx.doi.org/10.1016/j.watres.2015.10.050). The utility of the GFD and PSM markers was evaluated by testing a large number of tank water samples (n= 134) from the Brisbane and Currumbin areas. GFD and PSM markers were detected in 39 of 134 (29%) and 11 of 134 (8%) tank water samples, respectively. The GFD marker concentrations in PCR-positive samples ranged from 3.7 × 102to 8.5 × 105gene copies per liter, whereas the concentrations of the PSM marker ranged from 2.0 × 103to 6.8 × 103gene copies per liter of water. The results of this study suggest the presence of fecal contamination in tank water samples from avian and possum hosts. This study has established an association between the degradation of microbial tank water quality and avian and possum feces. Based on the results, we recommend disinfection of tank water, especially for tanks designated for potable use.IMPORTANCEThe use of roof-harvested rainwater (RHRW) for domestic purposes is a globally accepted practice. The presence of pathogens in rainwater tanks has been reported by several studies, supporting the necessity for the management of potential health risks. The sources of fecal pollution in rainwater tanks are unknown. However, the application of microbial source tracking (MST) markers has the potential to identify the sources of fecal contamination in a rainwater tank. In this study, we provide evidence of avian and possum fecal contamination in tank water samples using molecular markers. This study established a potential link between the degradation of the microbial quality of tank water and avian and possum feces.

PRODUTIVIDADE DE CANA-DE-AÇÚCAR FERTIRRIGADA COM DOSES DE N E INOCULADAS COM BACTÉRIAS DIAZOTRÓFICAS* WILLIAM JOSÉ DELLABIGLIA¹; GLAUBER JOSÉ DE CASTRO GAVA²; ADOLFO BERGAMO ARLANCH3; ROBERTO LYRA VILLAS BOAS4; HEITOR CANTARELLA5 E RAFFAELLA ROSSETTO6 * Artigo extraído da Dissertação do primeiro autor 1 Faculdade de Tecnologia de Botucatu (FATEC-BT), Av. José Ítalo Bacchi, s/n, Botucatu – SP – Brasil. E-mail: williamd@fatecbt.edu.br 2 Pesquisador, Instituto Agronômico de Campinas (IAC), Rodovia SP 304, Km 304, Jaú, SP - Brasil. E-mail: ggava@iac.sp.gov.br 3 Doutorando do Programa de Pós-Graduação em Irrigação e Drenagem, Universidade Estadual Paulista ‘‘Júlio Mesquita Filho’’ - UNESP/FCA, Rua José Barbosa de Barros, 1780, Botucatu, SP - Brasil. E-mail: adolfoarlanch@gmail.com 4 Professor Doutor do Departamento de Recursos Naturais/Ciência do Solo, Universidade Estadual Paulista ‘‘Júlio Mesquita Filho’’ - UNESP/FCA, Rua José Barbosa de Barros, 1780, Botucatu, SP - Brasil. E-mail: rlvboas@fca.unesp.br 5 Pesquisador, Instituto Agronômico de Campinas (IAC), Av. Barão de Itapura, 1481, Campinas, SP – Brasil. E-mail: hcantrll@gmail.com 6 Pesquisadora, Agência Paulista de Tecnologia (APTA), Rodovia SP 127, km 30, Piracicaba, SP – Brasil. E-mail: raffaella@apta.sp.gov.br 1 RESUMO O objetivo deste trabalho foi avaliar a eficiência da inoculação de bactérias diazotróficas e da fertilização nitrogenada na produtividade e qualidade tecnológica da cana-de-açúcar (cana-planta), nos manejos: irrigado por gotejamento subsuperficial e de sequeiro. O experimento foi conduzido na Unidade de Pesquisa Hélio de Moraes, do IAC, no município de Jaú, SP, (22°17’ S 48°34’ O, em Latossolo Vermelho). A variedade de cana-de-açúcar foi a RB92579. O delineamento experimental foi em blocos casualizados, composto por fatorial de 2 manejos de irrigação: irrigado (I) e não irrigado (NI), 2 manejos de inoculação: com inoculação (Inoc) e sem inoculação (Não inoc) com bactérias diazotróficas (BDs); e com 4 níveis de disponibilidade de nitrogênio (0, 70, 140 e 210 kg ha-1 de N), compondo assim 16 tratamentos com 4 repetições. O experimento teve duração de 365 dias, quando então foram realizadas as análises tecnológicas e determinou-se a produtividade de colmos (TCH) e de açúcar (TPH). A cana-de-açúcar elevou sua produtividade com a elevação das doses de nitrogênio. Nos tratamentos irrigados essa elevação foi maior comparando-se com os tratamentos não irrigados. Palavras-chave: Saccharum spp.; gotejamento subsuperficial; adubação nitrogenada; fixação biológica do nitrogênio. DELLABIGLIA, W. J.; GAVA, G. J. C.; ARLANCH, A. B.; BOAS, R. L. V.; CANTARELLA, H.; ROSSETTO, R. SUGARCANE YIELD FERTIGATION MANAGEMENT WITH DOSES OF N AND INOCULATED WITH DIAZOTROPHIC BACTERIA 2 ABSTRACT The objective of this study was to evaluate the efficiency of inoculation with diazotrophic bacteria and nitrogen fertilization on yield and technological quality of sugarcane (cane plant), in the following managements: irrigated by subsurface drip and rainfed. The experiment was conducted at Hélio de Moraes Research Unit, of IAC in the municipality of Jaú, SP, (22 ° 17 'S 48 ° 34' O, Rhodic). The variety of sugarcane was RB92579. The experimental design was randomized blocks, composed by factorial of two irrigation management systems: irrigated (I) and non-irrigated (NI); and two-inoculation managements: with inoculation (Inoc) and without inoculation (No inoc) with diazotrophic bacterias (BDs); and 4 availability levels of nitrogen (0, 70, 140 and 210 kg ha-1 de N), thus forming 16 treatments with 4 replications. The experiment lasted 365 days when then technological analysis was performed and determined sugarcane stalk yield (TCH) and sugar yield (TPH). The sugarcane raised its productivity with rising nitrogen levels. In irrigated treatments this increase was higher compared with non-irrigated treatments. Keywords: Saccharum spp., subsurface drip, nitrogen fertilization, nitrogen biological fixation.

Drury, C. F., Reynolds, W. D., Tan, C. S., McLaughlin, N. B., Yang, X. M., Calder, W., Oloya, T. O. and Yang, J. Y. 2014. Impacts of 49–51 years of years of fertilization and crop rotation on growing season nitrous oxide emissions, nitrogen uptake and corn yields. Can. J. Soil Sci. 94: 421–433. A field study was established in 1959 to evaluate the effects of fertilization and crop rotation on crop yields, soil and environmental quality on a Brookston clay loam. There were two fertilizer treatments (fertilized and not-fertilized) and six cropping treatments including continuous corn (CC), continuous Kentucky bluegrass sod and a 4-yr rotation of corn–oat–alfalfa–alfalfa with each phase present each year. We measured N2O emissions, inorganic N and plant N uptake over three growing seasons (2007–2009) in the corn phase. Nitrous oxide emissions varied over the 3 yr as a result of the seasonal variation in precipitation quantity, intensity and timing and differences in crop growth and N uptake. Fertilized CC lost, on average, 7.36 kg N ha−1 by N2O emissions, whereas the not-fertilized CC lost only 0.51 kg N ha−1. Fertilized rotation corn (RC) lost 6.46 kg N ha−1, which was 12% lower than fertilized CC. The not-fertilized RC, on the other hand, emitted about half as much N2O (2.95 kg N ha−1) as the fertilized RC. Fertilized RC had corn grain yields that averaged 10.0 t ha−1 over the 3 yr followed by fertilized CC at 5.48 t ha−1. Not-fertilized RC corn had yields that were 61% lower (3.93 t ha−1) than fertilized RC, whereas the not-fertilized CC had yields that were 75% lower (1.39 t ha−1) than fertilized CC. Nitrous oxide emissions were found to be dramatically affected by long-term management practices and crop rotation had lower emissions in the corn phase of the rotation even though the N input from fertilizer addition and legume N fixation was greater. These N2O emission and yield results were due to both factors that are traditionally used to describe these processes as well as long-term soil quality factors, which were created by the long-term management (i.e., soil organic carbon, soil physical parameters such as bulk density, and porosity, soil fauna and micro-flora) and that influenced crop growth, N uptake and soil water contents.

The effects of biochar and biochar combined with N-fertilizer on the content of soil organic matter in water-stable aggregates were investigated. A field experiment was conducted with different biochar application rates: B0 control (0 t ha-1), B10 (10 t ha-1) and B20 (20 t ha-1) and 0 (no N), 1st and 2nd levels of nitrogen fertilization on silt loam Haplic Luvisol (Dolna Malanta, Slovakia), in 2014. The N doses of level 1 were calculated on required average crop production using balance method. Level 2 included additional 100% of N in year 2014 and additional 50% of N in year 2016. The effects were investigated during the growing seasons of spring barley and spring wheat in 2014 and 2016, respectively. Results indicate that the B20N2 treatment significantly increased the proportion of water-stable macro-aggregates (WSAma) and reduced water-stable micro-aggregates (WSAmi). Aggregate stability increased only in the B20N1 treatment. The B20N2 treatment showed a robust decrease by 27% in the WSAma of 0.5-0.25 mm. On the other hand, an increase by 56% was observed in the content of WSAma with fractions 3-2 mm compared to the B0N0 treatment. The effect of N fertilizer on WSAma was confirmed only in the case of the B10N2 treatment. The proportion of WSAma with fractions 3-2 mm decreased by 42%, while the size fraction of 0.5-0.25 mm increased by 30% compared to the B10N0 treatment. The content of WSAma with fractions 1-0.5 mm decreased with time. On the contrary, the content of WSAma with particle sizes above 5 mm increased with time in all treatments except the B10N2 and B20N2 treatments. A statistically significant trend was identified in the proportion of WSA in the B10N2 and B20N2 treatments, which indicates that biochar with higher application levels of N fertilizer stabilizes the proportion of water-stable aggregates. In all treatments, the content of soil organic carbon (SOC) and labile carbon (CL) in WSAmi was lower than those in WSAma. A considerable decrease of SOC in the WSAma >5 mm and an increase of SOC in WSAmi were observed when biochar was applied at the rate of 10 t ha-1. Contents of SOC in WSAmi increased as a result of adding biochar combined with N fertilizer at first level. CL in WSA significantly increased in all size fractions of WSA.References Abiven S., Hund A., Martinsen V., Cornelissen G., 2015. Biochar amendment increases maize root surface areas and branching: a shovelomics study in Zambia. Plant Soil, 342, 1-11. Agegnehu G., Bass A.M., Nelson P.N., and Bird M.I., 2016. Benefits of biochar, compost and biochar–compost for soil quality, maize yield and greenhouse gas emissions in a tropical agricultural soil. Sci. Tot. Environ., 543, 295-306. Angers D.A., Samson N., Legere A., 1993. 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Effects of biochar on soil properties and erosion potential in a highly weathered soil. Catena, 110, 225-233. Kammann C., Linsel S., Goßling J., Koyro H.W., 2011. Influence of biochar on drought tolerance of Chenopodium quinoa Willd and on soil-plant relations. Plant Soil, 345, 195-210. Kodesova R., Nemecek K., Zigova A., Nikodem A., Fer M., 2015. Using dye tracer for visualizing roots I pact on soil structure and soil porous system. Biologia, 70, 1439-1443. Krol, A., Lipiec, J., Turski, M., J. Kuoe, 2013. Effects of organic and conventional management on physical properties of soil aggregates. Int. Agrophys., 27, 15-21. Kurakov A.V., Kharin S.A., 2012. The Formation of Water-Stable Coprolite Aggregates in Soddy-Podzolic Soils and the Participation of Fungi in This Process. Eur. Soil Sci., 45, 429-434. Loginow W., Wisniewski W., Gonet S.S., Ciescinska B., 1987. Fractionation of organic carbon based on susceptibility to oxidation. Pol. J. Soil Sci., 20, 47-52. Lynch, J.M., and E. 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The current state of centralized nitrogen (N) management has destabilized global environmental cycles via Haber-Bosch (HB) ammonia-N manufacturing which contributes 1.2% of global anthropogenic CO2-eq emissions.1 The majority of this N that is discharged to wastewaters goes untreated, leading to harmful algal blooms that threaten coastal and river ecosystems, which already costs the U.S. an estimated $210 billion per year in health and environmental damages.2 Furthermore, the production of HB ammonia, and the subsequent discharge of wastewater nitrogen, is expected to substantially increase in the next three decades as the human population climbs to 9 billion people.3 Simultaneously removing nitrogen pollutants and recovering value-added products can preserve national water quality and supplement supply chains of nitrogen consumables with renewably sourced electricity. The electrochemical nitrate reduction reaction (NO3RR) can be leveraged in reactive separation processes to convert wastewater nitrates to commodity products, such as ammonia. Engineering catalytic NO3RR processes that operate at feasible rates and faradaic efficiencies is challenging because the majority of nitrate-rich wastewaters (e.g., fertilizer runoff) are dilute in nitrate concentration (< 5 mM).4 Molecular catalysts are uniquely suited to reduce nitrate at low concentrations in real wastewaters due to their strong substrate recognition (reactant selectivity) and product selectivity. In this study, we benchmarked the performance of the molecular catalyst Co-DIM (a Co-N4 macrocycle complex and the only known molecular NO3RR catalyst selective for ammonia5) in a reactive separations process for the treatment of real, nitrate-rich wastewaters. We first demonstrated by cyclic voltammetry (CV) and controlled-potential electrolysis (CPE) that selective Co-DIM-mediated NO3RR is feasible in nitrate-rich secondary effluent (municipal wastewater after biological nitrification). We then employed Co-DIM in electrochemical stripping (ECS): a membrane-separated cell that facilitates reactive separation of produced ammonia.6,7 From real secondary effluent (28 mg NO3-N/L), we achieved greater than 60% nitrate removal with a faradaic efficiency of 25% and ammonia selectivity of 98%. However, the energy consumed for ECS per unit mass of N is 16 times the combined energy requirement for conventional wastewater N removal and HB ammonia synthesis. By introducing a mixed feed of ammonia- and nitrate-rich wastewater and performing electrodialysis (ED) to concentrate the reactant nitrate before ECS, the energy requirement for N removal and ammonia recovery was decreased by three times while the ED process became the dominant energy consumer in the overall process. Additionally, the increase in nitrate removal could not be explained by an increase in nitrate concentration alone. The ED process changes the concentrations and relative ratios of competing anions and buffering species, which can inhibit or promote the molecular electrocatalytic activity. We therefore explored a matrix of anion identities and concentrations by rotating-disk voltammetry and CPE to elucidate plausible inhibition and promotion mechanisms associated with catalyst activation and NO3RR catalysis. This study therefore (1) benchmarks current and future efforts to reactively separate ammonia from real nitrate-rich wastewater with a molecular catalyst and (2) highlights molecular and process-level improvements to realize a circular nitrogen economy. References 1 C. Smith, A. K. Hill and L. Torrente-Murciano, Energy Environ. Sci., 2020, 13, 331–344. 2 D. J. Sobota, J. E. Compton, M. L. McCrackin and S. Singh, Environ. Res. Lett., 2015, 10, 025006. 3 J. W. Erisman, M. A. Sutton, J. Galloway, Z. Klimont and W. Winiwarter, Nature Geoscience, 2008, 1, 636–639. 4 Unesco, Ed., Wastewater: the untapped resource, UNESCO, Paris, 2017. 5 S. Xu, D. C. Ashley, H.-Y. Kwon, G. R. Ware, C.-H. Chen, Y. Losovyj, X. Gao, E. Jakubikova and J. M. Smith, Chem. Sci., 2018, 9, 4950–4958. 6 W. A. Tarpeh, J. M. Barazesh, T. Y. Cath and K. L. Nelson, Environ. Sci. Technol., 2018, 52, 1453–1460. 7 M. J. Liu, B. S. Neo and W. A. Tarpeh, Water Research, 2020, 169, 115226.

The production and demand of tilapia (O. niloticus) in some countries continue to increase but are not matched by good growth quality. Several methods have been used to increase growth, such as the use of synthetic hormones and radiation, however, the methods require such a high cost. Thus it needs to be investigated the potential replacement with natural prooduct. Papaya leaf contains papain enzyme thought to be able to improve the growth performance of fish body weight through the conversion of proteins into amino acids. The purpose of this study was to investigate the growth performance of tilapia (O. niloticus) fish that were given papaya meal (C. papaya) treatments. The concentrations pellet with papaya meal respectively T1(feed with 0 grams of papaya leaf meal), T2 (administration of papaya leaf meal with 1.25 g/kg feed), T3 (administration of papaya leaf meal with 1.75 g/kg feed), T4 (administration of papaya leaf meal with 2 g/kg feed), T5 (administration of papaya leaf meal with 2.25 g/kg feed). Parameters analyzed included: absolute length growth, absolute weight, specific growth rate, FCR survival rate and, water quality. The results showed that the highest weight growth of tilapia fed with the administration of papaya leaf meal was found at T4 of 21.23 grams. In the specific weight, the optimal treatment was found in T4 with a percentage of 20.97%. In the length growth of tilapia, it was known that the T1, T4 and T5 had highest lengths when compared to other treatments and the highest survival rate of tilapia (O. niloticus) was in the T2, T3, T5 treatments of 73%. The optimal FCR value was found in the T4 treatment of 1.14. 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Pengaruh Activator Sistein dan Natrium Klorida Terhadap Aktivitas Papain. Jurnal Sains Kimia, 8 (1). 26-28Effendi, M. I. (2002). Biologi Perikanan. Cetakan Kedua. Yayasan Pustaka Nusantara, Yogyakarta:Effendi, M. I. (2003). Telaah Kualitas Air. Kanisius: Yogyakarta. 'Haetami, K., Junianto. & Andriani, Y. (2005). Tingkat Penggunaan Gulma Air Azolla pinnata dalam Ransum Terhadap Pertumbuhan dan Konversi Pakan Ikan Bawal Air Tawar. Laporan Penelitian. Universitas Padjadjaran, JatinangorHandajani, H. & W. Widodo. (2010). Nutrisi Ikan. Malang: UMM Press. Irawati, D., Rachmawati, D. & Pinandoyo. (2015). Performa Pertumbuhan Benih Ikan Nila Hitam (Oreochromis niloticus bleeker) Melalui Penambahan Enzim Papain dalam Pakan Buatan. Journal of Aquaculture Management Technology, 4 (1). 1-9.Isnawati, N., Sidik, R. & Mahasri, G. (2015). Potensi Serbuk Daun Pepaya untuk Meningkatkan Efisiensi Pemanfaatan Pakan, Rasio Efisiensi Protein Dan Laju Pertumbuhan Pada Budidaya Ikan Nila (Oreochromis niloticus). Jurnal Ilmiah Perikanan dan Kelautan, 7(2).Mareta, E. R., Subandiyono, & Hastuti, S. (2016). Pengaruh Enzim Papain dan Probiotik dalam Pakan Terhadap Tingkat Efisiensi Pemanfaatan Pakan dan Pertumbuhan Ikan Gurami (Osphronemus gouramy). Jurnal Sains Akuakultur Tropis, 1 (1):21-30.Murjani, A. (2011). Budidaya Beberapa Varietas Ikan Sepat Rawa (Trichogaster Trichopterus Pall) Dengan Pemberian Pakan Komersial. Jurnal Fish Scientiae, 1 (2): 214-133.Prakoso, T. (2014). Pengaruh Suhu yang Berbeda Terhadap Laju Pertumbuhan Benih Ikan Gurami (Osphronemus gouramy lac) didalam Akuarium. Skripsi. Program Studi Budidaya Perairan, Fakultas Pertanian, Universitas Antakusuma. Riyanti. A., Susanto. A. & Sukarti, K. (2014). Penambahan Tepung Buah Pepaya (Carica papaya). Dalam Pakan Terhadap Pertumbuhan dan Efesiensi Pakan Pada Ikan Nila Gift (Oreochromis sp) Ukuran 3-5 cm. Jurnal Ilmu Perikanan Tropis, 30 (1). 60-67Robinette, H. R. (1976). Effect of Sublethal of Ammonia on the Growth of Channel Catfish (Ictalarus punctatus R). Frog. Journal Fish Culture, 38 (1). 26-29Rukisah., Simanjuntak, R. F. & Anugrah, W. (2021). Pengaruh Pemberian Pakan Buatan dari Kombinasi Tepung Cacing Tanah (Lumbricus rubellus) dan Tepung Daun Pepaya Terhadap Pertumbuhan Ikan Nila. Jurnal Harpodon Borneo, 14 (1). 39-46Rukmana, H. R. (1997). Ikan Nila Budidaya dan Prospek Agribisnis. Yogyakarta: Kanisius.Sagita, F., Rachmawati, D. & Suminto. (2017). Pengaruh Penambahan Enzim Papain Pada Pakan Komersial Terhadap Efisiensi Pemanfaatan Pakan, Laju Pertumbuhan,Kelulushidupan Ikan Sidat (Anguilla bicolor). Journal of Aquaculture Management and Technology, 6(4). 77-84.Salsabila, M. & Suprapto, H. (2018). Teknik Pembesaran Ikan nila (Oreochromis niloticus) di Instalasi Budidaya Air Tawar Pandaan, Jawa Timus. Journal of Aquaculture and Fish Health, 7(3). 118-123Simanjuntak, R. F., Abdiani, I. M. & Verawati. (2018). Bioenrichment Tepung Pepaya (Carica Papaya) dengan Formulasi Pakan yang Berbeda pada Performa Pertumbuhan Ikan Nila (Oreochromis niloticus). Jurnal Harpodon Borneo, 11 (2). 59-68.Simanjuntak, R. F. & Ridwansyah. (2020). Membangung Keterampilan Mahasiswa Perbatasan Kaltara Melalui teknologi dan Manajemen Pembuatan Pakan Ikan Pada Masa Pancemi dan Pasca Covid-19. Jurnal Pengabdian Masyarakat Borneo, 4 (2). 143-150SNI 7550.2009. (2009). Produksi Ikan Nila (Oreochromis niloticus Bleeker) Kelas Pembesaran di Kolam Air Tenang. Badan Standardisasi nasional. JakartaSulasi, S., Hastuti, S. & Subandiyono, S. (2018). Pengaruh Enzim Papain dan Probiotik pada Pakan Buatan terhadap Pemanfaatan Protein Pakan dan Pertumbuhan Ikan Mas (Cyprinus Carpio). Sains Akuakultur Tropis : Indonesian Journal of Tropical Aquaculture, 2 ()1, Zonneveld, N., Huisman E. A. & Boon, J. H. (1991). Prinsip-Prinsip Budidaya Ikan. Jakarta: Gramedia Pustaka Utama.

Terroir factors and vineyard practices largely determine canopy and root system functioning. In this study, changes in soil conditions, multi-level (vertical, horizontal) light interception (quantitative, photographic, schematic, 3D modelled), leaf water potential and photosynthetic activity were measured during the grape ripening period on NS, EW, NE-SW, and NW-SE orientated (Southern Hemisphere) vertically trellised Shiraz grapevine canopies. It was hypothesised that the spatial radiation interception angle and radiation distribution of differently orientated and vertically trained grapevine rows would affect soil conditions and vine physiological activity. Soil water content showed an increase and soil temperature a decreasing gradient with soil depth. In the afternoon, soil layers of EW orientated rows reached their highest temperature. This, along with measured photosynthetic active radiation received by canopies, complimented the diurnally-captured photographic, constructed and 3D modelled images (also schematically) of canopy and soil exposure patterns. The top, bottom and outside of NS canopies mainly received radiation from directly above, from the E and the W; during midday, high radiation was only received from above. The EW rows received the highest radiation component from above and from the N. The NE-SW rows received high levels of radiation from above, from the SE until 10:00, and from the NW from 13:00. A similar profile can be described for NW-SE rows, but with high radiation received from the NE up to 13:00 and from the SW from 16:00. Overall, lowest leaf water potential occurred for NE-SW canopies, followed by those orientated NW-SE, NS and EW. Photosynthetic activity reflected the positive radiation impact of the sun azimuth during the grape ripening period; best overall performance seemed to occur for E and N exposed canopy sides. This was largely driven by the responsiveness of the secondary leaves to radiation. Photosynthetic output decreased from apical to basal canopy zones with low, erratic values in the light-limited canopy centre. The NS and EW orientated canopies generally showed the highest average photosynthesis, while it was lower for the sides facing S, SE and SW. The results provide a better understanding of the physiological functioning of horizontal and vertical leaf layers in differently orientated grapevine canopies, as affected by climatic conditions. The study contributes to the longstanding challenges of capturing the complexity of parallel microclimatic and physiological output of grapevine canopies under open field conditions. The results can be directly applied to the selection of vineyard practices and seasonal management to ensure the attainment of yield, grape composition and wine quality objectives.

This technical note summarizes a technical comparison of common testing procedures, as well as reviewed of the UN Test N` 5, for the assessment of the self-heating properties of cargoes and materials that has shown a clear trend on maritime fire and explosions events, as well as considering of external factors that can combine self-heating and emit flammable gases to conclude in an unlikely event affecting the security of crews and ships. A high understanding of the external factors effect on the cargo materials certainly will help the application of spontaneous reactions management actions (SRMA) on board of ships during the cargo sea passage. The intended comparison is based on laboratory, industry and field observations and data, whereas the among the external factors considered are, moisture content, stockpile procedure and aging, air velocities and moderate pressures internal and externally to the cargo material. The comparison results have shown that the self-heating and the flammable gas emissions has a common pattern when reacting with any oxygen available source, regardless the reactive material chemical composition. Keywords: reactive materials, self-heating, self-ignition, direct reduced iron fines, materials handling, UN test N` 5, maritime safety, spontaneous reactions, risk management. IMSBC Code , IMO. References [1]A. M. DeGennaro, M. W. Lohry, L. Martinelli, C. W. Rowley. Uncertainty Quantification for Cargo Hold Fires. Princeton University, Princeton, NJ, 08540, USA. American Institute of Aeronautics and Astronautics. [2]L.L.Sloss Assessing and Managing Spontaneous Combustion of Coals. IEA Clean Coal Center (CCC 259). Oct. 2015. [3].A. Janes, G Marlair, D Carson, j. Chaneausx. Towards the improvement of UN Test N1 5 Method for the characterization of substances which in contact with water emit Flammable Gases. Journal of Loss Prevention in the Process Industries. Elsevier 2012, 25 (3), pp 524-534. [4]G. Rouget, B. Majidi, D. Picard, G. Gauvin, D. Ziegler, J. Mashreghi, and H. Alamdar. Electrical Resistivity Measurement of Petroleum Coke Powder by Means of Four-Probe Method. Metallurgical and Materials Transactions B. Vol. 48B, Oct. 2017-2543. [5]Y. Rubiela Hernández Puerto, M.Triviño Restrepo. El coque metalúrgico aplicado a protección catódica (Metallurgia coque applied to catodic protection). Revista del Instituto de Investigaciones FIGMMG. Vol. 10, Nº 20, 60-67 (2007) UNMSM I. [6]S. Narayan Jha, K. Narsaiah, A.L. Basediya, R.Sharma, P. Jaiswal, R. Kumar, and R. Bhardwaj. Measurement techniques and application of electrical properties for nondestructive quality evaluation of foods—a review. Food Sci Technol. 2011 Aug; 48(4): 387–411. [7]R. Fontes Araujo, J. Batisa Zonta, E. Fontes Araujo, E. Heberle, E, F. Miranda Garcia Zonta. Teste de Conductividade Eletrica para Smentes de Feijao Mungo Verde 1. Rev. Brasikleira de Sementes, Vol. 33, N` 1, pp123/130, 2011. [8]P.A. Eidem. Electric Resistivity of Coke Beds. PhD Thesis. Norwegian University of Science and Technology Faculty of Natural Sciences and Technology Department of Materials Science and Engineering. Tronheim Oct. 2008. [9]N. Birks, et.al. - Mechanism in Corrosion Induced Auto-ignition of Direct Reduced Iron. Materials Science and Engineering Department, University of Pittsburgh. [10]Monitoring Implementation of the Hazardous and Noxious Substances Convention. Report on incidents involving HNS. Submitted by the United Kingdom. IMO 85th Session, Agenda item 5- LEG 85/INF.2, 19 September 2002.

This study aim to attempt mapping out the Land Use or Land Cover (LULC) status of Regional Project Coordination Committee (RPCC) between 2009-2019 with a view of detecting the land consumption rate and the changes that has taken place using RS and GIS techniques; serving as a precursor to the further study on urban induced variations or change in weather pattern of the cityn Rangpur City Corporation(RCC) is the main administrative functional area for both of Rangpur City and Rangpur division and experiencing a rapid changes in the field of urban sprawl, cultural and physical landscape,city growth. These agents of Land use or Land cover (LULC) varieties are responsible for multi-dimensional problems such as traffic congestion, waterlogging, and solid waste disposal, loss of agricultural land. In this regard, this study fulfills LULC changes by using Geographical Information Systems (GIS) and Remote Sensing (RS) as well as field survey was conducted for the measurement of change detection. The sources of data were Landsat 7 ETM and landsat 8 OLI/TIRS of both C1 level 1. Then after correcting the data, geometrically and radiometrically change detection and combined classification (supervised & unsupervised) were used. The study finds LULC changes built-up area, water source, agricultural land, bare soil in a change of percentage is 17.23, 2.58, -9.94, -10.19 respectively between 2009 and 2019. Among these changes, bare soil is changed to a great extent, which indicates the expansion of urban areas is utilizing the land to a proper extent. Keywords: Urban expansion; land use; land cover; remote sensing; geographic information system (GIS); Rangpur City Corporation(RCC). References Al Rifat, S. A., & Liu, W. (2019). Quantifying spatiotemporal patterns and major explanatory factors of urban expansion in miami metropolitan area during 1992-2016. Remote Sensing, 11(21) doi:10.3390/rs11212493 Arimoro AO, Fagbeja MA, Eedy W. (2002). The Need and Use of Geographic Information Systems for Environmental Impact Assessment in Africa: With Example from Ten Years Experience in Nigeria. AJEAM/RAGEE, 4(2), 16-27. Belal, A.A. and Moghanm, F.S. (2011).Detecting Urban Growth Using Remote Sensing and GIS Techniques in Al Gharbiya Governorate, Egypt.The Egyptian Journal of Remote Sensing and Space Science, 14, 73-79. http://dx.doi.org/10.1016/j.ejrs.2011.09.001 Dewan, A.M. and Yamaguchi, Y. (2009). Using Remote Sensing and GIS to Detect and Monitor and Use and Land Cover Change in Dhaka Metropolitan of Bangladesh during 1960-2005. Environmental Monitor Assessment, 150, 237- 249. Retrieved from http://dx.doi.org/10.1007/s10661-008-0226-5 Djimadoumngar, K.-N., & Adegoke, J. (2018). Satellite-Based Assessment of Land Use and Land Cover (LULC) Changes around Lake Fitri, Republic of Chad. Journal of Sustainable Development, 11(5), 71. doi:10.5539/jsd.v11n5p71 Edwards, B., Frasch, T., & Jeyacheya, J. (2019). Evaluating the effectiveness of land-use zoning for the protection of built heritage in the bagan archaeological zone, Myanmar—A satellite remote-sensing approach. Land use Policy, 88 doi:10.1016/j.landusepol.2019.104174 Fallati, L., Savini, A., Sterlacchini, S., & Galli, P. (2017). Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data. Environmental Monitoring and Assessment, 189(8). doi:10.1007/s10661-017-6120-2 Fučík, P., Novák, P., & Žížala, D. (2014). A combined statistical approach for evaluation of the effects of land use, agricultural and urban activities on stream water chemistry in small tile-drained catchments of south bohemia, czech republic. Environmental Earth Sciences, 72(6), 2195-2216. doi:10.1007/s12665-014-3131-y Elbeih, S. F., & El-Zeiny, A. M. (2018). Qualitative assessment of groundwater quality based on land use spectral retrieved indices: Case study sohag governorate, egypt. Remote Sensing Applications: Society and Environment, 10, 82-92. doi:10.1016/j.rsase.2018.03.001 Fasal, S. (2000). Urban expansion and loss of agricultural land – A GIS based study of Saharanpur City, India. Environment and Urbanization, 12(2), 133 – 149 He, S., Wang, X., Dong, J., Wei, B., Duan, H., Jiao, J., & Xie, Y. (2019). Three-dimensional urban expansion analysis of valley-type cities: A case study of chengguan district, lanzhou, china. Sustainability (Switzerland), 11(20) doi:10.3390/su11205663 Heimlich, R.E and W.D. Anderson. (2001). Development at the Urban Fringe and Beyond: Impacts on Agriculture and Rural Land. 803, Economic Research Service, U.S. Department of Agriculture, Washington D.C., pg 80 Im, N., Kawamura, K., Suwandana, E., & Sakuno, Y. (2014). Monitoring land use and land cover effects on water quality in cheung ek lake using ASTER images. American Journal of Environmental Sciences, 11(1), 1-12. doi:10.3844/ajessp.2015.1.12 Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423(6939), 528-531. doi:10.1038/nature01675 Matlhodi, B., Kenabatho, P. K., Parida, B. P., & Maphanyane, J. G. (2019). Evaluating land use and land cover change in the gaborone dam catchment, botswana, from 1984-2015 using GIS and remote sensing. Sustainability (Switzerland), 11(19) doi:10.3390/su11195174 Uddin, M. M. M. (2015). Causal relationship between agriculture, industry and services sector for GDP growth in Bangladesh: An econometric investigation. Journal of Poverty, Investment and Development, 8. Mondal, I., Srivastava, V. K., Roy, P. S., & Talukdar, G. (2014). Using logit model to identify the drivers of landuse landcover change in the lower gangetic basin, india. Paper presented at the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, , XL-8(1) 853-859. doi:10.5194/isprsarchives-XL-8-853-2014 Navale, V. B., & Mhaske, S. Y. (2019). Land use/land cover changes in sangamner city by using remote sensing and GIS. International Journal of Recent Technology and Engineering, 8(2), 4614-4621. doi:10.35940/ijrte.B3386.078219 Nicolson, L.D. (1987). The Greening of the cities; Routledge and Kegan Paul, London Nong, D., Fox, J., Miura, T., & Saksena, S. (2015). Built-up Area Change Analysis in Hanoi Using Support Vector Machine Classification of Landsat Multi-Temporal Image Stacks and Population Data. Land, 4(4), 1213–1231. doi:10.3390/land4041213 Park, H., Fan, P., John, R., Ouyang, Z., & Chen, J. (2019). Spatiotemporal changes of informal settlements: Ger districts in ulaanbaatar, mongolia. Landscape and Urban Planning, 191 doi:10.1016/j.landurbplan.2019.103630 Rajeshwari D. (2006). Management of the Urban Environment Using Remote Sensing and Geographic Information Systems.J. Hum. Ecol., 20(4), 269-277. Retrieved from http://www.krepublishers.com/02_journals/JHE/ Rasul, A., Balzter, H., Ibrahim, G., Hameed, H., Wheeler, J., Adamu, B., … Najmaddin, P. (2018). Applying Built-Up and Bare-Soil Indices from Landsat 8 to Cities in Dry Climates. Land, 7(3), 81. doi:10.3390/land7030081 Risma, Zubair, H., & Paharuddin. (2019). Prediction of land use and land cover (LULC) changes using CA-Markov model in Mamuju Subdistrict. Journal of Physics: Conference Series, 1341, 082033. doi:10.1088/1742-6596/1341/8/082033 Schilling, K. E., Jha, M. K., Zhang, Y.-K., Gassman, P. W., & Wolter, C. F. (2008). Impact of land use and land cover change on the water balance of a large agricultural watershed: Historical effects and future directions. Water Resources Research, 44(7). doi:10.1029/2007wr006644 Copyright (c) 2019 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

The experiment was conducted in the Agronomy Field, Sher-e-Bangla Agricultural University (SAU), Dhaka-1207 during the period of November 17, 2016 to March 29, 2017 on growth and yield performance of selected wheat genotypes at variable irrigation. In this experiment, the treatment consisted of three varieties viz. V1 = BARI Gom 26, V2 = BARI Gom 28, V3 = BARI Gom 30, and four different irrigations viz. I0 = No Irrigation throughout the growing season, I1 = One irrigation (Irrigate at CRI stage), I2= Two irrigation (Irrigate at CRI and grain filling), I3= Three irrigation (irrigate at CRI, booting and grain filling stages). The experiment was laid out in two factors split plot with three replications. The collected data were statistically analyzed for evaluation of the treatment effect. Results showed that a significant variation among the treatments in respect majority of the observed parameters. Results showed significant variation in almost every parameter of treatments. The highest Plant height, number of effective tillers hill-1, spike length, number of grain spike-1 was obtained from BARI Gom-30. The highest grain weight hectare-1 (3.44 ton) was found from wheat variety BARI Gom-30. All parameters of wheat showed statistically significant variation due to variation of irrigation. The maximum value of growth, yield contributing characters, seed yield was observed with three irrigation (irrigate at CRI, booting and grain filling stages). The interaction between different levels of variety and irrigation was significantly influenced on almost all growth and yield contributing characters, seed yield. The highest yield (3.99 t ha-1) was obtained from BARI Gom-30 with three irrigation (irrigate at CRI, booting and grain filling stages). The optimum growth and higher yield of wheat cv. BARI Gom-30 could be obtained by applying three irrigations at CRI, booting and grain filling stages. Introduction Wheat (Triticumaestivum L.) is one of the most important cereal crops cultivated all over the world. Wheat production was increased from 585,691 thousand tons in 2000 to 713,183 thousand tons in 2013 which was ranked below rice and maize in case of production (FAO, 2015). In the developing world, need for wheat will be increased 60 % by 2050 (Rosegrant and Agcaoili, 2010). The International Food Policy Research Institute projections revealed that world demand for wheat will increase from 552 million tons in 1993 to 775 million tons by 2020 (Rosegrantet al.,1997). Wheat grain is the main staple food for about two third of the total population of the world. (Hanson et al., 1982). It supplies more nutrients compared with other food crops. Wheat grain is rich in food value containing 12% protein, 1.72% fat, 69.60% carbohydrate and 27.20% minerals (BARI, 2006). It is the second most important cereal crop after rice in Bangladesh. So, it is imperative to increase the production of wheat to meet the food requirement of vast population of Bangladesh that will secure food security. During 2013-14 the cultivated area of wheat was 429607 ha having a total production of 1302998 metric tons with an average yield of 3.033 metric tons ha-1whereas during 2012-13 the cultivated area of wheat was 416522 ha having a total production of 1254778 metric tons with an average yield of 3.013 tons ha-1 (BBS, 2014). Current demand of wheat in the country is 3.0-3.5 million tons. Increasing rate of consumption of wheat is 3% per year (BBS, 2013). Wheat production is about 1.0 milllion from 0.40 million hectares of land. Bangladesh has to import about 2.0-2.5-million-ton wheat every year. Wheat is grown all over Bangladesh but wheat grows more in Dhaka, Faridpur, Mymensingh, Rangpur, Dinajpur, Comilla districts. Wheat has the umpteen potentialities in yield among other crops grown in Bangladesh. However, yield per hectare of wheat in Bangladesh is lower than other wheat growing countries in the world due to various problems. Increasing food production of the country in the next 20 years to much population growth is a big challenge in Bangladesh. It is more difficult because, land area devoted to agriculture will decline and better-quality land and water resources will be divided to the other sector of national economy. In order to grow more food from marginal and good quality lands, the quality of natural resources like seed, water, varieties and fuel must be improved and sustained. Variety plays an important role in producing high yield of wheat because different varieties responded differently for their genotypic characters, input requirement, growth process and the prevailing environment during growing season. In Bangladesh the wheat growing season (November-March) is in the driest period of the year. Wheat yield was declined by 50% owing to soil moisture stress. Irrigation water should be applied in different critical stages of wheat for successful wheat production. Shoot dry weight, number of grains, grain yield, biological yield and harvest index decreased to a greater extent when water stress was imposed at the anthesis stage while water stress was imposed at booting stage caused a greater reduction in plant height and number of tillers (Gupta et al., 2001). Determination of accurate amount of water reduces irrigation cost as well as checks ground water waste. Water requirements vary depending on the stages of development. The pick requirement is at crown root initiation stage (CRI). In wheat, irrigation has been recommended at CRI, flowering and grain filling stages. However, the amount of irrigation water is shrinking day by day in Bangladesh which may be attributed to filling of pond river bottom. Moreover, global climate change scenarios are also responsible for their scarcity of irrigation water. So, it is essential to estimate water saving technique to have an economic estimate of irrigation water. Information on the amount of irrigation water as well as the precise sowing time of wheat with change in climate to expedite wheat production within the farmer’s limited resources is inadequate in Bangladesh. The need of water requirement also varies with sowing times as the soil moisture depletes with the days after sowing in Bangladesh as there is scanty rainfall after sowing season of wheat in general in the month of November. With above considerations, the present research work was conducted with the following objectives: To evaluate yield performance of selected wheat genotypes(s) at variable irrigation management. To identify the suitable genotype (s) of wheat giving higher yield under moisture stress condition. Materials and Methods Description of the experimental site The experiment was conducted in the Research Field, Sher-e-Bangla Agricultural University (SAU), Dhaka-1207 during the period of November, 2016 to March, 2017 to observe the growth and yield performance of selected wheat genotypes at variable irrigation management. The experimental field is located at 23041´ N latitude and 90º 22´ E longitude at a height of 8.6 m above the sea level belonging to the Agro-ecological Zone “AEZ-28” of Madhupur Tract (BBS, 2013). Soil characteristics The soil of the research field is slightly acidic in reaction with low organic matter content. The selected plot was above flood level and sufficient sunshine was available having available irrigation and drainage system during the experimental period. Soil samples from 0-15 cm depths were collected from experimental field. The experimental plot was also high land, having pH 5.56. Climate condition The experimental field was situated under sub-tropical climate; usually the rainfall is heavy during Kharifseason, (April to September) and scanty in Rabi season (October to March). In Rabi season temperature is generally low and there is plenty of sunshine. The temperature tends to increase from February as the season proceeds towards kharif. Rainfall was almost nil during the period from November 2016 to March 2017 and scanty from February to September. Planting material The test crop was wheat (Triticumaestivum). Three wheat varieties BARI Gom-26, BARI Gom-28 and BARI Gom-30 were used as test crop and were collected from Bangladesh Agricultural Research Institute (BARI), Joydebpur, Gazipur. Treatments The experiment consisted of two factors and those were the wheat genotypes and irrigation. Three wheat genotypes and four irrigations were used under the present study. Factor A: three wheat varieties- V1 = BARI Gom-26, V2 = BARI Gom-28 and V3= BARI Gom-30. Factor B: four irrigations- I0 = No Irrigation throughout the growing season, I1 = One irrigation (Irrigate at CRI stage), I2= Two irrigation (Irrigate at CRI and grain filling) and I3= Three irrigation (Irrigate at CRI, booting and grain filling stages). The experiment was laid out in a split plot design with three replications having irrigation application in the main plots, verities in the sub plots. There were 12 treatments combinations. The total numbers of unit plots were 36. The size of unit plot was 2 m x 2 m = 4.00 m2. The distances between sub-plot to sub-plot, main plot to main plot and replication to replication were, 0.75, 0.75 and 1.5 m, respectively. Statistical analysis The collected data on each plot were statistically analyzed to obtain the level of significance using the computer-based software MSTAT-C developed by Gomez and Gomez, 1984. Mean difference among the treatments were tested with the least significant difference (LSD) test at 5 % level of significance. Results and Discussion Plant height Plant height varied significantly among the tested three varieties (Table 1). At, 75 DAS, BARI Gom 30 showed the tallest plant height (34.72 cm) and BARI Gom 26 recorded the shortest plant height (32.32 cm). At, 90 DAS, BARI Gom 30 recorded the highest plant height (76.13 cm) was observed from BARI Gom 26. However, BARI Gom 26 recorded the shortest plant height (75.01 cm) which was also statistically similar with BARI Gom 28. Islam and Jahiruddin (2008) also concluded that plant height varied significantly due to various wheat varieties. Plant height of wheat showed statistically significant variation due to amount of irrigation at 75, 90 DAS under the present trial (Table 2). At 75 DAS, the tallest plant (34.78 cm) was recorded from I3 (Three irrigation) while the shortest plant (32.02 cm) was observed from I0 (No Irrigation throughout the growing season) treatment. At 60 DAS, the tallest plant (77.51 cm) was found from I3, which was statistically similar with I2 (Two irrigation) and I1 (One irrigation). The shortest plant (71.29 cm) was observed from I0. Plant height was likely increased due to applying higher amount of irrigation compared to less amount of irrigation. Sultana (2013) stated that increasing water stress declined the plant height. Interaction effect of variety and different amount of irrigation showed significant differences on plant height of wheat at 75 and 90 DAS (Table 3). The highest plant height at 30 was 38.00 cm obtained from V3I3 treatment combination. The shortest plant height at 30 was 30.67 cm obtained from V1I0 treatment combination. At 60 DAS, plant height was 78.50 cm obtained from V3I3 and lowest was 69.83 cm obtained from V1I0 treatment combination, which was statistically similar with V2I0 and 3I0 treatment combination. Table 1. Effect of variety on plant height of wheat at different days after sowing Table 2. Effect of irrigation on plant height of wheat at different days after sowing Table 3. Interaction effect of variety and irrigation on plant height of wheat Number of effective tiller hill-1 Number of effective tillers hill-1of wheat was not varied significantly due to varieties (Table 4). BARI Gom 30 produced the highest number of effective tillers hill-1 (9.33) and the lowest number of effective tillers hill-1(8.58) was observed in BARI Gom 26. Different levels of irrigation varied significantly in terms of number of effective tillers hill-1 of wheat at harvest under the present trial (Table 5). The highest number of effective tillers hill-1 9.89 was recorded from I3 treatment, while the corresponding lowest number of effective tillers hill-1 were 7.89 observed in I0 treatment. Sultana (2013) stated that increasing water stress reduced the number of tillers per hill. Variety and irrigation showed significant differences on number of effective tillers hill-1 of wheat due to interaction effect (Table 6). The highest number of effective tillers hill-1 10.33 were observed from V3I3 treatment combination, while the corresponding lowest number of effective tillers hill-1 as 7.33 were recorded from V1I0 treatment combination. Number of non-effective tiller hill-1 Number of non-effective tillers hill-1of wheat was not varied significantly due to varieties (Table 4). BARI Gom 26 produced the highest number of non-effective tillers hill-1 (1.33) and the lowest number of non-effective tillers hill-1(1.00) was observed in BARI Gom 30. Different levels of irrigation varied significantly in terms of number of non-effective tillers hill-1 of wheat at harvest under the present trial (Table 5). The highest number of non-effective tillers hill-1 (2.00) was recorded from I0, while the corresponding lowest number of non-effective tillers hill-1 (0.67) was observed in I3. Variety and irrigation showed significant differences on number of non-effective tillers hill-1 of wheat due to interaction effect (Table 6). The highest number of non-effective tillers hill-1 (2.33) were observed from V1I0 treatment combination, while the corresponding lowest number of non-effective tillers hill-1 (0.33) were recorded from V3I2 treatment combination. Table 4. Effect of variety on yield and yield contributing characters of wheat Table 5. Effect of irrigation on yield and yield contributing characters of wheat Table 6. Interaction effect of variety and irrigation on yield and yield contributing characters of wheat Spike length (cm) Insignificant variation was observed on spike length (cm) at applied three types of modern wheat variety as BARI Gom-26 (V1), BARI Gom-28 (V2), and BARI Gom-30 (V3). From the experiment with that three types of varieties BARI Gom-30 (V3) (8.46 cm) given the largest spike length and BARI Gom-26 (V1) (8.08 cm) was given the lowest spike length (Table 4). Similar result was found using with different type varieties by Hefniet al. (2000). Different irrigation application has a statistically significant variation on spike length as irrigated condition (I3) was given the maximum result (9.17 cm) and non-irrigated condition (I0) given the lowest spike length (7.17 cm) (Table 5). Interaction effect of improved wheat variety and irrigation showed significant differences on spike length. Results showed that the highest spike length was obtained from V3I3 (10.33 cm). On the other hand, the lowest spike length was observed at V1I0 (6.50cm) treatment combination (Table 6). Grain spike-1 Significant variation was observed on grain spike-1 at these applied three types of modern wheat variety. The BARI Gom-30 (V3) (37.75) given the maximum number of grain spike-1 and BARI Gom-26 (V1) (36.92) was given the lowest number of grain spike-1, which was statistically similar with V2 treatment (Table 4). Different wheat genotypes have significant effect on grain spike-1 observed also by Rahman et al. (2009). Different irrigation application has a statistically significant variation on grain spike-1 as the irrigation condition (I3) was given the maximum result (39.33), which was statistically similar with I2 and non-irrigated condition (I0) given the lowest grain spike-1 (34.56) (Table 5). Sarkar et al. (2010) also observed that irrigation have a significant effect on grain spike-1. Interaction effect of improved wheat variety and irrigation showed significant differences on grain spike-1. Results showed that the highest grain spike-1 was obtained from V3I3 (41.0). On the other hand, the lowest grain spike-1 was observed at V1Io (34.00) which were also statistically similar with V3Io (34.67) (Table 6). 3Thousand Seed weight There was significant variation was observed on thousand seed weight due to different types of modern wheat variety. The wheat variety of BARI Gom-30 (V3) (50.40 g) given the maximum thousand seed weight and statistically different from BARI Gom-28 (V2) (46.74 g). BARI Gom-26 (V1) (46.22 g) was given the lowest thousand seed weight (Table 7). Rahman et al. (2009), Islam et al. (2015) also conducted experiment with different variety and observed have effect of varieties on yield. Different irrigation application has a statistically significant variation on thousand seed weight. The I3 was given the maximum thousand seed weight (48.91) and non-irrigated condition (I0) given the lowest yield (46.13 g) (Table 8). Sarkar et al. (2010), Baser et al. (2004) reported that grain yield under non-irrigated conditions was reduced by approximately 40%. Bazzaet al. (1999) reported that one water application during the tillering stage allowed the yield to be lower only than that of the treatment with three irrigations but Meenaet al. (1998) reported that wheat grain yield was the highest with 2 irrigations (2.57 ton/ha in 1993 and 2.64 ton/ha) at flowering and/or crown root initiation stages. Wheat is sown in November to ensure optimal crop growth and avoid high temperature and after that if wheat is sown in the field it faces high range of temperature for its growth and development as well as yield potential. Islam et al. (2015) reported that late planted wheat plants faced a period of high temperature stress during reproductive stages causing reduced kernel number spike-1 as well as the reduction of grain yield. Interaction effect of improved wheat variety and irrigation showed significant differences on thousand seed weight (Table 9). Results showed that the highest thousand seed weight (52.33 g) was obtained from V3I3 which was statistically similar with V3I2 (52.06 g). On the other hand, the lowest yield (45.36 g) was observed at V1I1. Table 7. Effect of variety on yield and yield of wheat Table 8. Effect of irrigation on yield and yield of wheat Table 9. Interaction effect of variety and irrigation on yield and yield of wheat Grain yield (t ha-1) Different wheat varieties showed significant difference for grain weight hectare-1 (Table 7). The highest grain yield hectare-1 (3.44 ton) was found from wheat variety BARI Gom-30 (V3), which was statistically similar with V2, whereas the lowest (3.21 ton) was observed from wheat variety BARI gom 26. Rahman et al. (2009), Islam et al. (2015) also conducted experiment with different variety and observed have effect of varieties on yield. Significant difference was observed for yield for different irrigation application. The three irrigation (I3) was given the maximum yield (3.74 t ha-1), which was statistically similar with I2 treatment and non-irrigated condition (I0) given the lowest yield (2.97 t ha-1) (Table 8). Sarkar et al. (2010), Baser et al. (2004) reported that grain yield under non-irrigated conditions was reduced by approximately 40%. Bazzaet al. (1999) reported that one water application during the tillering stage allowed the yield to be lower only than that of the treatment with three irrigations but Meenaet al. (1998) reported that wheat grain yield was the highest with 2 irrigations (2.57 ton/ha in 1993 and 2.64 ton/ha) at flowering and/or crown root initiation stages. Wheat is sown in November to ensure optimal crop growth and avoid high temperature and after that if wheat is sown in the field it faces high range of temperature for its growth and development as well as yield potential. Islam et al. (2015) reported that late planted wheat plants faced a period of high temperature stress during reproductive stages causing reduced kernel number spike-1 as well as the reduction of grain yield. Interaction effect of improved wheat variety and irrigation showed significant differences on yield (t ha-1). Results showed that the highest yield (3.99 t ha-1) was obtained from V3I3, which was statistically similar with V2I3 and V3I2. On the other hand, the lowest yield (2.93 t ha-1) was observed at V1I0 (Table 7). Straw yield (t ha-1) Applied three types of wheat variety have a statistically significant variation on straw yield (t ha-1). The maximum straw yield (1.95 t ha-1) was obtained from BARI Gom-30 and BARI Gom-26 (V1) was given the lowest straw yield (1.87 t ha-1), which was statistically similar with V2 treatment. Different irrigation application has a statistically significant variation on straw yield (t ha-1) of wheat. The I3 treatment for straw yield (2.01 t ha-1) was given the maximum result and non-irrigated condition (I0) given the lowest (1.80 t ha-1). Similar results were found by Ali and Amin (2004) through his experiment. Interaction effect of improved wheat variety and irrigation showed significant differences on straw yield (t ha-1). The highest straw yield (2.08 t ha-1) was obtained from V3I3 which was statistically similar with V3I2 (2.07 t ha-1) treatment combination. On the other hand, the lowest straw yield (1.78 t ha-1) was observed at V1Io, which was statistically similar with V2I0 (2.07 t ha-1) treatment combination. Biological yield Significant variation was attained for biological yield for different wheat varieties. The variety BARI Gom-30 given the maximum biological yield (5.39 t ha-1) and BARI Gom-26 (V1) was given the lowest biological yield (5.078 t ha-1). Different irrigation application has a statistically significant variation biological yield (t ha-1) of wheat. The I3 treatment for biological yield (5.76 t ha-1) was given the maximum result and non-irrigated condition (I0) given the lowest (4.77 t ha-1). Similar results were found by Ali and Amin (2004) through his experiment. At the time of biological yield (t ha-1) consideration with variety and irrigation statistically significance variation was observed as maximum biological yield (t ha-1) at V3I3 (6.07 t ha-1). On the other hand, the lowest result was given at V1Io (4.72 tha-1). Summary And Conclusion It may be concluded within the scope and limitation of the present study that the optimum growth and higher yield of wheat cv. BARI Gom-30 could be obtained by applying three irrigations at irrigate at CRI, booting and grain filling stages. However, further studies are necessary to arrive at a definite conclusion. References Ali, M. N.; and Amin, M.S. Effect of single irrigation and sowing date on growth and yield of wheat. M. S. thesis, SAU, Dhaka, Bangladesh. 2004. (Bangladesh Agricultural Research Institute). Hand book of Agricultural Technology. Joydebpur, Gazipur. 2006, 9. Baser, I.; Sehirali, S.; Orta, H.; Erdem, T.; Erdem, Y.; Yorganclar, O. Effect of different water stresses on the yield and yield components of winter wheat. Cereal Res. Comn. 2004, 32(2), 217-223. Bazza, S. S.; Awasthi, M. K.; Nema, R. K. Studies on Water Productivity and Yields Responses of Wheat Based on Drip Irrigation Systems in Clay Loam Soil. Indian J. Sci. Tech. 1999, 8(7), 650-654. Bangladesh Bureau of Statistics, Ministry of Planning, Government of the Peoples Republic of Bangladesh, Dhaka. 2013. Bangladesh Bureau of Statistics, Ministry of Planning, Government of the Peoples Republic of Bangladesh, Dhaka. 2014. K. A.; Gomez, A. A. Statistical Procedures for Agricultural Research. 2nd edition. John Willy and Sons, New York. 1984, 28-192. Gupta, P. K.; Gautam, R. C.; Ramesh, C. R. Effect of water stress on different stages of wheat cultivation. Plant Nutri. and Fert. Sci. 2001, 7(2), 33-37. Hanson, M.; Farooq, M.; Shabir, G.; Khan, M. B.; Zia, A. B.; Lee, D. G. Effect of date sowing and rate of fertilizers on the yield of wheat under irrigated condition. J. Agril. & Biol. 1982, 14(4), 25-31. Hefni, S.; Sajjad, A.; Hussain M. I.; Saleem, M. Growth and yield response of three wheat varieties to different seeding densities. J. Agric. Biol. 2000, 3(2), 228-229. Islam, S.; Islam, S.; Uddin, M. J.; Mehraj, H.; Jamal Uddin, A. F. M. Growth and yield response of wheat to irrigation at different growing stages. J. Agron. Agril. Res. 2015, 6(1), 70-76. Meena, B. N.; Tunio, S. D.; Shah, S. Q. A.; Sial, M. A.; Abro, S. A. Studies on grain and grain yield associated traits of bread wheat (Triticum aestivum L.) varieties under water stress conditions. Pakistan J. Agril. Engin. Vet. Sci. 1998, 24(2), 5-9. Rahman, M. ; Hossain, A.; Hakim, M. A.; Kabir, M. R; Shah, M. M. R. Performance of wheat genotypes under optimum and late sowing condition. Int. J. Sustain Crop Prod. 2009, 4(6), 34-39. Rosegrant, M. W.; Agcaoili, M. Global food demand, supply, and price prospects to 2010. Washington, DC: Int. Food Policy Res. Inst. 2010. Rosegrant, M. W.; Sombilla, M. A.; Gerpacio R. V.; Ringler, C. Global food markets and US exports in the twenty-first century. Paper prepared for the Illinois World Food and Sustainable Agriculture Program Conference ‘Meeting the Demand for Food in the 21st Century: Challenges and Opportunities for Illinois Agriculture’, 1997. Sarker, S.; Singh, S. K.; Singh, S. R.; Singh, A. P. Influence of initial profile water status and nitrogen doses on yield and evapotranspiration rate of dryland barley. Indian Soc. Soil Sci. 2010, 47(1), 22-28. Sultana, F. Effect of irrigation on yield and water use of wheat. M.S. Thesis, Dept. of Irrigation and Water Management. Bangladesh Agril. Univ., Mymensingh. 2013.

Abstract.<em>—</em>Our objectives were to study habitat use of different life stages of the burbot <em>Lota lota </em>L. in lowland rivers and to develop habitat models to assess possible reintroduction sites in Flanders, Belgium. Summer habitat use of subadult and adult burbot was studied in lowland rivers in northeast France in the Meuse basin. Highest burbot densities were found in the upper river parts over several watersheds. Adult and subadult burbot showed a strong preference for microhabitats characterized by undercut banks and cover by tree roots. Habitat use of larvae and fingerlings was studied in spring. Both larvae and fingerlings were exclusively found in small tributaries (width < 2 m). Fingerlings mainly occupied tributaries with low to moderate flow velocity (0.05–0.15 m/s) and high densities of vegetation (>25%). Winter spawning migration was studied using fyke nets. Adult burbot migrated into the deepest tributaries and upstream migration was highest at increased water levels or flows. Analysis of water quality requirements revealed that both nitrate (NO₃^–) and total nitrogen (N_<em>t</em>) content negatively influenced burbot densities. With these results, two models to evaluate habitat suitability of lowland rivers for burbot were developed and tested. The use of these models to evaluate potential reintroduction sites for burbot in Belgium is discussed.

Abstract The study area covers 1,300 km2 in southeastern Abu Dhabi and focuses on the Aptian (Apt.) 5 Upper Shuaiba progradational clinoform system. The Shuaiba Formation has been well-studied at the regional level, but with comparatively less focus on the Apt. 5 system. Studying depositional trends and shoal facies distributions within the Apt. 5 is critical for predicting reservoir presence and quality. Given the complexity of the Apt. 5 system, understanding the key controls over depositional environments, such as paleowind direction, is an important first step. This study combined regional context and geological understanding with previous studies to confirm existing clinoform interpretation, while also delineating four additional clinoform sequences using a reprocessed depth migrated 3-D seismic volume. Isochron maps were also used to group clinoforms into three packages distinguished by common morphologies possibly linked to their respective dominant reservoir facies. Preliminary observations suggest early clinoforms had more rudist build-ups, whereas the later clinoforms were dominated by narrow-shoal beaches. Coalescing clinoform shoal patterns, observed in the spectral decomposition and amplitude extraction maps, likely result from a combination of Bab Basin morphology, longshore current, and dominant paleowind direction during the Early to Middle Cretaceous. Existing interpretations of dominant paleowind direction vary significantly, ranging between E-W and S-N. Interpretations from this study are most consistent with prevailing paleowind out of the east-southeast. The Arabian plate was likely near the equator around 10°S latitude during the Aptian, which supports the southeast wind hypothesis when considering modern Coriolis patterns. Consistent wind influence on shallow water shoal environments would have winnowed mud and increased the proportion of grain-dominated sediment preserved relative to lower energy areas. The grain-dominated facies appear to be reflected in amplitude responses around the coalescing clinoforms, and in the amplitude variations along strike coincident with clinoform edges. Reservoir presence and quality uncertainty can be reduced if these observations can be confirmed. An improved understanding of the Apt. 5 clinoform system in southeast Abu Dhabi, and possible influences on reservoir distribution and quality, will help develop a better understanding of risk for prospect maturation.

Making the most of daylight in town planning is one of the important ingredients in the attempts for the sustainable city. Exactly 150 years ago Ildefons Cerdà presented his great work “Teoría General de la Urbanización” including methods for taking care of sunlight. However, with modern software, the possibilities to do comprehensive preparations are much better. This paper presents an urban typology considering daylight with basic geometric forms, shapes and patterns. Later this will be elaborated more in detail. The research includes three steps; choosing typical alternatives for settlements and designing some new principle urban solutions, calculations and evaluations of the alternatives considering especially energy saving. The quality and the quantity of daylight are dependent of the geometry of the urban spaces. That means the volumes for the buildings as well as the empty spaces in between. The accessibility for diffuse daylight from the sky and for direct rays from the sun is measurable by computer calculations where the sun angles and the skylight from the hemisphere are simulated. Relevant parameters are height, width and length. In a settlement with a high urban density it is more difficult to distribute daylight than in a settlement with low density. However the economy for exploitations is also worse with lower density. Therefore the comparisons between different settlements are with the same density. The orientation of the settlements according to the compass is of crucial importance looking to the direct sunlight and the shadows. How the local environment with parks, water, mountains and specific landmarks in the surroundings also affects the daylight distribution is included.References (100 words) Dubois, M.-C., Gentile, N., Amorim, C., Osterhaus, W., Stoffer, S.,Jakobiak, R., Geisler-Moroder, D., Matusiak, B., Onarheim, F. M., Tetri, E. (2016) Performance Evaluation of Lighting and Daylighting Retrofits: Results from IEA SHC Task 50. (Energy Procedia. vol. 91). Littefair, P. J. (2011) Site layout planning for daylight and sunlight: a guide to good practice (BRE, Building Research Establishment, IHS BRE Press, Watford). Rode, P., Keim, C., Robazza, G., Viejo, P. and Schofield, J. (2014) Cities and energy: urban morphology and heat energy demand (LSE, London School of Economics, Cities and EIFER, European Institute for Energy Research, Karlsruhe Institute of Technology, London).