Computer Simulation of Pineapple Growth, Development and Yield

Abstract

Fruit yield and harvest date of pineapple {Amnas comosus (L.) Merr.] are difficult to predict. Site-specific studies improve the predictability at one location but usually cannot be generalized to other environments. This study examined the effects of plant population density (PPD) and planting date (PD) on pineapple growth and fruiting and the data were used to develop a pineapple growth simulation model. ‘Smooth Cayenne’ pineapple was planted at Kunia, Hawaii; the crop was drip-irrigated. PPDs ranged from 2.61 to 12.81 plants m-2 and PDs were June and August 15, and October 18, 1989. Flower development was forced with ethylene on September 18, 1990. Leaf emergence rate was constant until 200 days after planting (DAP) and then decreased 0.9 leaves 1000-°C-day-1 with each increase in PPD of one plant m-2. Dry weight per plant decreased as PPD increased and as PD was delayed. Light interception reached 95% at a leaf area index of 4 to 5, which was attained at 350 DAP at 12.81 plants m-2 and later as PPD decreased. Dry matter partitioning (DMP) to leaves and stem during vegetative growth was not affected by PPD or PD. DMP to stem during fruiting decreased linearly and DMP to fruit increased curvilinearly as PPD increased and as PD was delayed. Fruit harvest date was delayed seven days for each PPD increase of 2.5 plants m-2 from 2.61 to 12.81 plants m-2. Fruit yield was asymptotically related to PPD; the economic yield-PPD relationship was parabolic. There was no effect of PD on rate of leaf emergence or fruit development. A pineapple simulation model (ALOHA-Pineapple) was developed using data from the experiment and the literature. ALOHA-Pineapple is process-oriented and incremented daily. It simulates the effects of PPD, PD, plant size at planting and forcing, and weather on crop growth and yield. When ALOHA-Pineapple was validated with data from eleven plantings in four locations in Hawaii, pineapple growth, fruit development and yield was simulated with reasonable accuracy although harvest date and yield were over- and under-predicted in some locations. ALOHA-Pineapple has potential to serve as a frame-work for pineapple research and as a decision aid for farmers.