Crop Sensor-Based In-Season Nitrogen Management of Wheat with Manure Application

It is difficult to predict the crop-available nitrogen (N) from farmyard manures applied to soil. The aim of this study was to assess the usefulness of the proximal sensors, Yara N-TesterTM and RapidScan CS-45, for diagnosing the N nutritional status of wheat after the application of manures at sowing. Three annual field trials were established (2014–2015, 2015–2016 and 2016–2017) with three types of fertilizer treatments: dairy slurry (40 t ha−1 before sowing), sheep manure (40 t ha−1 before sowing) and conventional treatment (40 kg N ha−1 at tillering). For each treatment, five different mineral N fertilization doses were applied at stem elongation: 0, 40, 80, 120, and 160 kg N ha−1. The proximal sensing tools were used at stem elongation before the application of mineral N. Normalized values of the proximal sensing look promising for adjusting mineral N application rates at stem elongation. For dairy slurry, when either proximal sensor readings were 60–65% of the reference plants with non-limiting N, the optimum N rate for maximizing yield was 118–128 kg N ha−1. When the readings were 85–90%, the optimum N rate dropped to 100–110 kg N ha−1 for both dairy slurry and conventional treatments. It was difficult to find a clear relationship between sensor readings and yield for sheep manure treatments. Measurements taken with RapidScan C-45 were less time consuming and better represent the spatial variation, as they are taken on the plant canopy. Routine measurements throughout the growing season are particularly needed in climates with variable rainfall. The application of 40 kg N ha−1 at the end of winter is necessary to ensure an optimal N status from the beginning of wheat crop development. These research findings could be used in applicator-mounted sensors to make variable-rate N applications.

Response of sunflowers (Helianthus annuus L.) to varying seeding rates and nitrogen fertilizer rates in a no-till cropping system in Saskatchewan

In the past, most sunflower research was conducted in tilled cropping systems and was based on wide row configurations established using precision planters. Little agronomic information is available for the no-till systems predominant in Saskatchewan, where crops are typically seeded in narrow rows using an air drill. Two studies were conducted in Saskatchewan to determine the optimum seeding and nitrogen (N) rates for short-season sunflowers in a no-till cropping system. The N rate study used 5 N rates (10, 30, 50, 70, and 90 kg N ha−1) with the hybrid 63A21. The seeding rate study used 7 seeding rates (37 000, 49 000, 61 000, 74 000, 86 000, 98 000, and 111 000 seeds ha−1) with two cultivars, AC Sierra (open pollinated) and 63A21 (hybrid). There was a linear yield increase as the N rate increased from 10 to 90 kg N ha−1. Based on the N rates tested in this study and current N fertilizer costs below $1 kg−1, sunflower yields and gross returns were most favorable at 90 kg N ha−1. Future N response research with a wider range of N rates is warranted to best determine the optimum N rate. The optimum seeding rate was between 98 000 and 111 000 seeds ha−1 for AC Sierra and between 74 000 and 86 000 seeds ha−1 for 63A21. The optimum plant density, approximately 70 000 to 75 000 plants ha−1, was similar for both cultivars. These results are higher than the current recommended seeding rates for wide-row precision planting systems in areas with a longer growing season.

Evaluation of the CERES-Rice Model for Precision Nitrogen Management for Rice in Northeast China

Over-application of nitrogen (N) in rice (Oryza sativaL.) production in China is common, leading to low N use efficiency (NUE) and high environmental risks. The objective of this work was to evaluate the ability of the CERES-Rice crop growth model to simulate N response in the cool climate of Northeast China, with the long term goal of using the model to develop optimum N management recommendations. Nitrogen experiments were conducted from 2011–2015 in Jiansanjiang, Heilongjiang Province in Northeast China. The CERES-Rice model was calibrated for 2014 and 2015 and evaluated for 2011 and 2013 experiments. Overall, the model gave good estimations of yield across N rates for the calibration years (R2=0.89) and evaluation years (R2=0.73). The calibrated model was then run using weather data from 2001–2015 for 20 different N rates to determine the N rate that maximized the long term marginal net return (MNR) for different N prices. The model results indicated that the optimum mean N rate was 120–130 kg N ha–1, but that the simulated optimum N rate varied each year, ranging from 100 to 200 kg N ha–1. Results of this study indicated that the CERES-Rice model was able to simulate cool season rice growth and provide estimates of optimum regional N rates that were consistent with field observations for the area.

Development of methods for remotely sensing grass growth to enable precision application of nitrogen fertilizer

A ‘chessboard’ field experiment set up to investigate how the yield response to nitrogen (N) fertiliser varied spatially within a field in the UK indicated that the optimum N rate varied substantially by up to 100 kg N/ha within the three hectare experimental area. Variation in N optima was negatively related to the soil N supply. However, soil N supply, yield potential and apparent fertiliser recovery rate were inter-related which meant that the influence of each element on N optima was complex. Spectral reflectance indices related well to crop N uptake and could be used to help estimate soil N supply.

PENENTUAN KEBUTUHAN NITROGEN TANAMAN JAGUNG (Zea mays L.) PADA BERBAGAI JARAK TANAM DALAM TUMPANGSARI DENGAN KACANG TANAH (Arachis hypogeae L.) DI LAHAN KERING MALUKU TENGAH

Most people in Maluku Islands have long used non-rice food consumption, especially tuber crops and maize. The development of diversification of non-rice food consumption certainly needs to be supported by the availability of adaptive crop cultivation technology to climate change. Cropping pattern is one of the appropriate steps for smallholder farmer to increase land productivity. An experiment of maize/peanut intercropping pattern had been conducted to determine optimum Nitrogen (N) rate for maize at different planting spacings in intercropping pattern with peanut in dryland of Makariki Village, Central Maluku. The experiments were arranged in a Split Plot Design with 3 (three) replicates. The main plot was maize spacing, namely: (i) J1 = 80 x 25 cm, 6 rows of maize, 2 rows of peanut, (ii) J2 = 160 x 25 cm, 3 rows of maize, 4 rows of peanut, and (iii) J3 = 240 x 25 cm, 2 rows of maize, 6 rows of peanut. The sub-plot was N rate (kg/ha), namely: (i) N0 = 0-0-0, (ii) N1 = 45-50-60, (iii) N2 = 90-50-60, (iv) N3 = 135-50-60, and (v) N4 = 180-50-60. The results showed that plant height, cob circle and yield of maize grown at different planting spacings in intercropping patterns in Makariki, Central Maluku affected by N fertilizer application. The application of N fertilizer increased growth and yield of maize by following a quadratic pattern. The use of maize spacing of J1 (80 x 25 cm) in intercropping with peanut requires the addition of the optimum N rate of 302 kg urea/ha, which gave the highest maize yield (t/ha) compared with other planting spacings.

PENENTUAN KEBUTUHAN NITROGEN TANAMAN JAGUNG (Zea mays L.) PADA BERBAGAI JARAK TANAM DALAM TUMPANGSARI DENGAN KACANG TANAH (Arachis hypogeae L.) DI LAHAN KERING MALUKU TENGAH

Most people in Maluku Islands have long used non-rice food consumption, especially tuber crops and maize. The development of diversification of non-rice food consumption certainly needs to be supported by the availability of adaptive crop cultivation technology to climate change. Cropping pattern is one of the appropriate steps for smallholder farmer to increase land productivity. An experiment of maize/peanut intercropping pattern had been conducted to determine optimum Nitrogen (N) rate for maize at different planting spacings in intercropping pattern with peanut in dryland of Makariki Village, Central Maluku. The experiments were arranged in a Split Plot Design with 3 (three) replicates. The main plot was maize spacing, namely: (i) J1 = 80 x 25 cm, 6 rows of maize, 2 rows of peanut, (ii) J2 = 160 x 25 cm, 3 rows of maize, 4 rows of peanut, and (iii) J3 = 240 x 25 cm, 2 rows of maize, 6 rows of peanut. The sub-plot was N rate (kg/ha), namely: (i) N0 = 0-0-0, (ii) N1 = 45-50-60, (iii) N2 = 90-50-60, (iv) N3 = 135-50-60, and (v) N4 = 180-50-60. The results showed that plant height, cob circle and yield of maize grown at different planting spacings in intercropping patterns in Makariki, Central Maluku affected by N fertilizer application. The application of N fertilizer increased growth and yield of maize by following a quadratic pattern. The use of maize spacing of J1 (80 x 25 cm) in intercropping with peanut requires the addition of the optimum N rate of 302 kg urea/ha, which gave the highest maize yield (t/ha) compared with other planting spacings.

Yield and fertilizer N recommendations in winter wheat – an alternative approach in high rainfall areas of the UK

SUMMARYThe requirement for inorganic fertilizer nitrogen (N) by winter wheat crops in the United Kingdom is derived using the Department for Environment, Food and Rural Affairs (Defra) Fertilizer Manual. In the experimental programme described and discussed in the present paper, the appropriateness of these recommendations for winter wheat grown in Northern Ireland is examined.Yield response to N varied in experiments conducted on two winter wheat cultivars (cvars) in Northern Ireland from 2007 to 2009. Consequently the optimum N rate (Nopt, defined as the rate of applied N where the value of the increase in yield equals the cost of the increment in fertilizer applied and beyond which additional N would not repay its cost) also varied from year to year. The band of fertilizer N rates over which margins were reduced by £20 (GBP) and £50 also varied from year to year. Changes in the N:grain price ratio affected Nopt to differing extents in the three experiments depending on the shape of the yield v. N response.Nopt should therefore be considered as a range of N rates because (1) it varies from year to year and probably also field to field and (2) the margin of income from grain over cost of fertilizer varies little over a range of N rates because of the shape of the asymptotic response of yield to N. Alternatively, in high rainfall areas (annual rainfall >700 mm) of England, Wales and Northern Ireland, where Table C of the Fertilizer Manual (formerly RB 209) is used to determine soil nitrogen supply (SNS) index, a single N rate could be adopted at SNS indices of 2 or less (equating to soil N supplies of 100 kg/ha or less). A rate of 240 kg N/ha could be adopted based on the over-years function fitted to all results in the three experiments reported in the present paper and including treatments that vary in the splitting of N applied between the two applications and in their timing.Grain N concentration rarely exceeded the guideline 19 mg/g for feed wheat crops identified in the Fertilizer Manual (Anon. 2010). Overall, N taken up by the crops was used efficiently, and particularly so at lower N rates. However, at low fertilizer N rates the contribution from ‘free’ soil N inflates the ‘apparent’ value of grain yield produced. The responses of yield and grain N concentration to N show that crop processes work to maximize yield at the expense of N concentration in the grain. Therefore there is less need to be concerned about identifying the optimum N rate and predicting fertilizer N requirement with a high degree of precision. Instead growers could assess and adjust the efficiency of their N use based on grain N concentration generally, rather than specifically assess whether their fertilizer N applications were close to Nopt. Essentially as grain N concentration increases, yield/kg of applied fertilizer N decreases. Thus at low grain N concentrations, yield could be increased by increasing N applications and at high grain N concentrations yield could be maintained and profitability increased by reducing N applications.

Long-term effect of crop production factors on the yield and yield stability of maize (zea mays L.) in different years

The effects of five crop production factors (tillage, fertilisation, plant density, variety, weed control) on the yield and yield stability of maize were examined in Martonvásár (HU) in a polyfactorial experiment and in separate long-term experiments on the effects of Nfertilisation, sowing date and plant density. In the polyfactorial experiment the five crop production factors contributed to the increase in maize yield in the following ratios (%): fertilisation 30.6, variety 32.6, plant density 20.2, weed control 14.2, soil cultivation 2.4. In the N fertilisation, sowing date and plant density experiments the effects of the treatments on the maize yield were examined separately for dry and wet years.Averaged over 40 years, the yields in the long-term N fertilisation experiment were 2.422 t ha−1 lower in the dry years than in the wet years (5.170 vs. 7.592 t ha−1). The optimum N rate was 160 kg ha−1. In the sowing date experiment the yield was 2.533 t ha−1 lower in the dry years than in the wet years (6.54 vs. 9.093 t ha−1), averaged over 19 years. In dry years the yield was highest for the early and optimum sowing dates, and in wet years for the optimum sowing date. Sowing at dates other than the optimum caused reductions in N fertiliser efficiency. Averaged over 22 years, the optimum plant density was 80,000 plants ha−1 in wet years and 50,000 plants ha−1 in dry years. The yield was most stable at a plant density of 60,000 plants ha−1. The clarification of year effects is particularly important in relation to the possible effects of climate change.