Category Archives: Plant Health

Monitoring Variability in Peas

Peas are one crop that has huge variation. It’s hard to know if the crop will yield four tonnes per hectare or twelve. Even within small sampling plots we measured yields less than 4 t/ha and greater than 13 t/ha.

Our peas were planted into wet soil and had cold weather afterwards. Then they were savaged by pigeons. So right from the start there was variation. There were bald patches, slow germinating plants and plants with growing tips nipped out.

Counting the number of peas in 1m2 to assess paddock population. Repeating measurements shows variability.
Counting the number of peas in 1m2 to assess paddock population. Comparing repeated measurements allows statistical variability to be calculated.

We put some cover cloth over plants and observed different growth. After three weeks we removed the covers and could see difference. We got a sensor that measures ground cover and compared covered and uncovered areas. There was as much as 50% difference with covered plants much bigger. We think some of the difference is pigeon related. But maybe the covers also have other effects.

After crop cover was removed, greater growth and fuller ground cover was obvious
After crop cover was removed, greater growth and fuller ground cover was obvious

We visited a number of pea crops in Central Hawke’s Bay. We saw the same variability in young crops and old. The rate of maturation is critical for vining peas as they have to peak the day (hour?) they are harvested. We’ve identified condensed flowering as a target for pea crops. We want flowering to start and stop in a short period, and pods to fill evenly to be similar maturity for harvest. In variable paddocks (uneven soils, dry areas) flowering can start and finish at different times. A long period means later pods will still be filling while the first are already getting past their prime.

This crop shows areas of delayed and advanced flowering. All is to be harvested at the same time so some will be ready and some not.
This crop shows areas of delayed and advanced flowering. All is to be harvested at the same time so some will be ready and some not.

We had cool conditions at the MicroFarm and think this extended the flowering period. We could see pods filling while new flowers were starting to bloom.

Variation occurs on a single plant when long flowering times see pods filling while new flowers are opening.
Variation occurs on a single plant when long flowering times see pods filling while new flowers are opening.

The variability is a problem at harvest. Setting beater speed is a difficult task when the TR range is wide; hard enough to get tougher pods open yet soft enough to save the tenderest young peas. The problem is very obvious then, but it started long ago.

Peas taken and hand sorted from a single sample from the harvester - those on the left are mature, those on the right too young and damaged.
Peas taken and hand sorted from a single sample from the harvester – those on the left are mature, those on the right too young and damaged.

Monitoring Variability in Onions

Our first MicroFarm onion crop is extremely variable. The view below was taken from on the linear move irrigator, a useful vantage point

Variability is obvious when viewed from the irrigator
Variability is obvious when viewed from the irrigator

We want to measure variability so we can better assess it. If we can measure objectively we can make better decisions. We are interested in spatial variability and temporal variability.

The image above shows spatial variability: some parts of the paddock are better than others. We want to understand why some plants have done quite well, while others have done very poorly. If we can identify patterns, it can help us identify causes.

There are two patterns showing up in the image. There seems to be a large area where growth is poor. Perhaps that is a lower, wetter area? We can also see that every third bed is stronger than those on either side. That pattern is quite strong across the whole paddock and matches planting pattern from our three bed planter.

We wanted to map our crop so we could look for more patterns. We took a GPS connected sensor that measures the amount of ground cover and went up and down the beds.

CropCoverMap
Ground cover map of MicroFarm onion crop from data collected in early December

In the image above, the sensor data is displayed as a colour scheme. Green is highest ground cover (the biggest plants and most continuous planting). Red is lowest ground cover (small plants or larger gaps between plants or both). We used a cheaper GPS without correction so our bed readings have strayed off line. But even still, we can see the same pattern as in the photo above.

Will this pattern reappear in future years? Temporal variability seeks to understand how crop performance changes from year to year. If we can identify “always high”, “always low” and “sometimes high/sometimes low” areas we can develop management strategies to suit. Sensor based mapping is one of the best ways to identify such zones.

Crop covers laid on onions and peas

Following the lead of Dr Charles Merfield at the BHU Future Farming Centre at Lincoln, we’ve laid some trial crop covers at the MicroFarm.

Crop covers laid over onions and peas at the MicroFarm
Crop covers laid over onions and peas at the MicroFarm

Merf first used the covers in an attempt to control the Tomato Potato Psyllid on biologically grown potatoes. His first season trial showed unexpected benefits including greatly reduced potato blight. You can view Merf discussing the trials on Rural Delivery here>

Scott Lawson has been using the covers at True Earth Organics in Hawke’s Bay. His observations are of significant benefit on a number of crops. He bought cloth to cover potatoes, a crop he struggled to produce one TPP arrived. After potatoes, the cloth was going back in the shed but instead he put it on to other crops and has seen benefits in those as well.

We have placed 6 x 8m covers on our onions in Paddocks 1 & 2. We also put covers on to our peas crops, largely to gauge the effect of pigeon attacks at germination.