<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">AJPS</journal-id><journal-title-group><journal-title>American Journal of Plant Sciences</journal-title></journal-title-group><issn pub-type="epub">2158-2742</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ajps.2015.67095</article-id><article-id pub-id-type="publisher-id">AJPS-55551</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Biomedical&amp;Life Sciences</subject></subj-group></article-categories><title-group><article-title>
 
 
  Effect of Mineral Fertilization and Irrigation on Sunflower Yields
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>ucia</surname><given-names>Helena Garófalo Chaves</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Danila</surname><given-names>Lima Araujo</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hugo</surname><given-names>Orlando Carvallo Guerra</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Walter</surname><given-names>Esfrain Pereira</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib></contrib-group><aff id="aff2"><addr-line>Federal University of Paraiba, Campus II, Areia, Brazil</addr-line></aff><aff id="aff1"><addr-line>Federal University of Campina Grande, Avenue Aprigio Veloso, Campina Grande, Brazil</addr-line></aff><author-notes><corresp id="cor1">* E-mail:<email>lhgarofalo@hotmail.com(UHGC)</email>;</corresp></author-notes><pub-date pub-type="epub"><day>10</day><month>04</month><year>2015</year></pub-date><volume>06</volume><issue>07</issue><fpage>870</fpage><lpage>879</lpage><history><date date-type="received"><day>24</day>	<month>September</month>	<year>2014</year></date><date date-type="rev-recd"><day>accepted</day>	<month>6</month>	<year>April</year>	</date><date date-type="accepted"><day>13</day>	<month>April</month>	<year>2015</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/</license-p></license></permissions><abstract><p>
 
 
  Among the cultures used for the production of biofuels, the sunflower is one of the most important. Although some information exists, the water and nutritional needs of sunflower in the north east of Brazil are not well known. To fill knowledge gaps, an experiment was carried out to evaluate the effect of nitrogen (N), phosphorus (P), potassium (K) fertilization and available soil water (ASW) on sunflower yields. The sunflower cultivar Embrapa 122-V2000 was subjected to 44 treatments on a completely randomized design generated by the Baconian Matrix with four rates of N (0, 60, 80 and 100 kg
  &amp;middotha
  &lt;sup&gt;-1&lt;/sup&gt;), four rates of P2O5 (0, 80, 100 and 120 kg
  &amp;middotha
  &lt;sup&gt;-1&lt;/sup&gt;), four rates of K2O (0, 80, 100 and 120 kg
  &amp;middotha
  &lt;sup&gt;-1&lt;/sup&gt;), and four available soil water (ASW) levels (55%, 70%, 85% and 100%) replicated three times. Urea was used as a source of N, triple super phosphate as P and potassium chloride as K. In all the experimental units was applied 2 kg
  &amp;middotB
  &amp;middotha
  &lt;sup&gt;-1&lt;/sup&gt; as boric acid. The components of production evaluated were dry matter of the head, total number of achenes, total achenes’ weight and 1000 achenes’ weight. The results of this research showed that nitrogen had a significant effect on the dry matter of the head, total number of achenes and total achenes’ weight. Phosphorus affected all production components and potassium affected the total number and the weight of achenes. With the exception of the 1000 achenes’ weight, all the production components of the sunflower increased with the increased ASW level influenced significantly at 0.01 level of probably the total number of achenes. The highest rates of N, P and K (100, 120 and 120 kg
  &amp;middotha
  &lt;sup&gt;-1&lt;/sup&gt;, respectively) and 100% of available soil water produced the highest production.
 
</p></abstract><kwd-group><kwd>Water</kwd><kwd> Fertilizers</kwd><kwd> Yields</kwd><kwd> Oil Plants</kwd><kwd> Seeds</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Sunflower (Helianthus annuus L.) occupies a prominent place among oilseed crops, as it contributes approximately 12% to global edible oil production. Water and nutrients play an important role in improving seed yield and oil quality of sunflowers [<xref ref-type="bibr" rid="scirp.55551-ref1">1</xref>] . Application of fertilizers substantially increases sunflower growth and yields, however, additions of nitrogen (N), phosphorus (P) and potassium (K) need to be optimized. In sunflowers, nutrient deficiency can result in up to 60% reduction in productivity [<xref ref-type="bibr" rid="scirp.55551-ref2">2</xref>] . The nutritional needs of sunflower are greater than many other crops like wheat, sorghum and corn, requiring higher amounts of N and other macronutrients [<xref ref-type="bibr" rid="scirp.55551-ref3">3</xref>] .</p><p>The number of achenes per head is a reflection of action of N in critical early stages of flowering in sunflower development. The potential number of flowers is determined very early, and subsequently affects the number of achenes and head diameter [<xref ref-type="bibr" rid="scirp.55551-ref4">4</xref>] . Head diameter is one of the morphological characteristics most affected by addition of N, showing increases even with small N doses (25 kg∙N∙ha<sup>−</sup><sup>1</sup>). However, this increase in head diameter does not continue with further increases of N. Sachs et al. [<xref ref-type="bibr" rid="scirp.55551-ref5">5</xref>] observed an increase of achenes productivity with N doses up to 55 kg∙N∙ha<sup>−</sup><sup>1</sup>, 41 kg ha<sup>−</sup><sup>1</sup>of K<sub>2</sub>O and 46 kg∙ha<sup>−1</sup> of P<sub>2</sub>O<sub>5</sub>. The achenes’ oil content increased with the application of K<sub>2</sub>O and P<sub>2</sub>O<sub>5</sub> and the protein content decreased with increasing K<sub>2</sub>O application.</p><p>Shortage of water, which is the most important component of life, limits plant growth and crop productivity, particularly in arid regions. Sunflower is commonly regarded as a plant that is tolerant to drought and it uses water efficiently. Nevertheless, the crop consumes a large amount of total water due to the fact that it produces high yields and a large vegetative bulk. It also has a long growing period coinciding with the warm months of spring and summer. Water stress on sunflower reduces plant height, root length, stomata number and causes early flowering, early maturity and seed yield reduction. Drought adversely influenced leaf area leaf area, days to maturity, leaf diameter, 1000-achene weight and achene yield per plant [<xref ref-type="bibr" rid="scirp.55551-ref6">6</xref>] .</p><p>The present research aimed to investigate the yield of sunflower affected by the interaction between NPK fertilization treatments and irrigation regimes under semiarid Brazilian conditions.</p></sec><sec id="s2"><title>2. Materials and Methods</title><p>The experiment was carried out from March to July 2011 under greenhouse conditions at the Agricultural Engineering Department of the Federal University of Campina Grande, Paraiba State, Brazil.</p><p>The sunflower cultivar used was the Embrapa 122-V2000. A total of 44 treatments on a completely randomized design generated by the Baconian Matrix (<xref ref-type="table" rid="table1">Table 1</xref>) with four doses of N (0, 60, 80 and 100 kg∙ha<sup>−1</sup>), four of P<sub>2</sub>O<sub>5</sub> (0, 80, 100 and 120 kg∙ha<sup>−1</sup>), four of K<sub>2</sub>O (0, 80, 100 and 120 kg∙ha<sup>−1</sup>), four available soil water (ASW) levels (55%, 70%, 85% and 100%) and three replicates resulting in 132 experimental units. Urea was used as a source of N; triple super phosphate as P and potassium chloride as K. In the soil in all the experimental units was applied, as pure solution, 2 kg∙B∙ha<sup>−1</sup> as boric acid.</p><p>Each experimental unit consisted of a plastic pot filled with 32 kg of an Alfisol with the following attributes using the procedures recommended by [<xref ref-type="bibr" rid="scirp.55551-ref7">7</xref>] : sand = 553.40 g∙kg<sup>−1</sup>; silt = 117.30 g∙kg<sup>−1</sup>; clay = 329.30 g∙kg<sup>−1</sup>; pH (H<sub>2</sub>O) = 6.6; Ca<sup>2+</sup> = 1.45 cmol<sub>c</sub>∙kg<sup>−1</sup>; Mg<sup>2+</sup> = 1.65 cmol<sub>c</sub>∙kg<sup>−1</sup>; Na = 0.17 cmol<sub>c</sub>∙kg<sup>−1</sup>; K<sup>+</sup> = 0.21 cmol<sub>c</sub>∙kg<sup>−1</sup>; H<sup>+</sup> + Al<sup>3+</sup> = 0.79 cmol<sub>c</sub>∙kg<sup>−1</sup>; organic matter = 22.2 g∙kg<sup>−1</sup>; Available P (Mehlich) = 8.1 mg∙kg<sup>−1</sup>.</p><p>Soil water content was monitored daily at three depth intervals: 0 - 10, 10 - 20 and 20 - 30 cm, using a Frequency Domain Reflectometry (FDR) segmented probe, inserted into the soil through an access tube installed in the pots. The volume of water required to maintain ASW for each treatment was calculated based the difference between field capacity and the permanent wilting point, and the FDR measurements. Irrigation was performed daily.</p><p>Five sunflower seeds were sown directly in the pots at a 2 cm depth. Twenty days after sowing, seedlings were thinned to one plant per pot.</p><p>When the experiment was finalized, plants were harvested and measured for dry matter (grams) of the head (DMH), total number of achenes (TNA), total weight (grams) achenes (TWA) and 1000 achenes weight (W1000A).</p><p>The results were analyzed statistically through the analyses of variance (ANOVA) described by [<xref ref-type="bibr" rid="scirp.55551-ref8">8</xref>] , using SAEG software [<xref ref-type="bibr" rid="scirp.55551-ref9">9</xref>] .</p><table-wrap id="table1" ><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Nitrogen (N), phosphorus (P<sub>2</sub>O<sub>5</sub>), potassium (K<sub>2</sub>O) and available soil water levels generated by the Baconian matrix</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Treatments.</th><th align="center" valign="middle" >N</th><th align="center" valign="middle" >P<sub>2</sub>O<sub>5</sub></th><th align="center" valign="middle" >K<sub>2</sub>O</th><th align="center" valign="middle" >Water</th><th align="center" valign="middle" >Treatments</th><th align="center" valign="middle" >N</th><th align="center" valign="middle" >P<sub>2</sub>O<sub>5</sub></th><th align="center" valign="middle" >K<sub>2</sub>O</th><th align="center" valign="middle" >Water</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle"  colspan="3"  >------kg∙ha<sup>−1</sup>-----</td><td align="center" valign="middle" >%</td><td align="center" valign="middle" ></td><td align="center" valign="middle"  colspan="3"  >------ kg∙ha<sup>−1</sup>-----</td><td align="center" valign="middle" >%</td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >23</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >25</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >26</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >5</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >6</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >7</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >29</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >8</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >9<sup>*</sup></td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >31<sup>*</sup></td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >10</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >32</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >11</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >55</td><td align="center" valign="middle" >33</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >85</td></tr><tr><td align="center" valign="middle" >12</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >34</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >13</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >14</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >36</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >15</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >37</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >16</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >38</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >17</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >39</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >18</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >40</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >19</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >41</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >20<sup>*</sup></td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >42*</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >21</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >43</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >100</td><td align="center" valign="middle" >100</td></tr><tr><td align="center" valign="middle" >22</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >70</td><td align="center" valign="middle" >44</td><td align="center" valign="middle" >60</td><td align="center" valign="middle" >80</td><td align="center" valign="middle" >120</td><td align="center" valign="middle" >100</td></tr></tbody></table></table-wrap><p><sup>*</sup>Reference level used by the sunflower growers of the region.</p></sec><sec id="s3"><title>3. Results and Discussion</title><p>The ANOVA results are presented in <xref ref-type="table" rid="table2">Table 2</xref>. The results indicate that N, P and ASW had a significant effect on dry matter of the head (DMH) at 1% level of probability (<xref ref-type="table" rid="table2">Table 2</xref>) corroborating [<xref ref-type="bibr" rid="scirp.55551-ref10">10</xref>] .</p><p>For plants treated with N the DMH increased with increasing N rate whose data were fitted to a quadratic regression model (<xref ref-type="fig" rid="fig1">Figure 1</xref>(a)). It is observed that the highest value of this variable (28 g) was registered for the highest dose of N (100 kg∙ha<sup>−1</sup>) 25% higher than the DMH found for the control treatment. The DMH was also influenced significantly by increasing P doses, and these results were fitted to a quadratic regression model (<xref ref-type="fig" rid="fig1">Figure 1</xref>(b)). The highest value of this variable (31 g) was obtained with the highest dose of P (120 kg∙ha<sup>−1</sup>) showing a superiority of 556% when compared with the reference level. The results corroborate [<xref ref-type="bibr" rid="scirp.55551-ref11">11</xref>] and [<xref ref-type="bibr" rid="scirp.55551-ref12">12</xref>] who found an increase of the DMH of sunflower cv. Embrapa 122/V-2000 with increasing N doses and ASW.</p><p>Potassium rates did not affect the DMH values (<xref ref-type="table" rid="table2">Table 2</xref>). These results disagree with those results found by [<xref ref-type="bibr" rid="scirp.55551-ref6">6</xref>] and [<xref ref-type="bibr" rid="scirp.55551-ref12">12</xref>] who found a positive significant effect of K on DMH.</p><p>The DMH increased linearly with increasing ASW from 18 to 24 g, for the lowest (55%) to the greatest ASW doses (100%), respectively (<xref ref-type="fig" rid="fig2">Figure 2</xref>). Guedes Filho et al. [<xref ref-type="bibr" rid="scirp.55551-ref11">11</xref>] observed an increase of 43% in DMH when</p><fig-group id="fig1"><label><xref ref-type="fig" rid="fig1">Figure 1</xref></label><caption><title> Regression curves for the relations N and P versus DMH.</title></caption><fig id ="fig1_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x6.png"/></fig><fig id ="fig1_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x7.png"/></fig></fig-group><fig id="fig2"  position="float"><label><xref ref-type="fig" rid="fig2">Figure 2</xref></label><caption><title> Regression curve for the relation available soil water content &#215; dry matter of the head</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x8.png"/></fig><table-wrap id="table2" ><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Analysis of variance for dry matter of the head (DMH), total achenes’ number (TAN), total achenes’ weight (TWA) and 1000 achenes’ weight (W1000A) for different levels of N, P, K and ASW</title></caption><table><tbody><thead><tr><th align="center" valign="middle" >Source</th><th align="center" valign="middle" >DF</th><th align="center" valign="middle" >Mean square</th><th align="center" valign="middle" >Pr &gt; F</th><th align="center" valign="middle" >Mean square</th><th align="center" valign="middle" >Pr &gt; F</th><th align="center" valign="middle" >Mean square</th><th align="center" valign="middle" >Pr &gt; F</th><th align="center" valign="middle" >Mean square</th><th align="center" valign="middle" >Pr &gt; F</th></tr></thead><tr><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle"  colspan="2"  >DMH</td><td align="center" valign="middle"  colspan="2"  >TAN</td><td align="center" valign="middle"  colspan="2"  >TWA</td><td align="center" valign="middle"  colspan="2"  >W1000A</td></tr><tr><td align="center" valign="middle" >N</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >141.76</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >77234.76</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >51.95</td><td align="center" valign="middle" >0.0013</td><td align="center" valign="middle" >618.67</td><td align="center" valign="middle" >0.0625</td></tr><tr><td align="center" valign="middle" >P</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >1682.16</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >423580.92</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >669.36</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >5869.42</td><td align="center" valign="middle" >&lt;0.0001</td></tr><tr><td align="center" valign="middle" >K</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >5.40</td><td align="center" valign="middle" >0.7513</td><td align="center" valign="middle" >5677.88</td><td align="center" valign="middle" >0.0009</td><td align="center" valign="middle" >27.59</td><td align="center" valign="middle" >0.0338</td><td align="center" valign="middle" >270.98</td><td align="center" valign="middle" >0.3511</td></tr><tr><td align="center" valign="middle" >ASW</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >61.78</td><td align="center" valign="middle" >0.0047</td><td align="center" valign="middle" >50590.70</td><td align="center" valign="middle" >0.0020</td><td align="center" valign="middle" >46.66</td><td align="center" valign="middle" >0.0026</td><td align="center" valign="middle" >54.61</td><td align="center" valign="middle" >0.8804</td></tr><tr><td align="center" valign="middle" >N<sup>*</sup> ASW</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >19.08</td><td align="center" valign="middle" >0.1894</td><td align="center" valign="middle" >32852.11</td><td align="center" valign="middle" >0.0010</td><td align="center" valign="middle" >15.84</td><td align="center" valign="middle" >0.0924</td><td align="center" valign="middle" >249.73</td><td align="center" valign="middle" >0.4311</td></tr><tr><td align="center" valign="middle" >P<sup>*</sup> ASW</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >25.66</td><td align="center" valign="middle" >0.0593</td><td align="center" valign="middle" >14096.31</td><td align="center" valign="middle" >0.1659</td><td align="center" valign="middle" >24.62</td><td align="center" valign="middle" >0.0079</td><td align="center" valign="middle" >252.92</td><td align="center" valign="middle" >0.4211</td></tr><tr><td align="center" valign="middle" >K<sup>*</sup> ASW</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >18.56</td><td align="center" valign="middle" >0.2063</td><td align="center" valign="middle" >7348.53</td><td align="center" valign="middle" >0.6415</td><td align="center" valign="middle" >5.33</td><td align="center" valign="middle" >0.8070</td><td align="center" valign="middle" >250.49</td><td align="center" valign="middle" >0.4287</td></tr><tr><td align="center" valign="middle" >Contrast</td><td align="center" valign="middle" >DF</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >N linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >109.05</td><td align="center" valign="middle" >0.0054</td><td align="center" valign="middle" >207053.43</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >142.18</td><td align="center" valign="middle" >0.0002</td><td align="center" valign="middle" >43.10</td><td align="center" valign="middle" >0.6760</td></tr><tr><td align="center" valign="middle" >N quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >177.65</td><td align="center" valign="middle" >0.0004</td><td align="center" valign="middle" >1227.04</td><td align="center" valign="middle" >0.7202</td><td align="center" valign="middle" >0.75</td><td align="center" valign="middle" >0.7745</td><td align="center" valign="middle" >229.97</td><td align="center" valign="middle" >0.3353</td></tr><tr><td align="center" valign="middle" >P linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >2417.57</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >556461.89</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >1031.08</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >8932.15</td><td align="center" valign="middle" >&lt;0.0001</td></tr><tr><td align="center" valign="middle" >P quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >1139.87</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >318864.65</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >644.27</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >2925.41</td><td align="center" valign="middle" >0.0008</td></tr><tr><td align="center" valign="middle" >K linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >2.22</td><td align="center" valign="middle" >0.6850</td><td align="center" valign="middle" >207053.43</td><td align="center" valign="middle" >&lt;0.0001</td><td align="center" valign="middle" >142.18</td><td align="center" valign="middle" >0.0002</td><td align="center" valign="middle" >43.10</td><td align="center" valign="middle" >0.6760</td></tr><tr><td align="center" valign="middle" >K quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >11.04</td><td align="center" valign="middle" >0.3664</td><td align="center" valign="middle" >1227.04</td><td align="center" valign="middle" >0.7202</td><td align="center" valign="middle" >0.75</td><td align="center" valign="middle" >0.7745</td><td align="center" valign="middle" >229.97</td><td align="center" valign="middle" >0.3353</td></tr><tr><td align="center" valign="middle" >ASW linear</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >124.20</td><td align="center" valign="middle" >0.0030</td><td align="center" valign="middle" >62694.06</td><td align="center" valign="middle" >0.0118</td><td align="center" valign="middle" >101.99</td><td align="center" valign="middle" >0.0012</td><td align="center" valign="middle" >130.48</td><td align="center" valign="middle" >0.4675</td></tr><tr><td align="center" valign="middle" >ASW quadratic</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >5.39</td><td align="center" valign="middle" >0.5275</td><td align="center" valign="middle" >87700.72</td><td align="center" valign="middle" >0.0031</td><td align="center" valign="middle" >17.67</td><td align="center" valign="middle" >0.1677</td><td align="center" valign="middle" >26.92</td><td align="center" valign="middle" >0.7411</td></tr><tr><td align="center" valign="middle" >N &#215; ASW</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >51.84</td><td align="center" valign="middle" >0.0522</td><td align="center" valign="middle" >53772.80</td><td align="center" valign="middle" >0.0195</td><td align="center" valign="middle" >21.65</td><td align="center" valign="middle" >0.1272</td><td align="center" valign="middle" >555.46</td><td align="center" valign="middle" >0.1357</td></tr><tr><td align="center" valign="middle" >P &#215; ASW</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >0.0007</td><td align="center" valign="middle" >0.9941</td><td align="center" valign="middle" >6512.35</td><td align="center" valign="middle" >0.4100</td><td align="center" valign="middle" >9.58</td><td align="center" valign="middle" >0.3085</td><td align="center" valign="middle" >359.46</td><td align="center" valign="middle" >0.2290</td></tr><tr><td align="center" valign="middle" >K &#215; ASW</td><td align="center" valign="middle" >1</td><td align="center" valign="middle" >19.93</td><td align="center" valign="middle" >0.2258</td><td align="center" valign="middle" >3238.75</td><td align="center" valign="middle" >0.5608</td><td align="center" valign="middle" >6.20</td><td align="center" valign="middle" >0.4122</td><td align="center" valign="middle" >591.56</td><td align="center" valign="middle" >0.1238</td></tr></tbody></table></table-wrap><p>ASW was increased from 55% to 100%. Similarly [<xref ref-type="bibr" rid="scirp.55551-ref13">13</xref>] observed that the level of ASW influenced the DMH linearly at 1% probability. The higher dry matter accumulation may be a reflection of a greater ion absorption in soil, since the increase in soil moisture on the development of sunflower crop can be significant in nutrient uptake by plants.</p><p>The total number of achenes (TAN) was significantly affected, at 1% level of probability, by the increase of N, P and K doses and available soil water. The interaction among N and ASW at 1% level of probability was also significant (<xref ref-type="table" rid="table2">Table 2</xref>) corroborating [<xref ref-type="bibr" rid="scirp.55551-ref12">12</xref>] .</p><p>The increase of the number of achenes with the N doses was fitted to a linear model as observed in <xref ref-type="fig" rid="fig3">Figure 3</xref>(a). The greatest TAN was obtained, thus, with the highest N doses.</p><p>The effect of P on the TAN was fitted to a quadratic model (<xref ref-type="fig" rid="fig3">Figure 3</xref>(b)) verifying the greatest achene number (416) at 80 kg∙P∙ha<sup>−</sup><sup>1</sup>. This kind of adjustment was also reported by [<xref ref-type="bibr" rid="scirp.55551-ref14">14</xref>] and [<xref ref-type="bibr" rid="scirp.55551-ref15">15</xref>] . The response of achene number to the K was also fitted to a quadratic model (<xref ref-type="fig" rid="fig4">Figure 4</xref>(a)) verifying the greatest achene number (506) for the 120 kg∙K∙ha<sup>−</sup><sup>1</sup>.</p><p>The increase in available soil water content increased, in a quadratic manner, the achene number from 301 to 448 when water increased from 55% to 100% ASW, an increase of 52.30% (<xref ref-type="table" rid="table2">Table 2</xref>). Otherwise, [<xref ref-type="bibr" rid="scirp.55551-ref11">11</xref>] found a quadratic effect producing above 600 achenes with 100% level available soil water.</p><p>The effect of ASW on the sunflower is similar to other studies [<xref ref-type="bibr" rid="scirp.55551-ref12">12</xref>] [<xref ref-type="bibr" rid="scirp.55551-ref16">16</xref>] - [<xref ref-type="bibr" rid="scirp.55551-ref18">18</xref>] . <xref ref-type="fig" rid="fig4">Figure 4</xref>(b) shows an increase of the TAN with the ASW in a quadratic model, obtaining the highest number of achenes for the highest level of water.</p><p>The interaction among N and the available soil water content on TAN was significant to the 1% level of probability (<xref ref-type="table" rid="table2">Table 2</xref>). <xref ref-type="fig" rid="fig5">Figure 5</xref> presents the cited interaction. It is observed that in general, the TAN increased</p><fig-group id="fig3"><label><xref ref-type="fig" rid="fig3">Figure 3</xref></label><caption><title> Regression curves for the relations N &#215; total achenes’ number and P &#215; total achenes’ number.</title></caption><fig id ="fig3_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x9.png"/></fig><fig id ="fig3_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x10.png"/></fig></fig-group><fig-group id="fig4"><label><xref ref-type="fig" rid="fig4">Figure 4</xref></label><caption><title> Regression curves for the relations K &#215; TAN and ASW &#215; TAN.</title></caption><fig id ="fig4_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x11.png"/></fig><fig id ="fig4_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x12.png"/></fig></fig-group><fig id="fig5"  position="float"><label><xref ref-type="fig" rid="fig5">Figure 5</xref></label><caption><title> Interaction among N and the ASW on TAN</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x13.png"/></fig><p>with the N application and with the ASW. Thus the highest total number of achenes (844) was obtained with the highest N application (100 kg∙ha<sup>−1</sup>) and the highest ASW (100%).</p><p>The total achenes’ weight was significantly influenced by increasing N, P, K rates and the ASW (<xref ref-type="table" rid="table2">Table 2</xref>). Total achenes’ weight increased with N and P treatments, the data was adjusted to a linear and quadratic regression model, respectively (<xref ref-type="fig" rid="fig6">Figure 6</xref>(a) and <xref ref-type="fig" rid="fig6">Figure 6</xref>(b), respectively). Analyzing <xref ref-type="fig" rid="fig6">Figure 6</xref>(a), it is observed that the highest total achene’ weight (16 g) was obtained with the highest N dose (100 kg∙ha<sup>−1</sup>). <xref ref-type="fig" rid="fig6">Figure 6</xref>(b) shows that the highest total achene’ weight (16 g) was obtained with the highest P doses (96 kg∙ha<sup>−1</sup>). These highest weights were 136% and 728% superior to the control treatment, respectively.</p><p>The TWA increased linearly with increasing K (<xref ref-type="fig" rid="fig7">Figure 7</xref>(a)) verifying the greatest achene weight (15.67 g) for the 120 kg∙P∙ha<sup>−</sup><sup>1</sup>. The ASW treatments increased the total achenes weight linearly obtaining 8.94 and 15.22 g for the lowest and highest treatment, respectively. There was an increase of 70.25% between the lowest and highest water treatments.</p><p>The 1000 achenes’ weight of sunflower was only affected by the P application, at the 1% level of probability. The regression was adjusted to a quadratic model (<xref ref-type="fig" rid="fig8">Figure 8</xref>), verifying an increase of the 1000 achenes’ weight with P application and therefore, the greatest value for the treatment of 120 kg∙P∙ha<sup>−</sup><sup>1</sup> (60 g).</p><fig-group id="fig6"><label><xref ref-type="fig" rid="fig6">Figure 6</xref></label><caption><title> Regression curves for the relations Nx TWA and P &#215; TWA.</title></caption><fig id ="fig6_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x14.png"/></fig><fig id ="fig6_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x15.png"/></fig></fig-group><fig-group id="fig7"><label><xref ref-type="fig" rid="fig7">Figure 7</xref></label><caption><title> Regression curves for the relation K &#215; total achenes’ weight (a) and ASW &#215; total achenes’ weight (b).</title></caption><fig id ="fig7_1"><label>(b)</label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x16.png"/></fig><fig id ="fig7_2"><label></label><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x17.png"/></fig></fig-group><fig id="fig8"  position="float"><label><xref ref-type="fig" rid="fig8">Figure 8</xref></label><caption><title> Regression curve for the relation P &#215; 1000 achenes’ weight</title></caption><graphic mimetype="image"   position="float"  xlink:type="simple"  xlink:href="http://html.scirp.org/file/6-2601759x18.png"/></fig></sec><sec id="s4"><title>4. Conclusions</title><p>The dry matter of the head, the total achenes’ number and the total achenes’ weight increased significantly with the nitrogen doses applied.</p><p>All the sunflower variables studied increased significantly with the phosphorus doses applied.</p><p>The total achenes’ number and the total achenes’ weight increased significantly with the potassium doses applied.</p><p>With the exception of the 1000 achenes’ weight, whose effect was not significant, all the production components of the sunflower increased with the available water in the soil.</p><p>The interaction between N and the available soil water content was significant only for the TAN. It increased with the N application and with ASW.</p><p>The highest rates of N, P, and K (100, 120 and 120 kg∙ha<sup>−1</sup>, respectively) and the 100% available soil water produced the highest production.</p></sec><sec id="s5"><title>Acknowledgements</title><p>Thanks to the Coordination of Improvement of Higher Education (CAPES) for the scholarship award to the second author at the Graduate School.</p></sec><sec id="s6"><title>NOTES</title></sec></body><back><ref-list><title>References</title><ref id="scirp.55551-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">Hussain, M.K., Rasul, E. and Ali, S.K. (2000) Growth Analysis of Sunflower (Helianthus annuus L.) under Drought Conditions. International Journal of Agriculture and Biology, 2, 136-140.</mixed-citation></ref><ref id="scirp.55551-ref2"><label>2</label><mixed-citation publication-type="other" xlink:type="simple">Biscaro, G.A., Machado, J.R., Tosta, M.S., Mendon&amp;ccedila, V., Soratto, R.P. and Carvalho, L.A. (2008) Nitrogen Side Dressing Fertilization in Irrigated Sunflower under Conditions of Cassilandia-MS. Ciência e Agrotecnologia, 32, 1366-1373. http://dx.doi.org/10.1590/S1413-70542008000500002</mixed-citation></ref><ref id="scirp.55551-ref3"><label>3</label><mixed-citation publication-type="other" xlink:type="simple">Vigil, M.F. (2000) Fertilization in Dryland Cropping Systems: A Brief Overview Central Great Plains. Research Station-USDA-ARS.</mixed-citation></ref><ref id="scirp.55551-ref4"><label>4</label><mixed-citation publication-type="other" xlink:type="simple">Zagonel, J. and Mundstock, C.M. (1991) Nitrogen Rates and Side-Dress Timing on Two Sunflower Cultivars. Pesquisa Agropecuária Brasileira, 26, 1487-1492.</mixed-citation></ref><ref id="scirp.55551-ref5"><label>5</label><mixed-citation publication-type="other" xlink:type="simple">Sachs, L.G., Portugal, A.P., Prudencio-Ferrreira, S.H., Ida, E.I. and Sachs, P.J. (2006) Efeito de NPK na produtividade e componentes químicos do girassol. Semina: Ciências Agrárias, 27, 533-546. 
http://dx.doi.org/10.5433/1679-0359.2006v27n4p533</mixed-citation></ref><ref id="scirp.55551-ref6"><label>6</label><mixed-citation publication-type="journal" xlink:type="simple"><name name-style="western"><surname>Bakht</surname><given-names> J.</given-names></name>,<name name-style="western"><surname> Shafi</surname><given-names> M.</given-names></name>,<name name-style="western"><surname> Yousaf</surname><given-names> M.</given-names></name>,<name name-style="western"><surname> Raziuddin R. and Khan</surname><given-names> M.A. </given-names></name>,<etal>et al</etal>. (<year>2010</year>)<article-title>Effect of Irrigation on Physiology and Yield of Sunflower Hybrids</article-title><source> Pakistan Journal of Botany</source><volume> 42</volume>,<fpage> 1317</fpage>-<lpage>1326</lpage>.<pub-id pub-id-type="doi"></pub-id></mixed-citation></ref><ref id="scirp.55551-ref7"><label>7</label><mixed-citation publication-type="other" xlink:type="simple">EMBRAPA, Centro Nacional de Pesquisa de Solos (1997) Manual de métodos de analise de solo. 2nd Edition, rev. atual, Embrapa, Rio de Janeiro. ISBN-85-85864-03-6.</mixed-citation></ref><ref id="scirp.55551-ref8"><label>8</label><mixed-citation publication-type="other" xlink:type="simple">Ferreira, D.F. (2000) Sistema de análises de variancia para dados balanceados. UFLA, Lavras (SISVAR 4. 1. Pacote computacional). http://www.scielo.br/scielo.php?script=sci_nlinks&amp;ref=000117&amp;pid=S0100-2945200900030002000012&amp;lng=en</mixed-citation></ref><ref id="scirp.55551-ref9"><label>9</label><mixed-citation publication-type="other" xlink:type="simple">Euclides, R.F. (1997) Manual de utiliza&amp;ccedil&amp;atildeo do programa SAEG: sistema para análises estatísticas e genéticas. 2nd Edition, UFV, Vi&amp;ccedilosa. 
http://www.scielo.br/scielo.php?script=sci_nlinks&amp;ref=000084&amp;pid=S0100-204X200100020001800012&amp;lng=en</mixed-citation></ref><ref id="scirp.55551-ref10"><label>10</label><mixed-citation publication-type="other" xlink:type="simple">Silva, P.C.C., Couto, J.L. and Santos, A.F. (2010) Absor 
&amp;ccedil&amp;atildeo dos íons am&amp;ocircnio e nitrato e seus efeitos no desenvolvimento do girassol em solu 
&amp;ccedil&amp;atildeo nutritiva. Revista de Biologia e Ciência da Terra, 10, 97-104.</mixed-citation></ref><ref id="scirp.55551-ref11"><label>11</label><mixed-citation publication-type="other" xlink:type="simple">Guedes Filho, D.H., Chaves, L.H.G., Campos, V.B., Santos Júnior, A. and Oliveira, J.T.L. (2011) Production of Sunflower and Biomass Depending on Availables Oil Water and Nitrogen Levels. Iranica Journal of Energy and Environment, 2, 313-319.</mixed-citation></ref><ref id="scirp.55551-ref12"><label>12</label><mixed-citation publication-type="other" xlink:type="simple">Chaves, L.H.G., Guerra, H.O.C., Campos, V.B., Pereira, W.E. and Ribeiro, P.H.P. (2014) Biometry and Water Consumption of Sunflower as Affected by NPK Fertilizer and Available Soil Water Content under Semiarid Brazilian Conditions. Agricultural Sciences, 5, 668-676.</mixed-citation></ref><ref id="scirp.55551-ref13"><label>13</label><mixed-citation publication-type="other" xlink:type="simple">Oliveira, J.T.L., Chaves, L.H.G., Campos, V.B.J., Santos Júnior, A. and Guedes Filho, D.H. (2012) Fitomassa de girassol cultivado sob aduba 
&amp;ccedil&amp;atildeo nitrogenada e níveis de água disponível no solo. Revista Brasileira de Agricultura Irrigada, 6, 23-32. http://dx.doi.org/10.7127/rbai.v6n100077</mixed-citation></ref><ref id="scirp.55551-ref14"><label>14</label><mixed-citation publication-type="other" xlink:type="simple">Sadiq, S.A., Shahid, M., Jan, A. and Noor-Ud-Din, S. (2000) Effect of Various Levels of Nitrogen, Phosphorus, Potassium (NPK) on Growth, Yield, Yield Components of Sunflower. Pakistan Journal of Biological Sciences, 3, 338-339.  
http://dx.doi.org/10.3923/pjbs.2000.338.339</mixed-citation></ref><ref id="scirp.55551-ref15"><label>15</label><mixed-citation publication-type="other" xlink:type="simple">Gerendás, J., Abbadi, J. and Sattelmacher, B. (2008) Potassium Efficiency of Safflower (Carthamus tinctoriusL.) and Sunflower (Helianthus annuus L.). Journal of Plant Nutrition and Soil Science, 171, 431-439.  
http://dx.doi.org/10.1002/jpln.200720218</mixed-citation></ref><ref id="scirp.55551-ref16"><label>16</label><mixed-citation publication-type="other" xlink:type="simple">Kakar, A.A. and Soomro, A.G. (2001) Effect of Water Stress on the Growth, Yield and Oil Content of Sunflower. Pakistan Journal of Agricultural Science, 38, 73-74.</mixed-citation></ref><ref id="scirp.55551-ref17"><label>17</label><mixed-citation publication-type="other" xlink:type="simple">Bajehbaj, A.A. (2010) Effects of Water Limitation on Grain and Oil Yields of Sunflower Cultivars. Journal of Food, Agriculture and Environment, 8, 98-101.</mixed-citation></ref><ref id="scirp.55551-ref18"><label>18</label><mixed-citation publication-type="other" xlink:type="simple">El Naim, A.M. and Ahmed, M.F. (2010) Effect of Irrigation Intervals and Inter-Row Spacing on Yield, Yields Components and Water Use Efficiency of Sunflower (Helianthus annuus L). Journal of Applied Sciences Research, 6, 1446-1451.</mixed-citation></ref></ref-list></back></article>