fit a count-response GLM, initially a Poisson model with log link, or a negative-binomial model if the data are overdispersed;
allow nonlinear predictor effects, for example quadratic terms or smooth functions of weight and width, with model selection or validation used to control complexity.
The first addresses discreteness and mean-dependent variance; the second addresses systematic lack of fit in the conditional mean.