The number of ears per unit ground area (ear density) is one of the main agronomic yield components in determining grain yield in wheat. A fast evaluation of this attribute may contribute to monitoring the efficiency of crop management practices, to an early prediction of grain yield or as a phenotyping trait in breeding programs. Currently the number of ears is counted manually, which is time consuming. Moreover, there is no single standardized protocol for counting the ears. An automatic ear-counting algorithm is proposed to estimate ear density under field conditions based on zenithal color digital images taken from above the crop in natural light conditions. Field trials were carried out at two sites in Spain during the 2014/2015 crop season on a set of 24 varieties of durum wheat with two growing conditions per site. The algorithm for counting uses three steps: (1) a Laplacian frequency filter chosen to remove low and high frequency elements appearing in an image, (2) a Median filter to reduce high noise still present around the ears and (3) segmentation using Find Maxima to segment local peaks and determine the ear count within the image. The results demonstrate high success rate (higher than 90%) between the algorithm counts and the manual (image-based) ear counts, and precision, with a low standard deviation (around 5%). The relationships between algorithm ear counts and grain yield was also significant and greater than the correlation with manual (field-based) ear counts. In this approach, results demonstrate that automatic ear counting performed on data captured around anthesis correlated better with grain yield than with images captured at later stages when the low performance of ear counting at late grain filling stages was associated with the loss of contrast between canopy and ears. Developing robust, low-cost and efficient field methods to assess wheat ear density, as a major agronomic component of yield, is highly relevant for phenotyping efforts towards increases in grain yield. Although the phenological stage of measurements is important, the robust image analysis algorithm presented here appears to be amenable from aerial or other automated platforms.

SUMMARY: A collection of 26 wheat genotypes widely grown in Spain during the 20th century was evaluated in eight contrasting environments in order to quantify breeding achievements in yield and associated traits. From 1930 to 2000, yield increased at a rate of 35·1 kg/ha/yr or 0·88%/yr, but estimations of relative genetic gain (RGG) were environment-dependent. RGG estimated for yield were positively associated with the average minimum daily temperatures from sowing to heading in the testing environments (R² = 0·81;P < 0·01). The number of grains/spike and the number of spikes/m²increased at a rate of 0·60%/yr and 0·30%/yr, respectively, while grain weight remained unchanged. The present study detected two main episodes of yield improvement during the century. The first one coincided with the introduction, during the 1950s, of the first improved cultivars derived from intra-specific crosses, which increased the yield of landraces by 30% due to an increase ofc. 58% in the number of grains/spike, accompanied by a 16% reduction in grain weight. These initial cultivars (termed ‘old-bred’ in a previous study by Sanchez-Garciaet al. 2012) exhibited a higher harvest index (HI), increased from 0·25 to 0·40, but maintained the same aboveground biomass at maturity as the landraces (despite reducing both plant height and the number of tillers/plant) due to increases in the proportion of tillers bearing spikes. The second yield gain occurred after the introduction, in the early 1970s, of semi-dwarf germplasm from CIMMYT (International Maize and Wheat Improvement Centre) and some French cultivars. This new germplasm further reduced plant height, improved HI up to 0·45 and increased the number of tillers/plant while maintaining their rate of fertility, thus resulting in a yield gain ofc. 37%. The cultivars released during the last decade of the century did not contribute to significant yield improvements.

Early prediction of crop yield can be an important tool for identifying promising genotypes in breeding programmes. To assess whether measurements of canopy reflectance at given stages of development could be used for yield forecasting and to identify the most appropriate indices, locations and growth stages for durum wheat yield assessment, nine field experiments, each including 20 or 25 durum wheat (Triticum turgidum L. var durum) genotypes, were carried out under a wide range of Mediterranean conditions. Canopy reflectance was recorded with a portable field spectroradiometer at several times from booting to physiological maturity, and nine indices were further derived. Grain yield was measured at harvesting. The results indicated that milk-grain stage was the most appropriate developmental stage for yield assessment. However, some indices were also sensitive to yield variations when determined at anthesis or even heading or booting. The capacity of spectral reflectance indices to forecast grain yield increased on locations that allowed genotypes to express their yield potentiality. Reflectance at 550 nm (R550), water index (WI), photochemical reflectance index (PRI), structural independent pigment index (SIPI), normalized difference vegetation index (NDVI) and simple ratio (SR) explained jointly a 95.7% of yield variability when all the experiments were analysed together, 92% being explained by R550. When regression analyses were carried out separately for each experiment, spectral reflectance indices explained from 17.3% to 65.2% of total variation in yield, and the indices that best explained differences in yield were experiment-dependent. Our data suggest that reflectance at 680 nm (R680), WI and SR may be suitable estimators of durum wheat grain yield under Mediterranean conditions, when determined at milk-grain stage.

Detecting and exploiting genetic variation in biomass accumulation is of great importance for increasing wheat yield when the harvest index is close