Artificial neural network potential in yield prediction of lentil (Lens culinaris L.) influenced by weed interference

This study was conducted to predict the yield and biomass of lentil (Lens culinaris L.) af- fected by weeds using artificial neural network and multiple regression models. Systematic sampling was done at 184 sampling points at the 8-leaf to early-flowering and at lentil maturity. The weed density and height as well as canopy cover of the weeds and lentil were measured in the first sampling stage. In addition, weed species richness, diversity and even- ness were calculated. The measured variables in the first sampling stage were considered as predictive variables. In the second sampling stage, lentil yield and biomass dry weight were recorded at the same sampling points as the first sampling stage. The lentil yield and biomass were considered as dependent variables. The model input data included the total raw and standardized variables of the first sampling stage, as well as the raw and stan- dardized variables with a significant relationship to the lentil yield and biomass extracted from stepwise regression and correlation methods. The results showed that neural network prediction accuracy was significantly more than multiple regression. The best network in predicting yield of lentil was the principal component analysis network (PCA), made from total standardized data, with a correlation coefficient of 80% and normalized root mean square error of 5.85%. These values in the best network (a PCA neural network made from standardized data with significant relationship to lentil biomass) were 79% and 11.36% for lentil biomass prediction, respectively. Our results generally showed that the neural net- work approach could be used effectively in lentil yield prediction under weed interference conditions

DIFFERENTIAL TOLERANCE OF PUMPKIN SPECIES TO BENTAZON, METRIBUZIN, TRIFLURALIN, AND OXYFLUORFEN

<div><p>ABSTRACT Response of pumpkin species including Cucurbita pepo convar. Pepo, Cucurbita moschata Duch, Cucurbita pepo, Cucurbita maxima, and Lagenaria vulgaris to bentazon, trifluralin, metribuzin, and oxyfluorfen was evaluated in Outdoor pot experiments in 2014 and 2015. Different postemergence doses (bentazon and oxyfluorfen) and preplant incorporated (metribuzin and trifluralin) herbicides were evaluted on pumpkin species at various growth stages. Results showed that the sensitivity of pumpkins species to applied herbicide varied greatly among tested species. On overall, dry weights of Cucurbita spp. were reduced by 12.50%, 48.60%, 23%, and 73.13% when pumpkin was treated with trifluralin, metribuzin, bentazon and oxyfluorfen, respectively. Pumpkin crops were not tolerant of metribuzin and oxyfluorfen and plants showed injures. Results indicated that trifluralin and bentazon have the potential for possible application in pumpkin particularly when broadleaf weeds are dominant.</p></div