A two parameter model for prediction of crop loss by weed competition from early observations of relative leaf area of the weeds

Abstract

SummaryThe recently introduced empirical model for early prediction of crop loss by weed competition based on the relative leaf area of the weeds shortly after crop emergence (Kropff & Spitters, 1991), assumes a maximum yield loss of 100% at high weed infestations. This is biologically not realistic. If weeds have a shorter life cycle than the crop, when they emerge much later than the crop or when they are unable to overtop the crop, maximum yield loss at high weed infestations is expected to be less than 100%. A two parameter model is introduced in this paper that accounts for a variable maximum crop yield loss by weed competition. The parameters are the "relative damage coefficient" q, and a parameter that describes the maximum yield loss caused by the weeds (m). The one and two parameter models were evaluated with data on the effects of weeds on rice, sugarbeet and tomato.Both models were able to describe the data on the effect of different weed densities and periods between crop and weed emergence fairly well. The introduction of the second parameter resulted in a significantly better description of observed data in five out of nine datasets. The value of the parameter q depends on the time of observation of the relative leaf area. The change in the value of q in time could be estimated from the difference in relative growth rate of the species. The accuracy of this estimation is strongly determined by the variability in the relative growth rate of the leaf area of single plants. Possibilities for scientific and practical application of the model are discussed.

Predicting Yield Losses in Rice Mixed-Weed Species Infestations in California

“…Although Model 2 fit better overall, the increase in q values may lead to overestimation of YL at low weed relative cover. Kropff et al (1995) observed a better fit with Model 2 when evaluating the fit for barnyardgrass and heartshape false pickerelweed [Monochoria vaginalis (Burm.f.) C. Presl ex Kunth] in transplanted rice.…”

“…The q coefficient for barnyardgrass was 1.05 for the same model. The Kropff et al (1995) study was conducted in transplanted rice, which may explain the lower q coefficients, since the rice was already large when weed emergence began, giving the rice a competitive advantage over the weeds.…”

“…The simplest of the models, the hyperbolic models, use only one measurement, such as plant density, relative leaf area, or relative cover, to predict losses (Cousens 1985;Kropff and Lotz 1993;Kropff and Spitters 1991;Kropff et al 1995). Relative leaf area has been shown to be one of the best predictors of yield loss when evaluated under field conditions due to the fact that unlike plant density, it accounts for the relative competitive ability of the weeds (Ali et al 2013).…”

Improving crop competitive ability using allelopathy — an example from rice

“…First, these traits can be morphological, or physiological traits linked with plant canopy establishment such as early vigour, plant height, growth rate, biomass, leaf area, leaf angle and expansion, tillering capacity, etc. (Grace 1990, Krop et al 1995, Caton et al 1999, Moolsri et al 1999, Ranasinghe and Crabtree 1999. Such traits adding to competition, are often negatively correlated with yield and are therefore seldom primary selection criteria in breeding programmes.…”

Yield Response of Red Pepper by Densities of D. ciliaris and A. patulus in Eco-firendly Cultivated Field

“…Crop yield as a function of weed density was predicted by using a rectangular hyperbola, and their economic threshold levels were determined by using the equation developed by Cousens (1987). The red pepper yield loss models of weeds were predicted as y=304.7/(1+0.063x), R 이러한 잡초 발생으로 인한 작물 수량 감소 정도는 수 학적인 모델식을 이용하여 예측 하려는 노력이 다양하게 시도되었으며 (Cousens, 1985;Kropff and Spitters, 1991;Kropff et al, 1995;Berti and Sattin, 1996), 이러한 모델 들 가운데서 Cousens ( …”