Using PhenoCams to track crop phenology and explain the effects of different cropping systems on yield,Agricultural Systems

当前位置： X-MOL 学术 › Agric. Syst. › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Using PhenoCams to track crop phenology and explain the effects of different cropping systems on yield
Agricultural Systems ( IF 6.1 ) Pub Date : 2021-11-13 , DOI: 10.1016/j.agsy.2021.103306
Yujie Liu ₁ , Christoph Bachofen _{1,

2} , Raphaël Wittwer ₃ , Gicele Silva Duarte ₁ , Qing Sun ₁ , Valentin H. Klaus ₁ , Nina Buchmann ₁

Affiliation

CONTEXT

Crop phenology integrates information of how environmental drivers and management practices affect plant performance and crop yield. However, little is known about the impact of cropping systems (CS) on crop phenology and how this relates to differences in yield.

OBJECTIVES

We assessed the applicability of PhenoCams to track crop phenology, how four CS, i.e., organic vs. conventional farming with either intensive or conservation (no/reduced) tillage affect the phenology of a pea-barley mixture and winter wheat, how crop phenology is related to harvest characteristics, e.g., grain yield and total N uptake, and explains CS effects on these characteristics.

METHODS

We used time-lapse cameras (PhenoCams) to track vegetation changes in the two crops and extracted the green chromatic coordinate (GCC) to estimate different phenological metrics, i.e., dates with major changes in GCC (PhenoTimePoints), the duration between those (PhenoPhases), and the rate of increasing or decreasing GCC (PhenoSlopes). We assessed how phenological metrics were affected by different CS, and related phenological metrics to harvest characteristics.

RESULTS AND CONCLUSIONS

CS significantly affected phenological metrics of both crops, with less pronounced effects in the unfertilized pea-barley mixture compared to the fertilized winter wheat, and stronger effects for early-season than for late-season PhenoTimePoints. For winter wheat, organic compared to conventional farming caused an initial growth lag (up to 7 days) and a shorter duration (approximately 10 days) of the period of stable GCC. Winter wheat in reduced/no-tillage systems showed a tendency of delayed phenology (up to 5 days) compared to intensive tillage. While phenological metrics explained harvest characteristics of winter wheat well, they were almost unrelated to those of pea-barley, most likely because pea-barley yields were similar among CS. For winter wheat, effects of CS on harvest characteristics could be well explained by phenological metrics (max. R² = 0.9). Thus, we demonstrated that delayed phenology acted as an important factor causing lower yield in organic compared to conventional farming.

SIGNIFICANCE

PhenoCams are valuable tool for high-resolution temporal monitoring of crop phenology. As different CS have been proposed as a tool for climate change adaptation, we suggest that the effects of CS on crop phenology need to be considered as they may impact yield via changes in crop phenology, particularly in organic agriculture.

中文翻译：

使用 PhenoCams 跟踪作物物候并解释不同种植系统对产量的影响

语境

作物物候整合了环境驱动因素和管理实践如何影响植物性能和作物产量的信息。然而，人们对种植系统 (CS) 对作物物候的影响以及这与产量差异的关系知之甚少。

目标

我们评估了 PhenoCams 跟踪作物物候的适用性，四种 CS，即有机与传统耕作，集约化或保护性（无/减少）耕作如何影响豌豆 - 大麦混合物和冬小麦的物候，作物物候如何与收获特性有关，例如谷物产量和总氮吸收量，并解释了 CS 对这些特性的影响。

方法

我们使用延时相机 (PhenoCams) 来跟踪两种作物的植被变化，并提取绿色色度坐标 (GCC) 来估计不同的物候指标，即 GCC 发生重大变化的日期 (PhenoTimePoints)，这些之间的持续时间 (PhenoPhases) )，以及 GCC (PhenoSlopes) 增加或减少的速率。我们评估了物候指标如何受到不同 CS 的影响，以及相关的物候指标对收获特征的影响。

结果和结论

CS 显着影响两种作物的物候指标，与受精冬小麦相比，未受精豌豆 - 大麦混合物的影响不那么明显，早季的影响比晚季的 PhenoTimePoints 强。对于冬小麦，与传统耕作相比，有机耕作导致初始生长滞后（最多 7 天）和更短的 GCC 稳定期持续时间（约 10 天）。与密集耕作相比，减耕/免耕系统中的冬小麦显示出物候延迟（最多 5 天）的趋势。虽然物候指标很好地解释了冬小麦的收获特征，但它们与豌豆大麦的收获特征几乎无关，很可能是因为豌豆大麦的产量在 CS 中相似。对于冬小麦，R ² = 0.9）。因此，我们证明，与传统农业相比，延迟物候是导致有机农业产量较低的重要因素。