Effect of Nitrogen Application Rates on Cotton Yield and Fibre Quality - Results from Recent Trials in Australia

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As a consequence, trials were conducted in Australia in 2018 and 2019 in four locations using three popular high yielding commercial varieties sown in the Australian cotton industry. Nitrogen was applied in the form of granular urea in three locations, in split applications either before or in-crop with Anhydrous ammonia applied at the fourth location before planting. Application rates ranged from zero (0 kg.ha − 1 ) to moderate (100 to 200 kg.ha − 1 ) to high (300 kg.ha − 1 ) and excessive (400 kg.ha − 1 ). Results The application of moderate (100 to 200 kg.ha − 1 ) rates of nitrogen resulted in the highest yield and nitrogen use efficiency and produced the longest, uniform, and strongest fibre. As the growing conditions for the two seasons were ideal it was shown that nitrogen application rates did not influence micronaire but did negatively affect colour and lint turn out. Conclusions Nitrogen application rates do impact yield, lint turn out and fibre quality. However excessive application rates above 14 to 15 kg of N per bale had no economic benefit to the grower and could negatively affected yield and fibre quality. Cotton Nitrogen Yield Fibre Quality Introduction The importance of nitrogen application in cotton production in terms of plant growth, health, yield etc. are well understood and has been studied for over a century (Maples et al. 1990 ), with practical guidelines (Anon 2001 ), decision support systems (Deutscher et al. 2001 ; Gerik et al. 1998 ), models (Zhao et al. 2010 ) and recent reviews (MacDonald et al. 2018 ; Soomro et al. 2020 ; Ali 2015 ; Khan et al. 2017 ) providing information on the importance of providing crops with sufficient supply of nutrients and improving nitrogen use efficiency (NUE). Unfortunately, despite the fact that the financial return to the grower in most crop production systems depends on crop quantity and quality only a limited number of studies and reviews have been published on work and knowledge relating to the effect of nitrogen (N) application rates on fibre quality, including lint turn out. A recently published review concluded that the observed effects of N application rates on fibre quality were rather varied and often inconsistent (van der Sluijs 2022 ). In terms of fibre length, the majority of studies (Reynolds and Killough 1933 ; Bennett et al. 1967 ; MacKenzie and Schaik 1963 ; Murray et al. 1965 ; Koli and Morrill 1976a ; Shrivastava and Singh 1988 ; Boman and Westerman 1994 ; Girma et al. 2007 ; Pettigew et al. 1996 ; Chand et al. 1997 ; Ebelhar et al. 1996 ; Janat and Somi 2002 ; Bauer and Roof 2004 ; Boquet 2005 ; Fritschi et al. 2003 ; McFarland et al. 1999 ; Janat 2008 ; Gormus 2005 ; Pettigew and Adamczyk 2006 ; Gadhiya et al. 2009 ; Afzal et al. 2018 ; Saleem et al. 2010 ; Rashidi and Gholami 2011 ; Hernandes-Cruz et al. 2015 ; Chen et al. 2019 ; McClanahan et al. 2020 ; Sawan et al. 1997 ; Read et al. 2006 ) concluded that increased application rates of N had no significant effect on length, with a few studies (Setatou and Simonis 1994 ; 1995 ; Ali 2011 ; Madani and Oveysi 2015) finding no clear trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Bennett et al. 1967 ; Nelson 1949 ; Perkins and Douglas 1965 ; Jackson and Tilt 1968 ; Grimes et al. 1969b ; Grimes et al. 1969a ; Hearn 1976 ; Constable and Hearn 1981 ; Tewolde and Fernandez 2003 ; Sawan et al. 2006 ) or a negative (decrease) (Lokhande and Reddy 2015 ; Sui et al. 2017 ) effect on fibre length. Similarly, the majority of studies (Bennett et al. 1967 ; Murray et al. 1965 ; Koli and Morrill 1976a ; Boman and Westerman 1994 ; Pettigew et al. 1996 ; Ebelhar et al. 1996 ; Janat and Somi 2002 ; Boquet 2005 ; Fritschi et al. 2003 ; McFarland et al. 1999 ; Janat 2008 ; Gormus 2005 ; Pettigew and Adamczyk 2006 ; Afzal et al. 2018 ; Saleem et al. 2010 ; Rashidi and Gholami 2011 ; Hernandes-Cruz et al. 2015 ; McClanahan et al. 2020 ; Sawan et al. 1997 ; Madani and Oveysi 2015; Perkins and Douglas 1965 ; Grimes et al. 1969b ; Grimes et al. 1969a ; Hearn 1976 ; Tewolde and Fernandez 2003 ; Sui et al. 2017 ; Hossein et al. 2014 ; Seilsepour and Rashidi 2011 ; Leal et al. 2020 ) concluded that increased N application rates had no significant effect on strength, with a few studies (MacKenzie and Schaik 1963 ; Read et al. 2006 ; Setatou and Simonis 1994 ; 1995 ; Jackson and Tilt 1968 ; Constable and Hearn 1981 ; Echer et al. 2020 ) finding no trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Girma et al. 2007 ; Bauer and Roof 2004 ; Chen et al. 2019 ; Sawan et al. 2006 ; Sui et al. 2017 ; Zhao et al. 2012 ; Pettigew 2012 ; Pettigew and Zeng 2014 ; Gormus et al. 2016a ; Gormus and El Sagagh 2016b ) or a negative (decrease)(Nelson 1949 ; Lokhande and Reddy 2015 ; Verna et al. 2017 ) effect on fibre strength. For micronaire the majority of studies concluded that increased N application rates had either no significant effect, or no clear trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Bauer and Roof 2004 ; Rashidi and Gholami 2011 ; Chen et al. 2019 ; Sawan et al. 1997 ; Sawan et al. 2006 ; Hossein et al. 2014 ; Seilsepour and Rashidi 2011 ; Gormus et al. 2016a ) or a negative (decrease)(Koli and Morrill 1976a ; Ebelhar et al. 1996 ; Janat and Somi 2002 ; Fritschi et al. 2003 ; Saleem et al. 2010 ; McClanahan et al. 2020 ; Hearn 1976 ; Tewolde and Fernandez 2003 ; Lokhande and Reddy 2015 ; Sui et al. 2017 ; Leal et al. 2020 ; Echer et al. 2020 ; Zhao et al. 2012 ) effect on micronaire. On the other hand, there was general agreement (Boman and Westerman 1994 ; Ebelhar et al. 1996 ; Bauer and Roof 2004 ; Tewolde and Fernandez 2003 ; Sui et al. 2017 ; Pettigew and Zeng 2014 ) that colour in terms of reflectance and yellowness was negatively affected by increased N application rates resulting in the fibre becoming less bright and duller and possibly resulting in a reduction in the colour grade. In terms of lint turn out the majority of studies (Bennett et al. 1967 ; Chand et al. 1997 ; Fritschi et al. 2003 ; Janat 2008 ; Hernandes-Cruz et al. 2015 ; Sawan et al. 1997 ; Setatou and Simonis 1994 ; 1995 ; Nelson 1949 ; Perkins and Douglas 1965 ; Sawan et al. 2006 ; Echer et al. 2020 ; Scarsbrook et al. 1959 ; Boman et al. 1997 ; Phipps et al. 1996 ; Rochester and Constable 2020 ) concluded that N application rates did result in either a significant reduction in lint turn out, no significant effect (Shrivastava and Singh 1988 ; Pettigew et al. 1996 ; Ali 2011 ) or with no clear trend (Bennett et al. 1967 ; Jackson and Tilt 1968 ). There were however a small number of studies that showed that N application rate did increase (MacKenzie and Schaik 1963 ; Gormus 2005 ;Gadhiya et al. 2009 ; Saleem et al. 2010 ; Chen et al. 2019 ; Gormus et al. 2016a ; Gormus and El Sagagh 2016b ; Verna et al. 2017 ) lint turn out. It was hypothesized that different varieties and growing conditions are the main reasons for these inconsistent results. With the range of different test methods and instruments and at times no indication of the test method and instrument also contributing to these differences. In order to obtain further clarification N was applied at different application rates ranging from zero to moderate to high and excessive over two years in four locations using popular high yielding (> 2000 kg.ha − 1 ) commercial Upland cotton ( Gossypium hirsutum L.) varieties common in the Australian cotton industry. Materials And Methods Three studies were undertaken during the 2018/2019 growing season (planted in 2018; defoliated, harvested and ginned in 2019) at the Australian Cotton Research Institute (ACRI) in Narrabri (149 o 36’E,30 o 12’S) in the Namoi Valley of New South Wales (NSW), one at the Irrigation Research and Extension Committee (IREC) in Griffith (34°17′24’S 146°2′24E) in the Murrumbidgee Valley (Southern region) of NSW, and one at Toobeah (28.4169°S 149.8702°E) in the MacIntyre Valley (Central region) of Queensland (Qld). Two further studies were undertaken during the 2019/2020 growing season (planted in 2019; defoliated, harvested, and ginned in 2020); one at ACRI and one at Cecil Plains (27.5316°S 151.1930°E) on the Darling Downs in Central Qld. A summary of the respective field operations employed on each of the fields (designated A to E) are presented in Tables 1 & 2 . The cotton varieties used for the trials were two CSIRO varieties, containing Bollgard® 3 technology stacked with Roundup Ready Flex®, Sicot 746 B3F (Stiller 2016a ) and Sicot 714 B3F (Stiller 2016b ), currently the two most popular Upland transgenic varieties grown in Australia as well as Sicala V-2 (Reid 1995 ), a popular CSIRO conventional variety grown in the late 1990s. All fields were subjected to standard management practices for irrigated Upland cotton in Australia. N was applied in the form of granular urea and at one field as Anhydrous ammonia, all in split applications, at application rates ranging from zero (0 kg.ha − 1 ) to moderate (100 to 200 kg.ha − 1 ) to high (300 kg.ha − 1 ) and excessive (400 kg.ha − 1 ). For ease of interpretation fibre properties were all measured by high volume instruments which is the preferred method of cotton classification for cotton trading (ICAC/ITMF 2018). Urea containing 46% N was applied by side dressing to the field at ACRI (designated as A for 2018 & D for 2019) using a Simplicity air cart with a Gessner-Walker frame and a Shearer double disc opener prior to planting. One hundred kg.ha − 1 was applied prior to planting followed by further application of 100 and 200 kg.ha − 1 respectively in-crop to achieve the application rate of 200 kg.ha − 1 and 300 kg.ha − 1 . The field was then subjected to three harvest aid applications by ground rig, with a mixture of leaf defoliant and boll opener. The trials were conducted using a randomized complete block design, with four replications. Seed cotton from 32 plots, with four rows spaced at one meter, was harvested by a single row Case IH 1822 spindle harvester (CNH America, Racine, WI). An average of 0.234 kg of seed cotton was collected from each replicate and ginned using a 20-saw gin (Continental Eagle, Prattville, AL) with a Mitchell feeder and pre-cleaner situated at ACRI. Urea containing 46% N was applied by side dressing to Field B using a Shearer double disc opener. One hundred and seventy five and 375 kg.ha − 1 respectively was applied prior to planting followed by a further application of 25 kg.ha − 1 in-crop to achieve the application rates of 200 kg.ha − 1 and 400 kg.ha − 1 . The field was then subjected to three harvest aid applications by air, with a mixture of leaf defoliant, boll opener and crop oil. The field was harvested using a grower owned and operated John Deere 7760 spindle round module harvester (Moline, IL), with Pro16 row units. Only part of the field was utilized for this trial (3.05 ha per treatment), using a randomized complete block design, with three replications. A total of sixty-four part round modules were harvested and were ginned, in sequence under standard commercial conditions, at the Namoi Cotton Limited MacIntyre No. 1 gin, situated in Goondiwindi, Qld. This gin is a Continental Eagle (Prattville, AL) high-capacity saw gin, equipped with four 181 gin stands, with no flow-through air lint cleaner and two stages of controlled-batt saw lint cleaners, capable of producing 60 bales.hour − 1 . Urea containing 46% N was spread across the soil surface (broadcast fertilisation) to Field C using a Marshall Multispread trailer. The IREC soil had a starting nitrate-N concentration of 136 kg N ha − 1 and there were three in-crop applications of 62 kg N ha − 1 , 40 kg N ha − 1 and 62 kg N ha − 1 to achieve 300 kg N ha − 1 . The field was then subjected to three harvest aid applications by ground rig, with a mixture of leaf defoliant and boll opener. The field was harvested using a grower owned and operated John Deere 7760 spindle round module harvester (Moline, IL), with Pro16 row units. The field utilized for this trial was sown with the two varieties using a randomized complete block design, with four replications, with each replication 0.156 ha. A total of sixteen part round modules were harvested and ginned in sequence, under standard commercial conditions, at Southern Cotton situated in Leeton, NSW. This gin is a Lummus Corporation (Savannah, GA) high-capacity saw gin, equipped with four 222 gin stands, with one stage of flow-through air lint cleaner and two stages of batt-less saw lint cleaners, capable of producing 60 bales.hour − 1 . Anhydrous ammonia containing 82% N was applied directly into the soil of Field E prior to planting by an Excel Agriculture SP200 double row unit to achieve the application rate of 300 kg.ha − 1 . The field was then subjected to two harvest aids by air, with a mixture of leaf defoliant, boll opener and crop oil. The trial was conducted using a randomized complete block design, with four replications. Seed cotton from 16 plots, with 18 rows spaced at 1 meter, was hand harvested, due to the uncertainty created by COVID and accessibility to a mechanical harvester. An average of 0.234 kg seed cotton samples were collected from each replicate and ginned using the 20-saw gin (Continental Eagle, Prattville, AL) with a Mitchell feeder and pre-cleaner situated at ACRI. For Fields A & D, samples collected after ginning were subjected to objective measurement, as per ASTM D5867 (ASTM 2012a ), using an Uster® Technologies AG HVI™ 1000 (Knoxville, TN) at ACRI. Two sub samples of each sample were evaluated for fibre length in terms of upper half mean length (UHML in mm), length uniformity (UI%), short fibre index (fibres < 12.7 mm) (SFI%), bundle strength in g.tex − 1 (STR) and micronaire (MIC). For Fields B & C, classing samples, from opposite sides, of each bale were collected at the gin after bale formation, with samples for Field E collected after ginning. Two sub samples were evaluated by objective measurement at commercial classing facilities including colour in terms of yellowness (+ b), reflectance (Rd) and trash in terms of leaf count, % area and leaf grade. Visual classing of the lint was also assessed for colour (CG) and visible trash (LG) according to the 2018 grades as established by USDA-AMS, as per ASTM D1684 (ASTM 2012b ). All fibre samples were conditioned under standard conditions of 21+/-1°C and relative humidity % of 65+/-2 as per ASTM D1776 (ASTM 2015 ). For all fields, the percentage of the weight of usable fibre per the weight of un-ginned seed cotton (lint turn out) was calculated either by the commercial ginning operators or by technicians at ACRI. NUE was also calculated for evaluating efficiency of the conversion of N fertiliser into cotton lint as per Eq. 1. A NUE of 13 to 18 kg lint/kg of N is recommended for irrigated cotton, with values below 13 indicating that too much N was applied and values above 18 indicating that insufficient N was applied (Rochester 2014 ). To test for statistical differences between treatment means, ANOVA was conducted on the experimental data using Genstat 16.0 (Lawes Agricultural Trust, IACR Rothamsted, UK). Means for each parameter followed by a different letter are significantly different at p ≤ 0.05, with non-significant differences designated as n.s. Results Tables 3 to 7 summarize the NUE, lint turn out, yield as well as fibre quality as measured by objective measurement using an HVI instrument for all fields (A to E), with visual assessment also conducted for the larger/commercial trials for two fields (B and C), as well as the hand harvested field (E). ACRI (A &D) Table 3 shows that there were statistically significant differences between the four N application rates for lint turn out and fibre strength for Sicot 746 B3F. At 48.7% the highest lint turn out was obtained from 0 kg.ha -1 , whereas the application of 200 kg.ha -1 , resulted in slightly stronger fibre than that achieved for 0, 100 and 300 kg.ha -1 , respectively. Although not significant, the application of 200 kg.ha -1 , produced slightly longer and uniform fibre. The application of 200 kg.ha -1 also resulted in the highest average yield of 8.5 bales.ha -1 (bale = 227 kg), which was 0.9, 0.6 and 0.6 bales.ha -1 more than that achieved for 0, 100 and 300 kg.ha -1 respectively, although 100 kg.ha -1 achieved the most desirable NUE of 18. There were no statistically significant differences between the four N application rates for lint turn out and fibre properties for Sicala V-2. The results did, however, indicate that overall, the most favourable results were obtained with the application of 200 kg.ha -1 , which also resulted in the highest average yield of 8.5 bales.ha -1 , which was 0.7, 0.2 and 0.9 bales.ha -1 more than that achieved for 0, 100 and 300 kg.ha -1 respectively, whilst 100 kg.ha -1 achieved the most desirable NUE of 19. Similarly, the application of 200 kg.ha -1 , resulted in producing the longest and amongst the most uniform, and strong fibre. Table 6 shows that there were no statistically significant differences between the three N application rates for lint turn out and fibre properties for all three varieties. The results for Sicot 746 B3F did, however, indicate that overall, the application of 200 kg.ha -1 , resulted in the strongest and one of the most uniform and even fibres produced with one of the highest lint turn out (46.7%), although 100 kg.ha -1 achieved the highest yield at 10.5 b. ha -1 . The NUE for all applications were mostly either too high or low for the yield achieved. The results for Sicot 714 B3F indicated that overall, 0 kg.ha -1 produced the longest, uniform, and strongest fibre with the highest lint turn out (44.0%), whilst 200 & 300 kg.ha -1 produced the highest yield, with 200 kg.ha -1 achieving the better NUE of 13. The results for Sicala V-2 indicated that overall, 100 kg.ha -1 produced the longest, strongest and amongst the most uniform fibre, with amongst the highest lint turn out (40.8%), and with 200 kg.ha -1 achieving the highest yield (7.7 bales.ha -1 ) whilst 100 kg.ha -1 achieved the most desirable NUE of 17. Toobeah (B) Table 4 shows that there were statistically significant differences between the three N application rates for most fibre properties for both Sicot 746 B3F and Sicot 714 B3F. In terms of Sicot 746 B3F, overall, the best fibre quality was achieved with 200 kg.ha -1 which resulted in a slight, but statistically significantly longer, uniform, and stronger fibre and although the colour and trash values, as measured by HVI, were marginally, but statistically significantly better, did not improve the visual determined colour and leaf grade, which was 31-3. There were no statistically significant differences in lint turn out between the three N applications. At a yield of 14.0 bales.ha -1 , the application of 200 kg.ha -1 also produced amongst the highest yield with an NUE of 16, although at a lower lint turn out. Similar results were obtained for Sicot 714 B3F, where overall, the best fibre quality was also achieved with 200 kg.ha -1 , resulting in a marginal, but statistically significantly, longer, uniform, and stronger fibre and although the colour and trash values, as measured by HVI, were also slightly, but statistically significantly better, did not improve the visual determined colour and leaf grade which was 31-3. There were no statistically significant differences in lint turn out between the three N applications. At a yield of 14.2 bales.ha -1 , the application of 200 kg.ha -1 , also produced amongst the highest yield and lint turn out, with an NUE of 16. IREC (C) Table 5 shows that there were no statistically significant differences between the two application rates for all the fibre properties for both varieties although the application of 136 kg.ha -1 did produce a marginally longer, uniform, and stronger fibre for Sicot 746 B3F. The accurate determination of lint turn out at commercial gins require the gin to completely run out prior to commencing the next batch and if this is not strictly adhered to results can be wrong and misleading. Certainly, the results for lint turn out and as a consequence yield and NUE for Sicot 746 B3F are therefore questionable. The results for Sicot 714 B3F were judged to be more realistic Cecil Plains (E) Table 7 shows that there were no statistically significant differences between 0 and 300 kg.ha -1 for all of the fibre properties for both Sicot 746 B3F and Sicot 714 B3F. Similarly, there were no practical differences in lint turn out and yield between 0 and 300 kg.ha -1 for both varieties, although Sicot 714 B3F achieved higher yields and as a consequence favourable NUE. Discussion Growing Season The three studies conducted during the 2018/2019 growing season all experienced hot and warm weather, with the number of days above 36°C and 40°C and the number of nights above 25°C all above average with below average rainfall. As can be seen in Table 2 , this resulted in the accumulation of high and above average day degrees in the 2400 to 3000 category which in Australia is considered as very good growing conditions (Anon 2014 ) having a positive effect on fibre quality specifically micronaire and colour (Luo et al. 2016 ; Bange et al. 2022 ). Similarly, the two studies conducted during the 2019/2020 growing season also experienced hot and warm weather, with the number of days above 36°C and 40°C and the number of nights above 25°C and rainfall experienced in Narrabri all above average. Although this resulted in the accumulation of slightly lower day degrees it was still considered as very good growing conditions. Cecil Plains, however, did not record any nights above 25°C and experienced more than double the number of cold shock days than the average and received less than average rainfall. This resulted in the accumulation of slightly lower day degrees in the 1800 to 2400 category which is considered in Australia as normal growing conditions. Yield The average yield for the 2018/19 for the three varieties was variable with Sicot 714 B3F achieving the highest yield of 12.2 bales.ha − 1 followed by Sicot 746 B3F at 10.4 bales.ha − 1 and Sicala V-2 with 8.1 bales.ha − 1 . With the exception of the Sicala V-2, these yields were either above or in line with the average cotton yields achieved in Australia for irrigated cotton during that time (Anon 2021 ). Although lower than the two current most popular varieties currently grown in Australia at almost 8 bales.ha − 1 the yield for Sicala V-2 a conventional variety grown in the 1990s can still be considered as exceptional. The average yield for the 2019/20 for the three varieties was 11.4 bales.ha − 1 for Sicot 714 B3F followed by Sicot 746 B3F at 10.1 bales.ha − 1 and Sicala V-2 with 7.2 bales.ha − 1 . Which again with the exception of the Sicala V-2, were above the average cotton yields achieved in Australia. Bearing these yields in mind the suggested amount of N required to achieve the average yields above for the three varieties was 200, 180 and 120 kg.ha − 1 respectively, to achieve the recommended NUE of 13 to 18, This result was similar to previous studies conducted in Australia that concluded that the application of N above 200 to 250 kg. ha − 1 did not result in increased yields (Buster 2019a , b , c , 2020 , 2021 ). With higher application rates resulting in no economical benefit to the grower and possibly leading to higher costs (i.e., increased defoliation and plant growth regulator applications) and quality downgrades. This equates to an average of 14 to 15 kg of N for the current most popular Upland transgenic varieties grown in Australia for each bale of lint produced. Lint turn out The lint turn out results for the five trials were variable with only the small scale trials (Fields A & D) at ACRI and to a lesser extend at Cecil Plains (Field E) achieving the expected lint turn out (47% for Sicot 746 B3F, 45% for Sicot 714 B3F and 39% for Sicala V-2 (Stiller 2016a ; 2016b ; Reid 1995 ). The lint turn out for the larger commercial trials (Fields B & C) that were ginned at high capacity throughput gins were lower. This was not entirely unexpected as these gins, as do most modern gins, have either two and three stages of lint cleaning as part of their processing system to remove foreign matter left in the lint after the seed cotton cleaning and ginning stages. With a recent study showing that lint cleaners can reduce bale weights by up to 27 kg and reduce lint turn out by up to 2% (van der Sluijs 2020 ). As highlighted earlier the results for Sicot 746 B3F from Field C were questionable and hence not included in this discussion. Overall, although there was no statistically significant effect of N application rate on lint turn out, there does seem to be a trend in a decrease in lint turn out with increased N application rates. This is consistent with previous studies that showed that in general increased N application rates led to reduced lint turn out (van der Sluijs 2022 ). Fibre Quality The fibre quality results for the five trials were either equivalent or better than the Australian base grade, which is length of 28.7 mm (36 32nds), length uniformity 81%, strength 29 g.tex − 1 , micronaire range 3.5 to 4.9 (G5), colour 31(Middling) and trash grade of 3, with short fibre content % preferably < 9.0%. Base grade refers to the grade of cotton that is used by cotton merchants as a basis for contracts and to determine premiums, and discounts. Except for Field B, there were no statistically significant differences in fibre length with an increase in N. The results for Field B for both varieties showed significant improvement in length by one grade (37 to 38 32 nds), with the application of 200 kg.ha − 1 , with a reduction in length with the application of 400 kg.ha − 1 . Similarly, length uniformity and short fibre content followed the same trend, with length uniformity improving and short fibre content decreasing with the application of 200 kg.ha − 1 . Although, not statistically significant Field A, followed a similar trend, with the results for Fields C, D & E more varied with either 0, 100, 136, 200 or 300 kg.ha − 1 producing the longest and most uniform fibre. These results are not entirely unexpected as it is a well-known fact that fibre length is primary a genetic trait and with the near perfect growing conditions experienced the application above NUE will not result in an improvement in fibre length, uniformity or short fibre % (van der Sluijs 2022 ). Except for fields, A & B, there were no statistically significant differences in fibre strength with increased N application rates. The results for Field A for only Sicot 746 B3F and for both varieties from Field B, showed a slight but significant improvement in fibre strength (1 g.tex − 1 ) with the application of 200 kg.ha − 1 , with a statistically significant reduction in fibre strength with increased application rates. This increase in strength corresponded to an NUE between 13 and 16. The results for Fields C,D & E and Sicala V-2 from Field A was more varied with either 0, 100, 136, 200 or 300 kg.ha − 1 , producing the strongest fibre. Again, this is not surprising as fibre strength is also primarily a genetic trait and with the growing conditions and management the application above NUE would not have resulted in an improvement in fibre strength. It is also likely that the results for Fields A,D & E were ginned on a laboratory size gin without lint cleaning which may have influenced the results (van der Sluijs 2022 ). Apart from Field B, there were no statistically significant differences in micronaire with an increase in N application rates. The results for Field B for only Sicot 746 B3F showed a slight reduction in micronaire with the application of 400 kg.ha − 1 . Although, not statistically significant the micronaire values for Fields C & D also reduced slightly with increased N application whereas the micronaire value increased slightly with N application rates for Fields A & E. All the changes were of little practical significance as all the micronaire values were within the Australian base grade. These results were not unsurprising as the two growing seasons were considered to be ideal and exceptional resulting in the accumulation of above average day degrees and hence favourable micronaire values (Bange et al 2022 ). Apart from Field B, there were no statistically significant differences in HVI colour measurements with an increase in N application rates. The results for Field B for both varieties showed a reduction in Rd and + b with the application of 200 kg.ha − 1 , with both Rd and + b improving with the application of 400 kg.ha − 1 . This change in the colour measurements were of little practical significance as at 31 the visual grade was equal to the Australian base grade. The colour measurements for Fields C & E were varied with no changes to the visual colour grade. Interestingly, with a colour grade of 21 (Strict Middling), Sicot 714 B3F was one grade better than Sicot 746 B3F. The colour and trash grade for both varieties from Field E were exceptional; graded as 11 (Good Middling) with a leaf grade of 1. This was not entirely unexpected as this cotton was harvested by hand and hence was free from impurities and trash as highlighted by the HVI trash results. Conclusions The importance of N application in the cotton production system is well understood. What is poorly understood is what the effect of N application rates are on fibre quality, including lint turn out, with previous studies reporting varied and inconsistent results. In order to obtain further clarification N was applied either in the form of granular urea or Anhydrous ammonia in split applications either before or in-crop at application rates ranging from zero (0 kg.ha − 1 ) to moderate (100 to 200 kg.ha − 1 ) to high (300 kg.ha − 1 ) and excessive (400 kg.ha − 1 ). Trials were conducted in 2018 and 2019 in four locations using two popular transgenic and one conventional Upland cotton varieties common in the Australian system. Results indicated that in general, the application of moderate (100 to 200 kg.ha − 1 ) rates of N resulted in the highest yield and desired NUE in the range of 13 to 18, which equates to an average of 14 to 15 kg of N for each bale of lint produced from the transgenic varieties currently used in Australia. Furthermore, the results showed that the application of moderate (100 to 200 kg.ha − 1 ) rates of N resulted in the highest yield, lint turn out and NUE and also produced the longest, uniform, and strongest fibre. As the growing conditions for the two seasons were closely aligned, N application rates did not influence micronaire but did negatively affect colour and lint turn out. Under these conditions there was not a variety effect. Certainly, more veritable, challenging and less than ideal growing conditions would no doubt report different conclusions. Declarations Acknowledgments The authors acknowledge the generous cooperation of Ella Arnold from Cotton Seed Distributors Limited for providing information on climatical conditions experienced at the various trial sites. Author Information Textile Technical Services, 35 Helena Street, Belmont, Geelong, Victoria, 3216, Australia Deakin University, Pigdons Road, Waurn Ponds, Geelong, Victoria, 3216, Australia VAN DER SLUIJS, Marinus, H.J. CSIRO Agriculture & Food, 21888 Kamilaroi Highway, Myall Vale, NSW, 2390, Australia WEAVER, Timothy, B. Contributions Weaver T.B designed and performed the experiments. van der Sluijs M.H.J. conducted data analyses and wrote the manuscript. Weaver T.B. revised the manuscript and both authors read and approved the final manuscript. Corresponding author Correspondence to VAN DER SLUIJS Marinus Disclaimer Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by Textile Technical Services and CSIRO. Funding The Australian Cotton Research and Development Corporation and CSIRO supported this work. Availability of data and materials All data generated or analysed during this study are included in this published article. Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare no competing interest References Maples RL, Miley WN, Keisling TC. Nitrogen Recommendations for Cotton and How They Were Developed in Arkansas. In: Miley WN, Oosterhuis DM, editors. Nitrogen Nutrition of Cotton: Pratical Issues. Madison, WI: American Society of Agronomy. 1990. p. 33-9. https:// doi. org/ 10. 1016/0378- 4290(93) 90060-Z. Anon. 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Crop Science. 2022;62(1):397-409. https://doi.org/ 10.1002/csc2.20679 Tables Table 1 Year, location, planting date, variety, harvest aid dates, harvest date, gin, and gin date Field Designation Location Plant date Varieties 1st Harvest aid date 2nd Harvest aid date 3rd Harvest aid date Harvest date A ACRI Narrabri, NSW 19 October 2018 Sicala V-2 Sicot 746 B3F 16 April 2019 27 April 2019 4 May 2019 04 June 2019 B Toobeah QLD 16 October 2018 Sicot 746 B3F Sicot 714 B3F 11 March 2019 20 March 2019 26 March 2019 11 April 2019 C IREC Griffith, NSW 12 October 2018 Sicot 746 B3F Sicot 714 B3F 30 March 2019 11 April 2019 01 May 2019 07 May 2019 D ACRI Narrabri, NSW 04 November 2019 Sicala V-2 Sicot 746 B3F Sicot 714 B3F 07 April 2020 20 April 2020 28 April 2020 14 June 2020 E Cecil Plains QLD 07 November 2019 Sicot 746 B3F Sicot 714 B3F 28 April 2020 10 May 2020 * 29 May 2020 Table 2 Location, N Application rate, product, method, application dates, rainfall, and max and min temperature* Field Designation N rate Kg ha − 1 Application 1 Application 2 Application 3 Rainfall (mm) Temp Max Temp Min DD Base 12 A 0, 100, 200, 300 12 September 2018 11 December 2018 * 248.5 30.9 16.9 2810 B 0, 200 & 400 12 April 2018 1 November 2018 * 227.8 34.8 19.8 2843 C 136 & 300 12 November 2018 15 November 2018 3 December 2018 220.0 30.9 16.3 2466 D 0, 100, 200 & 300 27 September 2019 17 December 2019 * 472.5 29.5 16.1 2646 E 0 & 300 2 July 2019 * * 327.6 30.7 15.8 2256 * Information for weather and day degrees were obtained from CSD data. Table 3 Lint turn out, yield, and average fibre properties as measured by HVI for Field A per N rate N rate kg.ha − 1 NUE Lint Turn Out % Yield b.ha − 1 MIC UHML (mm) UI (%) SFI (%) STR (g.tex − 1 ) Sicot 746 B3F 0 * 48.7b 7.6 4.75 30.07 84.2 5.8 31.4a 100 17.9 46.2a 7.9 4.73 30.43 84.6 5.4 33.1b 200 9.6 46.9a 8.5 4.79 30.73 85.0 5.2 33.6b 300 6.0 47.2a 7.9 4.81 30.61 84.5 5.4 33.2b p-value * < .001 n.s. n.s n.s n.s n.s < .001 Sicala V-2 0 * 41.9 7.8 4.81 29.08 83.7 5.4 31.7 100 18.8 40.8 8.3 4.74 29.29 84.2 5.2 32.5 200 9.6 41.2 8.5 4.88 29.64 84.1 5.4 32.6 300 5.8 40.2 7.6 4.82 29.57 84.5 5.1 33.0 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. Table 4 Lint turn out, yield, and average fibre properties as measured by HVI and visual assessment for Field B per N rate N rate kg.ha − 1 NUE Lint Turn Out % Yield b.ha − 1 MIC UHML (mm) UI (%) SFI (%) STR (g.tex − 1 ) Trash Colour Visual Leaf % Area Count Rd +b CG LG Sicot 746 B3F 0 * 41.3 13.7 4.50b 29.72a 81.0a 9.3a 33.2a 3 0.34b 39b 81.6b 7.4b 31 3 200 15.9 40.4 14.0 4.50b 30.48b 82.0b 9.6b 34.2b 3 0.30a 36a 80.1a 6.9a 31 3 400 7.9 41.2 14.0 4.40a 29.72a 81.0a 9.3a 33.0a 3 0.29a 36a 81.8b 7.4b 31 3 p-value * n.s. n.s. < .001 < .001 < .001 < .001 < .001 n.s. < .001 < .001 < .001 < .001 n.s. n.s. Sicot 714 B3F 0 * 39.4 14.0 4.60 29.21a 80.8a 9.8b 31.8a 3 0.33b 37a 79.6b 7.7b 31 3 200 16.1 39.8 14.2 4.60 29.97b 82.0b 9.7b 33.1b 3 0.29a 38b 78.1a 7.3a 31 3 400 8.1 39.9 14.2 4.60 29.72b 81.5b 8.7a 32.4a 3 0.34b 38b 79.4b 7.9b 31 3 p-value * n.s. n.s. n.s. < .001 < .001 < .001 < .001 n.s. < .001 < .001 < .001 < .001 n.s. n.s. Table 5 Lint turn out and average fibre properties as measured by HVI and visual assessment for Field C per N rate N rate kg.ha − 1 NUE Lint Turn Out % Yield b.ha − 1 MIC UHML (mm) UI (%) SFI (%) STR (g.tex − 1 ) Trash Colour Visual Leaf % Area Count Rd +b CG LG Sicot 746 B3F 136 18.4 41.8 11.0 4.47 31.50 83.5 7.4 34.6 3 0.28 27 82.4 7.2 31 3 300 15.4 33.8 9.2 4.42 31.06 83.3 7.6 33.5 3 0.31 28 82.4 7.2 31 3 p-value * < .001 < .001 n.s. n.s. n.s. n.s n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. Sicot 714 B3F 136 15.4 39.7 9.2 4.65 30.48 83.0 7.8 33.8 3 0.30 28 81.3 7.5 21 3 300 15.5 38.0 9.3 4.57 30.86 83.4 7.3 33.8 3 0.31 31 81.1 7.7 21 3 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s n.s n.s Table 6 Lint turn out, yield, and average fibre properties as measured by HVI for Field D per N rate N rate kg.ha − 1 NUE Lint Turn Out % Yield b.ha − 1 MIC UHML (mm) UI (%) SFI (%) STR (g.tex − 1 ) Sicot 746 B3F 0 * 46.7 8.7 4.71 29.31 82.2 8.9 30.2 100 23.8 46.2 10.5 4.65 29.77 82.0 8.5 31.2 200 10.7 46.7 9.4 4.55 30.66 82.5 7.0 32.6 300 7.1 46.4 9.4 4.45 31.01 83.4 7.0 32.4 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. Sicot 714 B3F 0 * 44.0 9.1 4.84 29.82 82.3 7. 5 30.9 100 25.2 44.1 11.1 5.01 28.96 81.6 8.7 29.4 200 13.1 43.8 11.5 5.06 29.60 82.1 8.5 30.2 300 7.6 43.5 10.1 4.71 29.31 82.2 8.9 30.2 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. Sicala V-2 0 * 41.0 6.9 4.39 29.52 82.8 7.7 31.6 100 16.6 40.8 7.3 4.36 29.80 82.7 7.4 31.7 200 8.7 40.4 7.7 4.36 29.52 83.2 6.7 31.0 300 5.1 40.1 6.7 4.10 28.85 82.0 8.8 30.2 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. Table 7 Lint turn out, yield, and average fibre properties as measured by HVI and visual assessment for Field E per N rate N rate kg.ha − 1 NUE Lint Turn Out % Yield b.ha − 1 MIC UHML (mm) UI (%) SFI (%) STR (g.tex − 1 ) Trash Colour Visual Leaf % Area Count Rd +b CG LG Sicot 746 B3F 0 * 45.1 11.3 4.09 31.01 83.4 7.0 31.9 3 0.23 19 85.3 8.8 11 1 300 8.7 43.3 11.4 4.14 31.39 83.3 6.9 32.4 2 0.22 16 84.8 8.8 11 1 p-value * n.s. n.s. n.s. n.s. n.s. n.s n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. Sicot 714 B3F 0 * 43.0 13.5 4.10 31.45 84.2 6.0 32.4 3 0.30 20 84.8 8.8 11 1 300 10.0 44.1 13.2 4.20 30.48 82.8 7.2 31.6 2 0.27 18 85.4 8.8 11 1 p-value * n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s. n.s n.s n.s Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1927381","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":127667195,"identity":"e95646ee-2cd9-47d8-9f6d-39103dd64286","order_by":0,"name":"Marinus H van der Sluijs","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACdgaGAxIMNqRoYQZrSWNgYANzDYjTAgSHSdAi38xjeMDiz3k5c/ke488FFX8Y+Nu7Exh+tuHWYnCYx+CAZNttY8s2HjPpGWcMGCTOnN3A2ItPCzNIS8PtxA3HeMyYedsMGAwkcjcw8OLRAnSYwQGJP+dAWow/8/6DaGH8i0cLA8hhEmwHQFoMpHkbIFqY8dlicJitAOiXZKBf0sqkeY4Z84D8cljmHB6HtTdv/izxx07OnPnw5s88NXJy/O29Gx++KcPjMCBglmBARAgPiDiAXwMDA+MHBuKifRSMglEwCkYoAACdOUnO+2UsmQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-3937-9236","institution":"Textile Technical Services","correspondingAuthor":true,"prefix":"","firstName":"Marinus","middleName":"H van der","lastName":"Sluijs","suffix":""},{"id":127667196,"identity":"8bb7d8c2-014e-457c-b3ea-fba7b29fdbb0","order_by":1,"name":"Timothy Weaver","email":"","orcid":"","institution":"CSIRO: Commonwealth Scientific and Industrial Research Organisation","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"","lastName":"Weaver","suffix":""}],"badges":[],"createdAt":"2022-08-04 01:18:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1927381/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1927381/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":26203750,"identity":"cc65501d-8499-46e9-8be9-a8261fa36c55","added_by":"auto","created_at":"2022-09-08 08:52:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":458327,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1927381/v1/878b15af-5871-4c96-8f9b-e8dc9dbce2ec.pdf"}],"financialInterests":"","formattedTitle":"Effect of Nitrogen Application Rates on Cotton Yield and Fibre Quality - Results from Recent Trials in Australia","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe importance of nitrogen application in cotton production in terms of plant growth, health, yield etc. are well understood and has been studied for over a century (Maples et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), with practical guidelines (Anon \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), decision support systems (Deutscher et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Gerik et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1998\u003c/span\u003e), models (Zhao et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) and recent reviews (MacDonald et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Soomro et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ali \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Khan et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) providing information on the importance of providing crops with sufficient supply of nutrients and improving nitrogen use efficiency (NUE). Unfortunately, despite the fact that the financial return to the grower in most crop production systems depends on crop quantity and quality only a limited number of studies and reviews have been published on work and knowledge relating to the effect of nitrogen (N) application rates on fibre quality, including lint turn out.\u003c/p\u003e \u003cp\u003eA recently published review concluded that the observed effects of N application rates on fibre quality were rather varied and often inconsistent (van der Sluijs \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In terms of fibre length, the majority of studies (Reynolds and Killough \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1933\u003c/span\u003e; Bennett et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; MacKenzie and Schaik \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Murray et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Koli and Morrill \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1976a\u003c/span\u003e; Shrivastava and Singh \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Boman and Westerman \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Girma et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Pettigew et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Chand et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Ebelhar et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Janat and Somi \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Bauer and Roof \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Boquet \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Fritschi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; McFarland et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Janat \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gormus \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Pettigew and Adamczyk \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Gadhiya et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Afzal et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Saleem et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Rashidi and Gholami \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hernandes-Cruz et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; McClanahan et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Read et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) concluded that increased application rates of N had no significant effect on length, with a few studies (Setatou and Simonis \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1994\u003c/span\u003e;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Ali \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Madani and Oveysi 2015) finding no clear trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Bennett et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Nelson \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1949\u003c/span\u003e; Perkins and Douglas \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Jackson and Tilt \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1968\u003c/span\u003e; Grimes et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1969b\u003c/span\u003e; Grimes et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1969a\u003c/span\u003e; Hearn \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Constable and Hearn \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Tewolde and Fernandez \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) or a negative (decrease) (Lokhande and Reddy \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sui et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) effect on fibre length.\u003c/p\u003e \u003cp\u003eSimilarly, the majority of studies (Bennett et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Murray et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Koli and Morrill \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1976a\u003c/span\u003e; Boman and Westerman \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Pettigew et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Ebelhar et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Janat and Somi \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Boquet \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Fritschi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; McFarland et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Janat \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gormus \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Pettigew and Adamczyk \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Afzal et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Saleem et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Rashidi and Gholami \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hernandes-Cruz et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; McClanahan et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Madani and Oveysi 2015; Perkins and Douglas \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Grimes et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1969b\u003c/span\u003e; Grimes et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1969a\u003c/span\u003e; Hearn \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Tewolde and Fernandez \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Sui et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hossein et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Seilsepour and Rashidi \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Leal et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) concluded that increased N application rates had no significant effect on strength, with a few studies (MacKenzie and Schaik \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Read et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Setatou and Simonis \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1994\u003c/span\u003e;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Jackson and Tilt \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1968\u003c/span\u003e; Constable and Hearn \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; Echer et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) finding no trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Girma et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Bauer and Roof \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Sui et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pettigew \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pettigew and Zeng \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Gormus et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e; Gormus and El Sagagh \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e) or a negative (decrease)(Nelson \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1949\u003c/span\u003e; Lokhande and Reddy \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Verna et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) effect on fibre strength.\u003c/p\u003e \u003cp\u003eFor micronaire the majority of studies concluded that increased N application rates had either no significant effect, or no clear trend. There were also some studies that found that N application rates either had a positive (i.e., increase) (Bauer and Roof \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Rashidi and Gholami \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Hossein et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Seilsepour and Rashidi \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Gormus et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e) or a negative (decrease)(Koli and Morrill \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e1976a\u003c/span\u003e; Ebelhar et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Janat and Somi \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Fritschi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Saleem et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; McClanahan et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hearn \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Tewolde and Fernandez \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Lokhande and Reddy \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sui et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Leal et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Echer et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Zhao et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) effect on micronaire.\u003c/p\u003e \u003cp\u003eOn the other hand, there was general agreement (Boman and Westerman \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e1994\u003c/span\u003e; Ebelhar et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Bauer and Roof \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Tewolde and Fernandez \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Sui et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Pettigew and Zeng \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) that colour in terms of reflectance and yellowness was negatively affected by increased N application rates resulting in the fibre becoming less bright and duller and possibly resulting in a reduction in the colour grade. In terms of lint turn out the majority of studies (Bennett et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Chand et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Fritschi et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Janat \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Hernandes-Cruz et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Setatou and Simonis \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e1994\u003c/span\u003e;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Nelson \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e1949\u003c/span\u003e; Perkins and Douglas \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e1965\u003c/span\u003e; Sawan et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Echer et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Scarsbrook et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e1959\u003c/span\u003e; Boman et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Phipps et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Rochester and Constable \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) concluded that N application rates did result in either a significant reduction in lint turn out, no significant effect (Shrivastava and Singh \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1988\u003c/span\u003e; Pettigew et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Ali \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) or with no clear trend (Bennett et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1967\u003c/span\u003e; Jackson and Tilt \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1968\u003c/span\u003e). There were however a small number of studies that showed that N application rate did increase (MacKenzie and Schaik \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1963\u003c/span\u003e; Gormus \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2005\u003c/span\u003e;Gadhiya et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Saleem et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Gormus et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e; Gormus and El Sagagh \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e; Verna et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) lint turn out.\u003c/p\u003e \u003cp\u003eIt was hypothesized that different varieties and growing conditions are the main reasons for these inconsistent results. With the range of different test methods and instruments and at times no indication of the test method and instrument also contributing to these differences. In order to obtain further clarification N was applied at different application rates ranging from zero to moderate to high and excessive over two years in four locations using popular high yielding (\u0026gt;\u0026thinsp;2000 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) commercial Upland cotton (\u003cem\u003eGossypium hirsutum\u003c/em\u003e L.) varieties common in the Australian cotton industry.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eThree studies were undertaken during the 2018/2019 growing season (planted in 2018; defoliated, harvested and ginned in 2019) at the Australian Cotton Research Institute (ACRI) in Narrabri (149\u003csup\u003eo\u003c/sup\u003e36\u0026rsquo;E,30\u003csup\u003eo\u003c/sup\u003e12\u0026rsquo;S) in the Namoi Valley of New South Wales (NSW), one at the Irrigation Research and Extension Committee (IREC) in Griffith (34\u0026deg;17\u0026prime;24\u0026rsquo;S 146\u0026deg;2\u0026prime;24E) in the Murrumbidgee Valley (Southern region) of NSW, and one at Toobeah (28.4169\u0026deg;S 149.8702\u0026deg;E) in the MacIntyre Valley (Central region) of Queensland (Qld). Two further studies were undertaken during the 2019/2020 growing season (planted in 2019; defoliated, harvested, and ginned in 2020); one at ACRI and one at Cecil Plains (27.5316\u0026deg;S 151.1930\u0026deg;E) on the Darling Downs in Central Qld.\u003c/p\u003e\n\u003cp\u003eA summary of the respective field operations employed on each of the fields (designated A to E) are presented in Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e \u0026amp; \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e. The cotton varieties used for the trials were two CSIRO varieties, containing Bollgard\u0026reg; 3 technology stacked with Roundup Ready Flex\u0026reg;, Sicot 746 B3F (Stiller \u003cspan class=\"CitationRef\"\u003e2016a\u003c/span\u003e) and Sicot 714 B3F (Stiller \u003cspan class=\"CitationRef\"\u003e2016b\u003c/span\u003e), currently the two most popular Upland transgenic varieties grown in Australia as well as Sicala V-2 (Reid \u003cspan class=\"CitationRef\"\u003e1995\u003c/span\u003e), a popular CSIRO conventional variety grown in the late 1990s. All fields were subjected to standard management practices for irrigated Upland cotton in Australia. N was applied in the form of granular urea and at one field as Anhydrous ammonia, all in split applications, at application rates ranging from zero (0 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to high (300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and excessive (400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). For ease of interpretation fibre properties were all measured by high volume instruments which is the preferred method of cotton classification for cotton trading (ICAC/ITMF 2018).\u003c/p\u003e\n\u003cp\u003eUrea containing 46% N was applied by side dressing to the field at ACRI (designated as A for 2018 \u0026amp; D for 2019) using a Simplicity air cart with a Gessner-Walker frame and a Shearer double disc opener prior to planting. One hundred kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was applied prior to planting followed by further application of 100 and 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively in-crop to achieve the application rate of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The field was then subjected to three harvest aid applications by ground rig, with a mixture of leaf defoliant and boll opener. The trials were conducted using a randomized complete block design, with four replications. Seed cotton from 32 plots, with four rows spaced at one meter, was harvested by a single row Case IH 1822 spindle harvester (CNH America, Racine, WI). An average of 0.234 kg of seed cotton was collected from each replicate and ginned using a 20-saw gin (Continental Eagle, Prattville, AL) with a Mitchell feeder and pre-cleaner situated at ACRI.\u003c/p\u003e\n\u003cp\u003eUrea containing 46% N was applied by side dressing to Field B using a Shearer double disc opener. One hundred and seventy five and 375 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively was applied prior to planting followed by a further application of 25 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e in-crop to achieve the application rates of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The field was then subjected to three harvest aid applications by air, with a mixture of leaf defoliant, boll opener and crop oil. The field was harvested using a grower owned and operated John Deere 7760 spindle round module harvester (Moline, IL), with Pro16 row units. Only part of the field was utilized for this trial (3.05 ha per treatment), using a randomized complete block design, with three replications. A total of sixty-four part round modules were harvested and were ginned, in sequence under standard commercial conditions, at the Namoi Cotton Limited MacIntyre No. 1 gin, situated in Goondiwindi, Qld. This gin is a Continental Eagle (Prattville, AL) high-capacity saw gin, equipped with four 181 gin stands, with no flow-through air lint cleaner and two stages of controlled-batt saw lint cleaners, capable of producing 60 bales.hour\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eUrea containing 46% N was spread across the soil surface (broadcast fertilisation) to Field C using a Marshall Multispread trailer. The IREC soil had a starting nitrate-N concentration of 136 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and there were three in-crop applications of 62 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, 40 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and 62 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e to achieve 300 kg N ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The field was then subjected to three harvest aid applications by ground rig, with a mixture of leaf defoliant and boll opener. The field was harvested using a grower owned and operated John Deere 7760 spindle round module harvester (Moline, IL), with Pro16 row units. The field utilized for this trial was sown with the two varieties using a randomized complete block design, with four replications, with each replication 0.156 ha. A total of sixteen part round modules were harvested and ginned in sequence, under standard commercial conditions, at Southern Cotton situated in Leeton, NSW. This gin is a Lummus Corporation (Savannah, GA) high-capacity saw gin, equipped with four 222 gin stands, with one stage of flow-through air lint cleaner and two stages of batt-less saw lint cleaners, capable of producing 60 bales.hour\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAnhydrous ammonia containing 82% N was applied directly into the soil of Field E prior to planting by an Excel Agriculture SP200 double row unit to achieve the application rate of 300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The field was then subjected to two harvest aids by air, with a mixture of leaf defoliant, boll opener and crop oil. The trial was conducted using a randomized complete block design, with four replications. Seed cotton from 16 plots, with 18 rows spaced at 1 meter, was hand harvested, due to the uncertainty created by COVID and accessibility to a mechanical harvester. An average of 0.234 kg seed cotton samples were collected from each replicate and ginned using the 20-saw gin (Continental Eagle, Prattville, AL) with a Mitchell feeder and pre-cleaner situated at ACRI.\u003c/p\u003e\n\u003cp\u003eFor Fields A \u0026amp; D, samples collected after ginning were subjected to objective measurement, as per ASTM D5867 (ASTM \u003cspan class=\"CitationRef\"\u003e2012a\u003c/span\u003e), using an Uster\u0026reg; Technologies AG HVI\u0026trade; 1000 (Knoxville, TN) at ACRI. Two sub samples of each sample were evaluated for fibre length in terms of upper half mean length (UHML in mm), length uniformity (UI%), short fibre index (fibres\u0026thinsp;\u0026lt;\u0026thinsp;12.7 mm) (SFI%), bundle strength in g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (STR) and micronaire (MIC). For Fields B \u0026amp; C, classing samples, from opposite sides, of each bale were collected at the gin after bale formation, with samples for Field E collected after ginning. Two sub samples were evaluated by objective measurement at commercial classing facilities including colour in terms of yellowness (+\u0026thinsp;b), reflectance (Rd) and trash in terms of leaf count, % area and leaf grade. Visual classing of the lint was also assessed for colour (CG) and visible trash (LG) according to the 2018 grades as established by USDA-AMS, as per ASTM D1684 (ASTM \u003cspan class=\"CitationRef\"\u003e2012b\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eAll fibre samples were conditioned under standard conditions of 21+/-1\u0026deg;C and relative humidity % of 65+/-2 as per ASTM D1776 (ASTM \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFor all fields, the percentage of the weight of usable fibre per the weight of un-ginned seed cotton (lint turn out) was calculated either by the commercial ginning operators or by technicians at ACRI.\u003c/p\u003e\n\u003cp\u003eNUE was also calculated for evaluating efficiency of the conversion of N fertiliser into cotton lint as per Eq.\u0026nbsp;1.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAWsAAABFCAYAAACMl8eKAAALaElEQVR4nO3dvW7iTBcH8OP3MlZRhGxfwxYRpEjBcAEpcCqqSHa9wk3KNEZbY4kq1eIiF4ApUsQoRa4htqLVam/DT5F3Zmf8bUJCDP+flCLgjxkDh5nxMEdL0zQlAAD40v637wIAAEA9BGsAgA5AsAYA6AAEawCADkCwBgDoAARrAIAOQLAGAOgABGsAgA5AsAYA6AAEawCADkCwBgDoAARrAIAOQLAGAOgABGsAgA5AsAYA6AAEawCADkCwBgDoAARrAIAOQLAGqDEajWg0Gu27GHDkEKwPVBAEZJrm3s4/Go1oNpuVPp8kCWmapmzvOM5Ozq1pGgVBsJNjjUYjmkwmymP7vrbw9TmOU/n+l202G+WzUKZRsHYchzRNy508CALlJNn/ZdkPkKZpub+mldsVHjA2m03uObSmPtb9/T3Ztr3vYtRarVb0/ft35bHxeExEtLMvBDg8vu/T5eVl7nFN03Jxpd/vE2OsNv41blkbhkGu61KSJE13qbVcLilNU/E3nU53duzP1vTbEd4sFgu6urradzG2NhwO6fHxcd/FgC8oCAJijJGu6+KxuvhwcXFBDw8PlcdtHKxN0yTGGP38+bPpLp22Wq1otVrtuxgHabPZUBzH1O/3912UHN6LrPvivbq6It/3P6lU0CV3d3d0cXGhPDYYDMjzvNLe5OXlJYVhWNkYbjVmfXNzQ77vFw4bfBT+jVT095HlcBxH6a7w8xWdfzab0WAwENtpmlZ40R3HEX98O/kc/Ph8OEkeF53NZsq5s+O7fJ+yQFM0JmyaptKVzx5DrkP2/NlrPxqNSsuW9fT0RIZhVG5jmqZybeTjNx02M02ztLzZ+vC6zudz0dOr8u3bNyKiT/0sQDeEYUinp6fKY3UjB7wV/vz8XLpNq2DNx1Zub2/b7FbKsqzKAMPPKQ+VyH+f3TIbDAYUxzGlaUqe54kAPZ1OKYoiIiJRNrkLJPN9n3q9ntguDMNccLu5uaE0Tenl5YWI3gKL67pK3X3fF/ttNhuyLEsMK8VxTJZltapbEARkWZaoXxRF4vjZ80dRRIPBQAQ4x3EoDEPxfK/XozAMS8/1+vpaeYPONE0aDoeiZzObzejl5UUcnzFGtm1Xvvkty6L1ep17rfjxiP69VrZt03A4LDzOaDQiwzAoDEMl6PPX98+fP6VlgOPDPxMnJyet9zUMg37//l36fOvZIPP5nMIw3EmLIjtm/dUtl0vxIT07OyMiaj2GzxhTgoznebRer5Vtsv+7rkvL5VJ5TN6Pt1T5jS9d13Pb17m7uyPbtkX9+v2+CJaLxUI5Xr/fJ8Mw6P7+XpTX8zzx/HQ6JcZY5fnKvsxM06Tr62uaz+fisYeHB7q+vhb/X1xc1F73qtdqOp0qr8H5+TnFcVx4nNVqVdpAqOsdwPHiPa826mYYtQ7Wuq6Tbdu56UxE9d8m23zb7GsYpM42L0aRbHepTPbanZ6eigBT11JtqtfrFT7OW+rytZeDWxzHjetRxff9wqCp67py82WxWJQG+yJFr5U8RNK2FwKwD1vNs/7x4wfFcUx3d3fK42XjePz/bQLcVxoG+QhV3R5Ztrv9+/dv0bIrC7KyJsHt9fW18HHDMHK9IHkMbpsWZlHL2LZtiqKIXNfNvYf4MAQfy5db3m2NRiMaDoeiHm17IVxZaxzg79+/rffhw55ltgrWuq6T53m5cUld14kxlmt1TyaT3FSWQ1XXPQ/DULkx5rqu0sUvYtt2rvUn73d2dqYMTfExbFmv11NmLziOowSbyWRCvu+L8idJIm7wDYdDurm5KS1f9nk+hl2m1+uVvjH7/b4YY+ZlWa/XFEWRCK7ZWTrZm5F1sufONjqaeM/YJByu99zLqOuhbv0LxrKbO6vVSuliapqm3CySZbvWu/oFW1uDwaB0FkRT/OarYRiVx2CM0evrqzhX3Y0yorf7BIwxpYye54n95ACnaRpNJhNxw5ObTqeibJqmUa/XU8aVx+MxeZ4ntjEMQ7Re5/M5DYfD3DCUPIOCiJRjV/3g5ezsjOI4Lr1G0+mUbNsWLfa7u7vca/SeHyyt12vyfV8cKzvNqgl+1/4QenewW4yx3Bx8/l7zfV/0EuWhS97Qyv4AS5HCp7FtO2WM7bsYXwIRpcvlsvG2URRtvf9HwGsJZTzPSw3D2Pk+WBsE9sK27Ua/AOStb/l+x1cYgliv14U32QEuLy8re45FsjOeimhp2oE5cx8APw2HLjvSj21n8CHdJjfCkyQhwzBqX9OjDdYAAF2CYRAAgA5AsAYA6AAEawCADkCwBgDoAARrgC+CL1G7ywQfcDgQrFvYxa/nmjBN89NTnH2W7Drh79UkH+JoNBLrdlelnmtrl3UJgoAeHx9zqxXue8Ey+DqOLliX/aS8LmGr4zjEGCtcm+K9HMcpDTh81cFD/cB+dO7NJEkoDEOxfOxXNR6PC+fkep63s/XjoduOLlgTva0S13YdkiRJtlpDIms2myER7yfqSmLeMnyRLoCjDNbX19etEyjULV/4HvP5vHIVuvRAloMtkn5wouTFYkHn5+cfdvxtyeu0V2VJ54kekEkdjjJYn56eliZQyEqSRCy277quMiSRTYwgd+d5C5rnW+Tjm67r5lbdms1mpcMg/Pz8nPz/opUKq56ryu9YdL6iOvHx4ap8j0W5KqsCTXZ8vqoOvAx1qeDkY8VxXLmGCM/FyIfFssevulbZYxSVt+x6yuu01w3RmKaJTOpwfKvu0f9Xa4vjWFm5jTGW2rZdup9hGKnneeL/KIpyq8HJx/M8LyWi3DE9z8ut1pZdcUs+Fy8nPw9jTCkHl61P9ji8vFUre8VxrDyfreNyuUyJSCk/Y0zZh4hSIkrjOFb24cfIrlZXVNe6OvDn+fZldeLb87LI5UnTf69R9hpm61vGtu2UiErLX3c9Zfxc/E9+32CFP0jTI151jydQqFpUv8qvX7/Itm1leMK2bWUhe3lN6F2SU1xx9/f3xBhTWmnX19e0WCyU7bL5HWW6rivDMbxu2YXU5RusNzc3uRXG5PyH4/GYDMOgp6en2nrV1WHbXJNFSS9msxktFgtl8Zzn52cyDEPUm68tXDWVTs6pqeu6kvS06fUkertOqZSFR37fNMkEBIfvaIM10dsi93EcbzUbIUkSZQF7vrD4R+OBMjur5fX1VUl9pWkaua7b+vhyl77JFLcmqdqa5oesq8Ouck0SUeG1OTk5Ub54eELgNhmOsuVrez0Byhx1sCZ6mxq1TVDjiYPTTF7CXU/rK8IzbvPMLkQkMr9ky9PmxmgQBOS6bquM801yzTUtQ10dtm1hFrWMed2KZgXxbDmu674rz+I217NIWW5MOC5HH6x5uqu206POz8+VnIVt7GpmyenpqQjW2TyM28gm7y27MShPPby9vc3l17QsS7lhF8cxXV5e1p6/rg5Nck3KeKu/7AuFp/fiPaunp6fcF7Bcr+zNyDpNr2edJEmOIn8pVDv6YE1EW/3oYDwe03K5VPIa1s18IPo39NJklkER+VyWZYkx6H6/T1EU5XIVthnimU6nSq7Hx8fHwszlk8lEbPPy8pLrTcjXxbIsiqKoUbCpq0OTXJMyPoZcNl6u67rIph4EAU2nU1qv16W5Jttqej3rhGH4JacfwudC8gFoLAgCsiyrsjuvaRotl8sv84tBx3EoSZJGw1NF2T3a7P8RNpsNDQYDiuMYresjh5Y1HLSrq6vGQ1xJkuTGxfc9BPH09JQbZoLjhGANB63f7xNjrNFw0Gq1Ej98kmdvfMT0y6YWi8XW00vhsGAYBACgA9CyBgDoAARrAIAOQLAGAOgABGsAgA5AsAYA6AAEawCADkCwBgDoAARrAIAOQLAGAOgABGsAgA5AsAYA6AAEawCADkCwBgDoAARrAIAO+A8T304b9qigaAAAAABJRU5ErkJggg==\"\u003e\u003c/p\u003e\n\u003cp\u003eA NUE of 13 to 18 kg lint/kg of N is recommended for irrigated cotton, with values below 13 indicating that too much N was applied and values above 18 indicating that insufficient N was applied (Rochester \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eTo test for statistical differences between treatment means, ANOVA was conducted on the experimental data using Genstat 16.0 (Lawes Agricultural Trust, IACR Rothamsted, UK). Means for each parameter followed by a different letter are significantly different at p\u0026thinsp;\u0026le;\u0026thinsp;0.05, with non-significant differences designated as n.s.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eTables 3 to 7 summarize the NUE,\u0026nbsp;lint turn out, yield as well as fibre quality as measured by objective measurement using an HVI instrument for all fields (A to E), with visual assessment also conducted for the larger/commercial trials for two fields (B and C), as well as the hand harvested field (E).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eACRI (A \u0026amp;D)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 shows that there were statistically significant differences between the four N application rates for lint turn out and fibre strength for Sicot 746 B3F. At 48.7% the highest lint turn out was obtained from 0 kg.ha\u003csup\u003e-1\u003c/sup\u003e, whereas the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, resulted in slightly stronger fibre than that achieved for 0, 100 and 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e, respectively. Although not significant, the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, produced slightly longer and uniform fibre. The application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e also resulted in the highest average yield of 8.5 bales.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003e(bale = 227 kg), which was 0.9, 0.6 and 0.6 bales.ha\u003csup\u003e-1\u003c/sup\u003e more than that achieved for 0, 100 and 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e respectively, although 100 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieved the most desirable NUE of 18.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no statistically significant differences between the four N application rates for lint turn out and fibre properties for Sicala V-2. The results did, however, indicate that overall, the most favourable results were obtained with the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, which also resulted in the highest average yield of 8.5 bales.ha\u003csup\u003e-1\u003c/sup\u003e, which was 0.7, 0.2 and 0.9 bales.ha\u003csup\u003e-1\u003c/sup\u003e more than that achieved for 0, 100 and 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e respectively, whilst 100 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieved\u003csup\u003e\u0026nbsp;\u003c/sup\u003ethe most desirable NUE of 19. Similarly, the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, resulted in producing the longest and amongst the most uniform, and strong fibre.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 6 shows that there were no statistically significant differences between the three N application rates for lint turn out and fibre properties for all three varieties. The results for Sicot 746 B3F did, however, indicate that overall, the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, resulted in the strongest and one of the most uniform and even fibres produced with\u003csup\u003e\u0026nbsp;\u003c/sup\u003eone of the highest lint turn out \u0026nbsp;(46.7%), although 100 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieved the highest yield at 10.5 b. ha\u003csup\u003e-1\u003c/sup\u003e. The NUE for all applications were mostly either too high or low for the yield achieved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results for Sicot 714 B3F indicated that overall, 0 kg.ha\u003csup\u003e-1\u003c/sup\u003e produced the longest, uniform, and strongest fibre with the highest lint turn out (44.0%), whilst 200 \u0026amp; 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e produced the highest yield, with 200 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieving the better NUE of 13. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe results for Sicala V-2 indicated that overall, 100 kg.ha\u003csup\u003e-1\u003c/sup\u003e produced the longest, strongest and amongst the most \u0026nbsp;uniform fibre, with amongst the highest lint turn out (40.8%), and with 200 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieving the highest yield (7.7 bales.ha\u003csup\u003e-1\u003c/sup\u003e) whilst 100 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003eachieved\u003csup\u003e\u0026nbsp;\u003c/sup\u003ethe most desirable NUE of 17.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eToobeah (B)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 4 shows that there were statistically significant differences between the three N application rates for most fibre properties for both Sicot 746 B3F and Sicot 714 B3F.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn terms of Sicot 746 B3F, overall, the best fibre quality was achieved with 200 kg.ha\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003ewhich \u0026nbsp;resulted in a slight, but statistically significantly longer, uniform, and stronger fibre and although the colour and trash values, as measured by HVI, were marginally, but statistically significantly better, did not improve the visual determined colour and leaf grade, which was 31-3. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no statistically significant differences in lint turn out between the three N applications. At a yield of 14.0 bales.ha\u003csup\u003e-1\u003c/sup\u003e, the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e also produced amongst the highest yield with an NUE of 16, although at a lower lint turn out.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilar results were obtained for Sicot 714 B3F, where overall, the best fibre quality was also achieved with 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, resulting in a marginal, but statistically significantly, longer, uniform, and stronger fibre and although the colour and trash values, as measured by HVI, were also slightly, but statistically significantly better, did not improve the visual determined colour and leaf grade which was 31-3. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere were no statistically significant differences in lint turn out between the three N applications. At a yield of 14.2 bales.ha\u003csup\u003e-1\u003c/sup\u003e, the application of 200 kg.ha\u003csup\u003e-1\u003c/sup\u003e, also produced amongst the highest yield and lint turn out, with an NUE of 16.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIREC (C)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 5 shows that there were no statistically significant differences between the two application rates for all the fibre properties \u0026nbsp;for both \u0026nbsp;varieties although the application of 136 kg.ha\u003csup\u003e-1\u003c/sup\u003e did produce a marginally longer, uniform, and stronger fibre for Sicot 746 B3F.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe accurate determination of \u0026nbsp;lint turn out at commercial gins require the gin to completely run out prior to commencing the next batch and if this is not strictly adhered to results can be wrong and misleading. Certainly, the results for lint turn out and as a consequence yield and NUE for Sicot 746 B3F are therefore questionable. The results for Sicot 714 B3F were judged to be more realistic \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCecil Plains (E)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 7 shows that there were no statistically significant differences between 0 and 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e for all of the fibre properties for both Sicot 746 B3F and Sicot 714 B3F. Similarly, there were no practical differences in lint turn out and yield between 0 and 300 kg.ha\u003csup\u003e-1\u003c/sup\u003e for both varieties, although Sicot 714 B3F achieved higher yields and as a consequence favourable NUE.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eGrowing Season\u003c/p\u003e \u003cp\u003eThe three studies conducted during the 2018/2019 growing season all experienced hot and warm weather, with the number of days above 36\u0026deg;C and 40\u0026deg;C and the number of nights above 25\u0026deg;C all above average with below average rainfall. As can be seen in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, this resulted in the accumulation of high and above average day degrees in the 2400 to 3000 category which in Australia is considered as very good growing conditions (Anon \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) having a positive effect on fibre quality specifically micronaire and colour (Luo et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Bange et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Similarly, the two studies conducted during the 2019/2020 growing season also experienced hot and warm weather, with the number of days above 36\u0026deg;C and 40\u0026deg;C and the number of nights above 25\u0026deg;C and rainfall experienced in Narrabri all above average. Although this resulted in the accumulation of slightly lower day degrees it was still considered as very good growing conditions. Cecil Plains, however, did not record any nights above 25\u0026deg;C and experienced more than double the number of cold shock days than the average and received less than average rainfall. This resulted in the accumulation of slightly lower day degrees in the 1800 to 2400 category which is considered in Australia as normal growing conditions.\u003c/p\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eThe average yield for the 2018/19 for the three varieties was variable with Sicot 714 B3F achieving the highest yield of 12.2 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e followed by Sicot 746 B3F at 10.4 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and Sicala V-2 with 8.1 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. With the exception of the Sicala V-2, these yields were either above or in line with the average cotton yields achieved in Australia for irrigated cotton during that time (Anon \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough lower than the two current most popular varieties currently grown in Australia at almost 8 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e the yield for Sicala V-2 a conventional variety grown in the 1990s can still be considered as exceptional.\u003c/p\u003e \u003cp\u003eThe average yield for the 2019/20 for the three varieties was 11.4 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e for Sicot 714 B3F followed by Sicot 746 B3F at 10.1 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e and Sicala V-2 with 7.2 bales.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Which again with the exception of the Sicala V-2, were above the average cotton yields achieved in Australia.\u003c/p\u003e \u003cp\u003eBearing these yields in mind the suggested amount of N required to achieve the average yields above for the three varieties was 200, 180 and 120 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e respectively, to achieve the recommended NUE of 13 to 18, This result was similar to previous studies conducted in Australia that concluded that the application of N above 200 to 250 kg. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e did not result in increased yields (Buster \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e,\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003eb\u003c/span\u003e,\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003ec\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). With higher application rates resulting in no economical benefit to the grower and possibly leading to higher costs (i.e., increased defoliation and plant growth regulator applications) and quality downgrades. This equates to an average of 14 to 15 kg of N for the current most popular Upland transgenic varieties grown in Australia for each bale of lint produced.\u003c/p\u003e \u003cp\u003eLint turn out\u003c/p\u003e \u003cp\u003eThe lint turn out results for the five trials were variable with only the small scale trials (Fields A \u0026amp; D) at ACRI and to a lesser extend at Cecil Plains (Field E) achieving the expected lint turn out (47% for Sicot 746 B3F, 45% for Sicot 714 B3F and 39% for Sicala V-2 (Stiller \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e; \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e; Reid \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). The lint turn out for the larger commercial trials (Fields B \u0026amp; C) that were ginned at high capacity throughput gins were lower. This was not entirely unexpected as these gins, as do most modern gins, have either two and three stages of lint cleaning as part of their processing system to remove foreign matter left in the lint after the seed cotton cleaning and ginning stages. With a recent study showing that lint cleaners can reduce bale weights by up to 27 kg and reduce lint turn out by up to 2% (van der Sluijs \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). As highlighted earlier the results for Sicot 746 B3F from Field C were questionable and hence not included in this discussion.\u003c/p\u003e \u003cp\u003eOverall, although there was no statistically significant effect of N application rate on lint turn out, there does seem to be a trend in a decrease in lint turn out with increased N application rates. This is consistent with previous studies that showed that in general increased N application rates led to reduced lint turn out (van der Sluijs \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFibre Quality\u003c/p\u003e \u003cp\u003eThe fibre quality results for the five trials were either equivalent or better than the Australian base grade, which is length of 28.7 mm (36 32nds), length uniformity 81%, strength 29 g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, micronaire range 3.5 to 4.9 (G5), colour 31(Middling) and trash grade of 3, with short fibre content % preferably\u0026thinsp;\u0026lt;\u0026thinsp;9.0%. Base grade refers to the grade of cotton that is used by cotton merchants as a basis for contracts and to determine premiums, and discounts.\u003c/p\u003e \u003cp\u003eExcept for Field B, there were no statistically significant differences in fibre length with an increase in N. The results for Field B for both varieties showed significant improvement in length by one grade (37 to 38 32 nds), with the application of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with a reduction in length with the application of 400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Similarly, length uniformity and short fibre content followed the same trend, with length uniformity improving and short fibre content decreasing with the application of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Although, not statistically significant Field A, followed a similar trend, with the results for Fields C, D \u0026amp; E more varied with either 0, 100, 136, 200 or 300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e producing the longest and most uniform fibre. These results are not entirely unexpected as it is a well-known fact that fibre length is primary a genetic trait and with the near perfect growing conditions experienced the application above NUE will not result in an improvement in fibre length, uniformity or short fibre % (van der Sluijs \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eExcept for fields, A \u0026amp; B, there were no statistically significant differences in fibre strength with increased N application rates. The results for Field A for only Sicot 746 B3F and for both varieties from Field B, showed a slight but significant improvement in fibre strength (1 g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) with the application of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with a statistically significant reduction in fibre strength with increased application rates. This increase in strength corresponded to an NUE between 13 and 16. The results for Fields C,D \u0026amp; E and Sicala V-2 from Field A was more varied with either 0, 100, 136, 200 or 300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, producing the strongest fibre. Again, this is not surprising as fibre strength is also primarily a genetic trait and with the growing conditions and management the application above NUE would not have resulted in an improvement in fibre strength. It is also likely that the results for Fields A,D \u0026amp; E were ginned on a laboratory size gin without lint cleaning which may have influenced the results (van der Sluijs \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApart from Field B, there were no statistically significant differences in micronaire with an increase in N application rates. The results for Field B for only Sicot 746 B3F showed a slight reduction in micronaire with the application of 400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Although, not statistically significant the micronaire values for Fields C \u0026amp; D also reduced slightly with increased N application whereas the micronaire value increased slightly with N application rates for Fields A \u0026amp; E. All the changes were of little practical significance as all the micronaire values were within the Australian base grade. These results were not unsurprising as the two growing seasons were considered to be ideal and exceptional resulting in the accumulation of above average day degrees and hence favourable micronaire values (Bange et al \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eApart from Field B, there were no statistically significant differences in HVI colour measurements with an increase in N application rates. The results for Field B for both varieties showed a reduction in Rd and +\u0026thinsp;b with the application of 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, with both Rd and +\u0026thinsp;b improving with the application of 400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. This change in the colour measurements were of little practical significance as at 31 the visual grade was equal to the Australian base grade. The colour measurements for Fields C \u0026amp; E were varied with no changes to the visual colour grade. Interestingly, with a colour grade of 21 (Strict Middling), Sicot 714 B3F was one grade better than Sicot 746 B3F. The colour and trash grade for both varieties from Field E were exceptional; graded as 11 (Good Middling) with a leaf grade of 1. This was not entirely unexpected as this cotton was harvested by hand and hence was free from impurities and trash as highlighted by the HVI trash results.\u003c/p\u003e "},{"header":"Conclusions","content":"\u003cp\u003eThe importance of N application in the cotton production system is well understood. What is poorly understood is what the effect of N application rates are on fibre quality, including lint turn out, with previous studies reporting varied and inconsistent results. In order to obtain further clarification N was applied either in the form of granular urea or Anhydrous ammonia in split applications either before or in-crop at application rates ranging from zero (0 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to high (300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and excessive (400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). Trials were conducted in 2018 and 2019 in four locations using two popular transgenic and one conventional Upland cotton varieties common in the Australian system.\u003c/p\u003e \u003cp\u003eResults indicated that in general, the application of moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) rates of N resulted in the highest yield and desired NUE in the range of 13 to 18, which equates to an average of 14 to 15 kg of N for each bale of lint produced from the transgenic varieties currently used in Australia.\u003c/p\u003e \u003cp\u003eFurthermore, the results showed that the application of moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) rates of N resulted in the highest yield, lint turn out and NUE and also produced the longest, uniform, and strongest fibre. As the growing conditions for the two seasons were closely aligned, N application rates did not influence micronaire but did negatively affect colour and lint turn out. Under these conditions there was not a variety effect. Certainly, more veritable, challenging and less than ideal growing conditions would no doubt report different conclusions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the generous cooperation of Ella Arnold from Cotton Seed Distributors Limited for providing information on climatical conditions experienced at the various trial sites.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTextile Technical Services, 35 Helena Street, Belmont, Geelong, Victoria, 3216, Australia Deakin University,\u0026nbsp;Pigdons\u0026nbsp;Road,\u0026nbsp;Waurn\u0026nbsp;Ponds, Geelong, Victoria, 3216, Australia\u003c/p\u003e\n\u003cp\u003eVAN DER SLUIJS, Marinus, H.J.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCSIRO Agriculture \u0026amp; Food, 21888\u0026nbsp;Kamilaroi\u0026nbsp;Highway, Myall Vale, NSW, 2390, Australia\u003c/p\u003e\n\u003cp\u003eWEAVER, Timothy, B.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWeaver T.B designed and performed the experiments. \u0026nbsp;van der Sluijs M.H.J. conducted data analyses and wrote the manuscript. Weaver T.B. revised the manuscript and both authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to VAN DER SLUIJS Marinus\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclaimer\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by \u0026nbsp;Textile Technical Services and CSIRO.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Australian Cotton Research and Development Corporation and CSIRO supported this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interest\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMaples RL, Miley WN, Keisling TC. Nitrogen Recommendations for Cotton and How They Were Developed in Arkansas. In: Miley WN, Oosterhuis DM, editors. Nitrogen Nutrition of Cotton: Pratical Issues. Madison, WI: American Society of Agronomy. 1990. p. 33-9. https:// doi. org/ 10. 1016/0378- 4290(93) 90060-Z.\u003c/li\u003e\n\u003cli\u003eAnon. Nutripak- A Practical Guide to Cotton Nutrition. Narrabri, NSW: Australian Cotton Cooperative Research Centre; 2001. p. 65.\u003c/li\u003e\n\u003cli\u003eDeutscher SA, Bange MP, Rochester IJ. Testing NutriLOGIC, a Decision Aid for Nitrogen Fertiliser Management in Cotton. 10th Agronomy Conference; Hobart, TAS, Australia. 2001. p. 5.\u003c/li\u003e\n\u003cli\u003eGerik TJ, Oosterhuis DM, Torbert HA. Managing Cotton Nitrogen Supply. Advances in Agronomy. 1998; 64: 115-47. https:// doi. org/ 10. 1016/ S0065- 2113(08)60503-9.\u003c/li\u003e\n\u003cli\u003eZhao S, Wang C, Segarra E, et al. Multidimensional Quality Attributes and Input Use in Cotton. Beltwide Cotton Conference; New Orleans, LA. 2010. p. 482-7.\u003c/li\u003e\n\u003cli\u003eMacDonald BCT, Latimer JO, Schwenke GD, et al. The Current Status of Nitrogen Fertiliser Use Efficiency and Future Research Directions for the Australian Cotton Industry. Journal of Cotton Research. 2018; 1: 1-15. https:// doi. org/ 10. 1186/s42397- 018- 0015-9.\u003c/li\u003e\n\u003cli\u003eSoomro AW, Keerio A, Khuhro SN. An Overview of Factors Affecting on Cotton Production International Journal of Cotton Reseach and Technology. 2020;2(1): 9.\u003c/li\u003e\n\u003cli\u003eAli N. Review: Nitrogen Utilization Features in Cotton Crop. American Journal of Plant Sciences. 2015; 6: 987-1002. https:// doi. org/ 10. 4236/ ajps. 2015. 67105.\u003c/li\u003e\n\u003cli\u003eKhan A, Tan DKY, Afridi MZ, et al. Nitrogen Fertility and Abiotic Stresses Management in Cotton Crop: a Review. Environmental Science and Pollution Research. 2017;24(17): 14551-66. https:// doi. org/ 10. 1007/ s11356- 017- 8920-x.\u003c/li\u003e\n\u003cli\u003evan der Sluijs MHJ. Effect of Nitrogen Application Level on Cotton Fibre Quality. Journal of Cotton Research. 2022; 5(9): 35. https://doi.org/10.1186/s42397-022-00116-9\u003c/li\u003e\n\u003cli\u003eReynolds EB, Killough DT. The Effect of Fertilizers and Rainfall on the Length of Cotton Fiber. Agronomy Journal. 1933; 25(11): 756-64. https:// doi. org/ 10. 2134/agron j1933. 00021 96200 25001 10004x.\u003c/li\u003e\n\u003cli\u003eBennett OL, Erie LJ, MacKenzie AJ. Boll, Fiber, and Spinning Properties of Cotton as Affected by Management Practices. Washington, DC, USA: USDA-ARS; 1967. p. 115.\u003c/li\u003e\n\u003cli\u003eMacKenzie AJ, Schaik PH. Effect of Nitrogen on Yield, Boll, and Fiber Properties of Four Varieties of Irrigated Cotton. 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Beltwide Cotton Conference; Nashville, TN. 1996. p. 1373-9.\u003c/li\u003e\n\u003cli\u003eJanat M, Somi G. Comparative Study of Nitrogen Fertilizer Use Efficiency of Cotton Grown under Conventional and Fertigation Practices Using N Methodology. Vienna, Austria: International Atomic Energy Agency; 2002. p. 85-98.\u003c/li\u003e\n\u003cli\u003eBauer PJ, Roof ME. Nitrogen, Aldicarb, and Cover Crop Effects on Cotton Yield and Fiber Properties. Agronomy Journal. 2004; 96(2): 369-76. https:// doi. org/ 10.2134/ agron j2004. 3690.\u003c/li\u003e\n\u003cli\u003eBoquet DJ. Cotton in Ultra-Narrow Row Spacing: Plant Density and Nitrogen Fertilizer Rates. Agronomy Journal. 2005; 97(1):279-87. https:// doi. org/ 10. 2134/agron j2005. 0279.\u003c/li\u003e\n\u003cli\u003eFritschi FB, Roberts BA, Travis RL, et al. Response of Irrigated Acala and Pima Cotton to Nitrogen Fertilization: Growth, Dry Matter Partitioning, and Yield. 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Nitrogen and Boron Effects on Yield and Quality of Cotton (\u003cem\u003eGossypium hirsutum\u003c/em\u003e L.). International Research Journal of Agricultural Science and Soil Science. 2011; 1(4): 118-25.\u003c/li\u003e\n\u003cli\u003eHernandes-Cruz AE, Sanchez E, Preciado-Rangel P, et al. Nitrate Reductase Activity, Biomass, Yield, and Quality in Cotton in response to Nitrogenous Fertilization. Phyton - International Journal of Experimental Botany. 2015; 84(2): 429-35.\u003c/li\u003e\n\u003cli\u003eChen J, Liu L, Wang Z, et al. Nitrogen Fertilization Effects on Physiology of the Cotton Boll - Leaf System. Agronomy 2019; 9(6): 271-87.\u003c/li\u003e\n\u003cli\u003eMcClanahan S, Frame WH, Stewart RD, et al. Cotton Yield and Lint Quality Responses to Nitrogen Rate and Placement in the Humid Southeast. Agronomy Journal. 2020; 112(5): 4276-86. https:// doi. org/ 10. 1002/ agj2. 20290.\u003c/li\u003e\n\u003cli\u003eSawan ZM, Mahmoud MH, Momtaz OA. Influence of Nitrogen Fertilization and Foliar Application of Plant Growth Retardants and Zinc on Quantitative and Qualitative Properties of Egyptian Cotton (\u003cem\u003eGossypium barbadense\u003c/em\u003e L. Var. Giza 75). Journal of Agricultural and Food Chemistry. 1997; 45(8): 3331-6.\u003c/li\u003e\n\u003cli\u003eRead JJ, Reddy KR, Jenkins JN. Yield and Fiber Quality of Upland Cotton as Influenced by Nitrogen and Potassium Nutrition. European Journal of Agronomy. 2006; 24(3): 282-90. https:// doi. org/ 10. 1016/j. eja. 2005. 10. 004.\u003c/li\u003e\n\u003cli\u003eSetatou HB, Simonis AD. Response of Cotton to NPK Fertilization - The Creek Experience. World Cotton Research Conference - 1; Brisbane, QLD. 1994. p. 147-51.\u003c/li\u003e\n\u003cli\u003eSetatou HB, Simonis AD. Effect of Time and Rate of Nitrogen Application on Cotton. Fertilizer Research. 1995; 43: 49-53. https:// doi. org/ 10. 1007/ BF007 47682\u003c/li\u003e\n\u003cli\u003eAli N. 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The Journal of Agricultural Science. 1976; 86(2): 257-69. https:// doi. org/ 10. 1017/S0021 85960 00547 1X.\u003c/li\u003e\n\u003cli\u003eConstable GA, Hearn AB. Irrigation for Crops in a Sub-Humid Environment VI. Effect of Irrigation and Nitrogen Fertilizer on Growth, Yield and Quality of Cotton. Irrigation Science. 1981; 3(1): 17-28. https:// doi. org/ 10. 1007/ BF002 51380\u003c/li\u003e\n\u003cli\u003eTewolde H, Fernandez CJ. Fiber Quality Response of Pima Cotton to Nitrogen and Phosphorus Deficiency. Journal of Plant Nutrition. 2003; 26(1): 223-35. https:// doi.org/ 10. 1081/ PLN- 12001 6506\u003c/li\u003e\n\u003cli\u003eSawan ZM, Mahmoud MH, El-Guibali AH. Response of Yield, Yield Components, and Fiber Properties of Egyptian Cotton (\u003cem\u003eGossypium barbadense\u003c/em\u003e L.) to Nitrogen Fertilization and Foliar-applied Potassium and Mepiquat Chloride. The Journal of Cotton Science. 2006; 10(3): 224-34.\u003c/li\u003e\n\u003cli\u003eLokhande SB, Reddy KR. Cotton Reproductive and Fiber Quality Responses to Nitrogen Nutrition. International Journal of Plant Production. 2015; 9(2): 191-210. https:// doi. org/10. 22069/ IJPP. 2015. 2044\u003c/li\u003e\n\u003cli\u003eSui R, Byler RK, Delhom CD. Effect of Nitrogen Application Rates on Yield and Quality in Irrigated and Rainfed Cotton. The Journal of Cotton Science. 2017; 21(2): 113-21.\u003c/li\u003e\n\u003cli\u003eHossein RS, Eskandari M, Rezaei H. A Study of Nitrogen and Boron Impacts on Yield and Significance of Cotton (\u003cem\u003eGossypium hirsutum\u003c/em\u003e L.). African Journal of Environmental Economics and Management. 2014; 2(3): 188-94.\u003c/li\u003e\n\u003cli\u003eSeilsepour M, Rashidi M. Effect of Different Application Rates of Nitrogen on Yield and Quality of Cotton (\u003cem\u003eGossypium hirsutum\u003c/em\u003e). American-Eurasian Journal of Agriculture and Environmental Sciences. 2011; 10(3): 366-70.\u003c/li\u003e\n\u003cli\u003eLeal AJF, Piati GL, Leite RC, et al. Nitrogen and Mepiquat Chloride can affect Fber Quality and Cotton Yield. Revista Brasileira de Engenharia Agr\u0026iacute;cola e Ambiental. 2020; 24(4): 238-43. https:// doi. org/ 10. 1590/ 1807- 1929/ agria mbi. v24n4p238- 243\u003c/li\u003e\n\u003cli\u003eEcher FR, dos Santos CF, de Jesus E, et al. The Effects of Nitrogen, Phosphorus, and Pottasium Levels on the Yield and Fiber Quality of Cotton Cultivars. Journal of Plant Nutrition. 2020; 43(7): 921-32. https:// doi. org/ 10. 1080/ 01904 167. 2019.17022 04\u003c/li\u003e\n\u003cli\u003eZhao W, Wang YH, Zhou ZG, et al. Effect of Nitrogen Rates and Flowering Dates on Fiber Quality of Cotton (\u003cem\u003eGossypium hirsutum\u003c/em\u003e L.). American Journal of Experimental Agriculture. 2012; 2(2): 133-59. https:// doi. org/ 10. 9734/ AJEA/ 2012/ 954\u003c/li\u003e\n\u003cli\u003ePettigew WT. Irrigation and Nitrogen Fertility Effects on Cotton Yield and Fiber Quality. 15 th Annual National Conservation Systems Cotton \u0026amp; Rice Conference; Tunica, MS. 2012. p. 16-7.\u003c/li\u003e\n\u003cli\u003ePettigew WT, Zeng L. Interactions among Irrigation and Nitrogen Fertility Regimes on Mid-South Cotton Production. Agronomy Journal. 2014; 106(5): 1614-22. https:// doi. org/ 10. 2134/ agron j13. 0457\u003c/li\u003e\n\u003cli\u003eGormus O, El Sabagh A, Islam MS. Optimizing Yield and Fiber Quality of Cotton under Mediterranean Enviroment: Managing Nitrogen and Potassium Nutrition. Journal of Experimental Biology and Agricultural Services. 2016a; 4(5): 572-80. https:// doi. org/ 10.18006/ 2016. 4(5S). 572. 580.\u003c/li\u003e\n\u003cli\u003eGormus O, El Sagagh A. Effect of Nitrogen and Sulfur on the Quality of the Cotton Fiber under Mediterranean Conditions. Journal of Experimental Biology and Agricultural Services. 2016b; 4(6): 662-9.\u003c/li\u003e\n\u003cli\u003eVerna VP, Kaur R, Shivay YS, et al. Yield and Quality Parameters of Bt Cotton as Affected by Nitrogen Dose and its Scheduling. International Journal of Current Microbiology and Applied Sciences. 2017; 6(3): 901-6. https:// doi. org/ 10. 20546/ ijcmas. 2017. 603. 106.\u003c/li\u003e\n\u003cli\u003eScarsbrook CE, Bennett OL, Pearson RW. The Interaction of Nitrogen and Moisture on Cotton Yields and Other Characteristics. Agronomy Journal. 1959; 51(12): 718-21. https:// doi. org/ 10. 2134/ agron j1959. 00021 9620051001 20007x.\u003c/li\u003e\n\u003cli\u003eBoman RK, Raun WR, Westerman RL, et al. Long-Term Nitrogen Fertilization in Short-Season Cotton: Interpretation of Agronomic Characteristics Using Stability Analysis. Journal of Production Agriculture. 1997; 10(4): 580-5. https:// doi. org/ 10.2134/ jpa19 97. 0580.\u003c/li\u003e\n\u003cli\u003ePhipps BJ, Stevens WE, Mobley JB, et al. Effect of Nitrogen Level and Mepiquat Chloride (Pix) upon Maturity. Beltwide Cotton Conference; Nashville, TN. 1996. p. 1211-2.\u003c/li\u003e\n\u003cli\u003eRochester IJ, Constable GA. Nitrogen-fertiliser Application Effects on Cotton Lint Percentage, Seed Size, and Seed Oil and Protein Concentrations. Crop \u0026amp; Pasture Science. 2020; 71(9): 831-6. https://doi.org/10.1071/CP20288\u003c/li\u003e\n\u003cli\u003eICAC/ITMF. Guideline for Standardized Instrument Testing of Cotton. Zurich, Switserland. 2018. p. 45.\u003c/li\u003e\n\u003cli\u003eAnon. 2021 Grower Survey 2021. Narrabri, NSW: Intuitive Solutions: p. 57.\u003c/li\u003e\n\u003cli\u003eStiller W. Sicot 746 B3F. Plant Varieties Journal. 2016a; 29(4): 128-32.\u003c/li\u003e\n\u003cli\u003eStiller W. Sicot 714 B3F. Plant Varieties Journal. 2016b; 29(4): 133-7.\u003c/li\u003e\n\u003cli\u003eReid P. Sicala V-2. Plant Varieties Journal. 1995; 8(1): 12-3.\u003c/li\u003e\n\u003cli\u003eASTM. D5867 Standard Test Methods for Measurement of Physical Properties of Raw Cotton by Cotton Classification Instruments. West Conshohocken, PA: ASTM International; 2012a. p. 5.\u003c/li\u003e\n\u003cli\u003eASTM. D1684 Standard Practice for Lighting Cotton Classing Rooms for Color Grading. West Conshohocken, PA: ASTM International; 2012b. p. 4.\u003c/li\u003e\n\u003cli\u003eASTM. D1776 Standard Practice for Conditioning and Textile Testing West Conshohocken, PA: ASTM International; 2015. p. 5.\u003c/li\u003e\n\u003cli\u003eRochester IJ. Growing High-Yielding Nitrogen-Efficient Cotton. 17 th Australian Cotton Conference; Gold Coast, QLD. 2014. p. 68-70.\u003c/li\u003e\n\u003cli\u003eAnon, Potential for Growth in the Australian Cotton Industry. 2014, Eco Logical Australia: Canberra, ACT. p. 47.\u003c/li\u003e\n\u003cli\u003eLuo Q, Bange MP, Johnston D. Enviroment and Cotton Fibre Quality. Climate Change. 2016;138(1): 207-22. https://doi.org/10.1007/s10584-016-1715-0\u003c/li\u003e\n\u003cli\u003eBange MP, Long RL, Caton SJ, et al. Prediction of Upland Cotton Micronaire accounting for the effects of Environment and Crop demand from Fruit Growth. Crop Science. 2022; 62(1): 397-409. https://doi.org/10.1002/csc2.20679\u003c/li\u003e\n\u003cli\u003evan der Sluijs MHJ, Roth GW. Comparing Dryland Cotton Upland Fbre Quality from On-board Spindle and Stripper Harvesting Systems. The Journal of The Textile Institute. 2021; 112(2): 192-9. https://doi.org/10.1080/00405000.2020.1731288\u003c/li\u003e\n\u003cli\u003eBuster S. Cotton Field Preliminary Season Review 2020-2021. Carrathool, NSW: RivCott Ltd.; 2021. p. 22.\u003c/li\u003e\n\u003cli\u003evan der Sluijs MHJ. The Effect of Various Processing Stages During Ginning on Fiber Quality. The Journal of Cotton Science. 2020; 24(1): 44-59.\u003c/li\u003e\n\u003cli\u003eBuster S. Preliminary Season Review 2019-2020. Carrathool, NSW: RivCott Ltd; 2020. p.8.\u003c/li\u003e\n\u003cli\u003eBuster S. Cotton Field Season Review 2017-2018. Carrathool, NSW: RivCott Ltd; 2019a. p.53.\u003c/li\u003e\n\u003cli\u003eBuster S. Cotton Field Multi-Season Review 2017-2019. Carrathool, NSW: RivCott Ltd; 2019b. p. 50.\u003c/li\u003e\n\u003cli\u003eBuster S. Field Trials Report 2018-2019. Carrathool, NSW: RivCott Ltd; 2019c. p. 48.\u003c/li\u003e\n\u003cli\u003eBange MP, Long RL, Caton SJ, et al. Prediction of Upland Cotton Micronaire accounting for the effects of Environment and Crop Demand from Fruit Growth. Crop Science. 2022;62(1):397-409. https://doi.org/ 10.1002/csc2.20679 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eYear, location, planting date, variety, harvest aid dates, harvest date, gin, and gin date\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eField\u003c/p\u003e \u003cp\u003eDesignation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLocation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePlant\u003c/p\u003e \u003cp\u003edate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVarieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1st Harvest\u003c/p\u003e \u003cp\u003eaid date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2nd Harvest aid date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3rd Harvest aid date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHarvest\u003c/p\u003e \u003cp\u003edate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACRI\u003c/p\u003e \u003cp\u003eNarrabri, NSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 October\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSicala V-2\u003c/p\u003e \u003cp\u003eSicot 746 B3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16 April\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27 April\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 May\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e04 June\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eToobeah\u003c/p\u003e \u003cp\u003eQLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 October\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSicot 746 B3F Sicot 714 B3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 March\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 March\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 March\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e11 April\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIREC\u003c/p\u003e \u003cp\u003eGriffith, NSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 October\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSicot 746 B3F Sicot 714 B3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 March\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 April\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e01 May\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e07 May\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACRI\u003c/p\u003e \u003cp\u003eNarrabri, NSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e04 November\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSicala V-2\u003c/p\u003e \u003cp\u003eSicot 746 B3F Sicot 714 B3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e07 April\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20 April\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28 April\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14 June\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCecil Plains\u003c/p\u003e \u003cp\u003eQLD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e07 November\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSicot 746 B3F Sicot 714 B3F\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28 April\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10 May\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29 May\u003c/p\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLocation, N Application rate, product, method, application dates, rainfall, and max and min temperature*\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eField\u003c/p\u003e \u003cp\u003eDesignation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003eKg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApplication\u003c/p\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eApplication\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eApplication\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRainfall\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTemp\u003c/p\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTemp\u003c/p\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDD\u003c/p\u003e \u003cp\u003eBase 12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0, 100, 200, 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 September\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 December\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e248.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0, 200 \u0026amp; 400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 April\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 November\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e227.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136 \u0026amp; 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 November\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 November\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 December\u003c/p\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e220.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0, 100, 200 \u0026amp; 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 September\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 December\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e472.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e29.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 \u0026amp; 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 July\u003c/p\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e327.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e* Information for weather and day degrees were obtained from CSD data.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLint turn out, yield, and average fibre properties as measured by HVI for Field A per N rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003ekg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNUE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLint Turn\u003c/p\u003e \u003cp\u003eOut %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eb.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUHML\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSFI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 746 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.7b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.4a\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.1b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.6b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.2b\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicala V-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e84.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLint turn out, yield, and average fibre properties as measured by HVI and visual assessment for Field B per N rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003ekg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNUE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLint Turn Out %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eb.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUHML\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSFI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eTrash\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eColour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eVisual\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eLeaf\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e% Area\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eCount\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eRd\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+b\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003eCG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003eLG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 746 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.50b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.72a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.2a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.34b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e39b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e81.6b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.50b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.48b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.0b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.6b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.2b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.30a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e36a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e80.1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e6.9a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.40a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.72a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.0a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.29a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e36a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e81.8b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 714 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.21a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e80.8a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.8b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.8a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.33b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e37a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e79.6b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.7b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.97b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.0b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9.7b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.1b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.29a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e38b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e78.1a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.3a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.72b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.5b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.7a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.4a\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.34b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e38b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e79.4b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.9b\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLint turn out and average fibre properties as measured by HVI and visual assessment for Field C per N rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003ekg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNUE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLint Turn\u003c/p\u003e \u003cp\u003eOut %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eb.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUHML\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSFI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eTrash\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eColour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eVisual\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eLeaf\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e% Area\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eCount\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eRd\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+b\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003eCG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003eLG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 746 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e82.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e82.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 714 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e136\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e81.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e33.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e81.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003en.s\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLint turn out, yield, and average fibre properties as measured by HVI for Field D per N rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003ekg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNUE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLint Turn\u003c/p\u003e \u003cp\u003eOut %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eb.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUHML\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSFI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 746 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e32.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 714 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7. 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicala V-2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e82.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003en.s.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLint turn out, yield, and average fibre properties as measured by HVI and visual assessment for Field E per N rate\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eN rate\u003c/p\u003e \u003cp\u003ekg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNUE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLint Turn\u003c/p\u003e \u003cp\u003eOut %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYield\u003c/p\u003e \u003cp\u003eb.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUHML\u003c/p\u003e \u003cp\u003e(mm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSFI\u003c/p\u003e \u003cp\u003e(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSTR\u003c/p\u003e \u003cp\u003e(g.tex\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c12\" namest=\"c10\"\u003e \u003cp\u003eTrash\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c14\" namest=\"c13\"\u003e \u003cp\u003eColour\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c16\" namest=\"c15\"\u003e \u003cp\u003eVisual\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003eLeaf\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e% Area\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003eCount\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cb\u003eRd\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cb\u003e+b\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cb\u003eCG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cb\u003eLG\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"16\" nameend=\"c16\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSicot 746 B3F\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31.01\u003c/p\u003e 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Quality","lastPublishedDoi":"10.21203/rs.3.rs-1927381/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1927381/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eA recent extensive review showed that the effect of nitrogen application rates on fibre quality were varied and inconsistent. As a consequence, trials were conducted in Australia in 2018 and 2019 in four locations using three popular high yielding commercial varieties sown in the Australian cotton industry. Nitrogen was applied in the form of granular urea in three locations, in split applications either before or in-crop with Anhydrous ammonia applied at the fourth location before planting. Application rates ranged from zero (0 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) to high (300 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) and excessive (400 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe application of moderate (100 to 200 kg.ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) rates of nitrogen resulted in the highest yield and nitrogen use efficiency and produced the longest, uniform, and strongest fibre. As the growing conditions for the two seasons were ideal it was shown that nitrogen application rates did not influence micronaire but did negatively affect colour and lint turn out.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNitrogen application rates do impact yield, lint turn out and fibre quality. However excessive application rates above 14 to 15 kg of N per bale had no economic benefit to the grower and could negatively affected yield and fibre quality.\u003c/p\u003e","manuscriptTitle":"Effect of Nitrogen Application Rates on Cotton Yield and Fibre Quality - Results from Recent Trials in Australia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-08-11 17:19:02","doi":"10.21203/rs.3.rs-1927381/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9e2b9d0a-2d31-4a97-8d81-26d60e773d47","owner":[],"postedDate":"August 11th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-09-08T08:52:44+00:00","versionOfRecord":[],"versionCreatedAt":"2022-08-11 17:19:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1927381","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1927381","identity":"rs-1927381","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}