Modelling Sunflower Yield Prediction at Field Scale

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of the plant and correlate it to crop yield. This strategy is totally under farmers control, therefore is the only that can be used by the farmers to take decisions about their agricultural processes. This approach is the less expensive and the most accurate, because is based on the simplest relationship: development of one organ of the plant related to biomass of the commercial organ. In order this strategy can be practically useful for predicting yield, it has to evaluate vegetative organs, preferably since before capitulum appears on the plant. In this way it is possible to construct a curve since the first sampling few days after planting and predict the final result of the harvest.
There are several studies of correlation between morphological traits and yield in several crops such as maize [9,10], wheat [11], rice [12], soybean [13], and sunflower [14,15] but they are used as information for selection programs, not for predicting the quantity to harvest of the commercial organ based on some parameter of vegetative organs. Sunflower (Helianthus annuus L.) is an important crop because a healthy and edible oil is extracted from its seeds, and this oil is highly consumed worldwide. Achene yield in sunflower is considered a trait highly variable because of the environment conditions [14]. There are two types of environment conditions, those predictable such as soil traits, and those unpredictable such as weather. Farmers may plan how to manage the soil to get good sunflower harvest, but they cannot manage the climate, therefore farmers decisions during the agricultural process related to necessary changes in the crop management as consequence of changes in environment, are immediate; if farmers do not have accurate predictions of yield, it is not possible to manage the crop in other more efficient way. The aim of the present study was to stablish the basis for getting a sunflower yield prediction model, for that, this study investigated the partition of dry matter in sunflower plants, and also investigated if the dry mass of the second pair of leaves is a good predictor of the dry mass of the whole plant.

Field Assay
At fields of Experimental Station Miguel Luna Lugo, in Universidad Centroccidental Lisandro Alvarado, Cabudare, Lara state, Venezuela, forty rows of 12.5 m length, separated by 1.2 m, were prepared. Twenty rows were placed on a sandy clay loam soil, and the other 20 rows were placed on a sandy loam soil. Ten rows of each soil type were sown with seeds of a commercial hybrids, and the other 20 rows were sown with seeds of other commercial hybrid. Seeds were separated by 0.50 m, to have an approximate availability of 500 plants of each hybrid in each soil type. This experiment was repeated twice, in two years.

Sampling
Sampling was carried out randomly. Rows within hybrids and soil type were ordered randomly, and nine sampling points (plants) were chosen randomly on each row. Sampling was carried out each 11 days for 103 days, starting 26 days after planting. Each sampling date consisted in taking plants of the 9 sampling points within the row for only one row, for each hybrid in each soil type. Sampling planting; in all these cases dry mass resulted higher in sandy loam soil than in sandy clay loam soil. Due to absence of interaction, but significant effect for Soil Type, means for each hybrid in two years were averaged within soil type and sampling date. Table 1

Discussion
Partition of dry matter of the above ground biomass of the sunflower plants resulted between 27.28 and 33.82% for capitulum at the day 103 after planting. Harvest index is defined as the ratio of seed yield to the total biomass in the plant [16], and ratio between seed mass and capitulum mass is about 60% [17], it means that harvest index for present study was around 18%. Magnitude of harvest index must be considered low when it is compared to recent reports with values between 27 and 31% [17], 34 and 44 % [18], however, sunflower phonotypic variability is also expressed for harvest index because some studies have reported values so low such as 3, 4, and 9% [19]. One of the objectives of sunflower breeding is to increase harvest index, however it is a trait highly influenced by environment, and it can explain the broad range for the magnitude of this trait.
The close relationship between dry mass of the second pair of leaves and dry mass of the above ground plant biomass opens opportunities for sunflower yield prediction based on direct observations of the agricultural process, and also simple nutritional diagnosis of the plant [20]. Yield prediction based on leaves sampling is very accurate, it is associated to photosynthetic capacity [21], and it is evaluating a direct measure of the plant biomass growth, in the same units of the commercial production (mass of seeds). Several traits have been reported as associated to sunflower yield, such as days to 50% of plant to maturity, plant height, and number of leaves per plant [22], but they have not been used as yield predictors, and 2) Prediction must be on the expected result at the harvest according to dry mass of the second pair of leaves determined in any day of the cycle, therefore, it must be fixed a specific day for harvesting.
3) When a sample of the second pair of leaves is taken, term X of the equation 2 must be found out (which will be called X1).
This X1 must be compared to the actual day of the sampling, if they are the same, the prediction of production will be which is indicated for the equation 1 for the harvest day when X1 is placed. If they are different, it must be calculated how many  2) Dry mass of second pair of leaves from the top to down is an accurate predictor of above ground plant biomass.
3) A simple model of sunflower yield prediction at field scale is proposed and consists in obtaining regression equation of dry mass of second pair of leaves on sunflower cycle days, and also equation of dry mass of above ground plant biomass on sunflower cycle days. With both equations, yield prediction can be performed from a simple datum of second pair of leaves dry mass, since first days after planting.