Effects of measurement methods and growing conditions on phenotypic expression of photosynthesis in seven diverse rice genotypes

Introduction

Light response curves are widely used to quantify phenotypic expression of photosynthesis by measuring a single sample and sequentially altering light intensity within a chamber (sequential method) or by measuring different samples that are each acclimated to a different light level (non-sequential method). Both methods are often conducted in controlled environments to achieve steady-state results, and neither method involves equilibrating the entire plant to the specific light level.

Methods

Here, we compare sequential and non-sequential methods in controlled (greenhouse), semi-controlled (plant grown in growth chamber and acclimated to field conditions 2-3 days before measurements), and field environments. We selected seven diverse rice genotypes (five genotypes from the USDA rice minicore collection: 310588, 310723, 311644, 311677, 311795; and 2 additional genotypes: Nagina 22 and Zhe 733) to understand (1) the limitations of different methods, and (2) phenotypic plasticity of photosynthesis in rice grown under different environments.

Results

Our results show that the non-sequential method was time-efficient and captured more variability of field conditions than the sequential method, but the model parameters were generally similar between two methods except the maximum photosynthesis rate (Amax). Amax was significantly lower across all genotypes under greenhouse conditions compared to the growth chamber and field conditions consistent with prior work, but surprisingly the apparent quantum yield (α) and the mitochondrial respiration (Rd) were generally not different among growing environments or measurement methods.

Discussion

Our results suggest that field conditions are best suited to quantify phenotypic differences across different genotypes and nonsequential method was better at capturing the variability in photosynthesis.

Evaluating Greenhouse Gas Emissions and Climate Mitigation Goals of the Global Food and Beverage Sector

The dramatic increase in greenhouse gas (GHG) emissions by humans over the past century and a half has created an urgency for monitoring, reporting, and verifying GHG emissions as a first step toward mitigating the effects of climate change. Fifteen percent of global GHG emissions come from agriculture, and companies in the food and beverage industry are starting to set climate goals. We examined the GHG emissions reporting practices and climate goals of the top 100 global food and beverage companies (as ranked by Food Engineering) and determined whether their goals are aligned with the science of keeping climate warming well below a 2°C increase. Using publicly disclosed data in CDP Climate reports and company sustainability reports, we found that about two thirds of the top 100 global food and beverage companies disclose at least part of their total company emissions and set some sort of climate goal that includes scope 1 and 2 emissions. However, only about half have measured, disclosed, and set goals for scope 3 emissions, which often encompass about 88% of a company's emissions across the entire value chain on average. We also determined that companies, despite setting scope 1, 2, and 3 emission goals, may be missing the mark on whether their goals are significantly reducing global emissions. Our results present the current disclosure and emission goals of the top 100 global food and beverage companies and highlight an urgent need to begin and continue to set truly ambitious, science-aligned climate goals.

The detection of single cells forming antibodies to defined epitopes on insulin

A solid-phase immunoenzymatic technique was modified to permit the detection and enumeration of antibody-secreting cells recognizing the amino or carboxy terminal of the insulin B chain. The procedure involves coating well surfaces with avidin and binding insulins specifically labelled with biotin at the B1 or B30 residue. On day 15 after immunization with human insulin, 20 outbred NMRI mice had generated cells secreting anti-insulin antibodies. The recognition of B1- or B30-related epitopes differed between individuals, suggesting that there was genetic determination of the epitopes expressed early in the immune response. The method can be used to find strains of mice with a preferential immune response to defined areas on the surface of small peptide molecules. Such strains could then be used to produce specific monoclonal antibodies.