Farms.com Home   News

Temporal Crop Diversity Stabilizes Agricultural Production

Securing food supplies around the globe is a major challenge facing humanity, especially in light of the predicted increase in the world's population to almost ten billion people by 2050 and the effects of climate change. Greater crop diversity in agriculture is seen as a stabilising factor for food security. Yet crop diversity alone is not sufficient. In an article for Nature, a team of researchers coordinated by the Helmholtz Centre for Environmental Research (UFZ) argue that it is also essential that crops differ in their temporal production patterns.

Crop diversity is a key factor in securing agricultural production. Having a wider variety of crops reduces the risk of total harvest failure when certain crops are affected by plant diseases and protects against poor harvests resulting from extreme weather events, such as droughts, or pest infestation. "However, asynchrony is at least equally important in securing production," says Lukas Egli, UFZ agroecologist and first author of the study. Differences in the temporal sequence in which crops are sown and harvested on arable land or the variation in phenology, i.e. differing development over time during the vegetation period, are both examples of factors that lead to greater asynchrony. "The more heterogeneously crops are distributed in time and respond to the effects of extreme events, natural disasters and economic crises, the less the agricultural production of a country as a whole will fluctuate," says Egli. For example, when different types of crops become ready to harvest at the same time this increases the likelihood of the entire harvest being destroyed in a storm or flood. Asynchrony prevents such total failure, for instance by varying sowing and harvesting times, growing crops with different climate and cultivation requirements and mixed cropping.

Click here to see more...

Trending Video

Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.